A Green Streetscapes Framework for Climate Change Adaptation in Tropical Jakarta, Indonesia

Master Thesis

Integrating Grey-Green Infrastructure: A Green Streetscapes Framework for Climate Change Adaptation in Tropical Jakarta, Indonesia Master Thesis Draft

Submitted by: Ike Larasayu Raymond B.Sc Matriculation No.: 3377840 Master of Infrastructure Planning (MIP)

First Examiner: Univ.-Prof. Dr. rer. nat. Leonie Fischer Second Examiner: Dr. rer. nat. Hans-Georg Schwarz-von Raumer

10. December 2020

Universität Stuttgart Institut fur Landschaftplanung und Ökologie (ILPÖ)

Summary

Summary Currently, developing countries are competing in constructing more and more grey infrastructure development to meet the demands of the rapidly growing population.

Based on UN DESA, the population of the urban area will continue to grow and be predicted to reach 2.5 billion by 2050, hence urban areas are progressively burdened by the expansion of residential areas, offices, commercials, industrials, and numerous kinds of infrastructure expansion such as roads (e.g. highway and bridges), transportation services (e.g. transit area, railway, harbor, airport), energy, water management, and waste treatment. Along with more intense development in the city, many environmental values are subordinated to meet the city’s physical infrastructure needs. Eventually, urban areas become more deprived of their ecological function and prone to various kinds of climate change-related disasters. This kind of thing also happens in Jakarta, Indonesia, where the proportion of green open spaces has significantly decreased due to rapid urban inhabitants growth. The deficiency of urban greening can lead to various kinds of negative impacts, such as floods and extremely increased temperature of a city compared to its surrounding rural area. Unfortunately, Jakarta itself does not yet have strict and strong regulations to maintain and monitor the availability of green open spaces that can be seen from how small the proportion of green open spaces available in each administrative area. However, providing green open spaces to restore the city’s ecological function in a densely populated area is not a simple issue. Therefore, the utilization of grey and green infrastructure integration can be one of the solutions to solve this problem. Unfortunately, research and studies on urban greening integration with established grey infrastructure such as streets and other impervious urban areas have only been done in developed countries, such as the USA, Australia, and European countries. Hence, this thesis aims to review successfully earlier retrofitting green infrastructure projects and frameworks on the street-level and examine an area in Jakarta that is conflicted and affected by climate change through desktop screening evaluation and later expected to carry out the development of green infrastructure integration on streetscape level based on the city characteristics.

© ILPÖ 2020

i

Declaration of Authorship

Declaration of Authorship I hereby declare that the thesis submitted is my unaided work. All direct or indirect sources used are acknowledged as references. This paper or any parts of it were not previously presented to another examination board and have not been published.

I confirm that the printed version and the electronic copy I provided are identical in all parts.

Ehrenwörtliche Erklärung Ich erkläre hiermit ehrenwörtlich, dass ich die vorliegende Arbeit selbständig angefertigt habe. Die aus fremden Quellen direkt und indirekt übernommenen Gedanken sind als solche kenntlich gemacht. Die Arbeit oder Teile daraus wurden weder einer anderen Prüfungsbehörde vorgelegt noch veröffentlicht. Ich bestätige, dass die gedruckte und die elektronische Fassung der Arbeit in allen Teilen identisch sind.

Date: 15.10.2020

Signature: _______________________________________________

Ike Larasayu Raymond

© ILPÖ 2020

iii

Table of Content

Table of Content Summary

i

Declaration of Authorship

iii

Table of Content

v

List of Figures

vii

List of Tables

viii

Abbreviation

ix

1

1

Introduction

1.1

Background

1

1.2

Problem statement

1

1.3

Objectives

3

1.4

Research questions

3

1.5

Research methodology

4

1.6

Scope and limitation

5

2

Theoretical Framework

7

2.1

Urban area and climate challenges

7

2.2

Green-grey integration: streets as an opportunity for UGI

8

2.2.1

Green infrastructure streetscape typology

2.2.2

Performance and limitation

19

2.2.3

Existing green streetscape framework review

21

2.3

Urban challenges for developing good green streetscape approaches

8

24

2.3.1

Exposure to climate change

24

2.3.2

Social vulnerability

24

2.3.3

Urban characteristics

24

Case study area: Jakarta

27

3 3.1

Introduction

27

3.1.1

Jakarta’s urban heat island

28

3.1.2

Jakarta’s urban flooding

29

3.1.3

Jakarta’s policy strategies towards the green city

31

© ILPÖ 2020

v

Table of Content

3.2

Methodology on green streetscape prioritization screening

31

3.2.1

UHI hot spots recognition

32

3.2.2

Flood hazard recognition

35

3.2.3

Sensitive population distribution

37

3.2.4

Conceptual solution for retrofit application on street-scale

37

3.3

The graphical spatial analysis result

37

3.3.1

UHI hot spots recognition

37

3.3.2

Flood hazard recognition

41

3.3.3

Sensitive population distribution

45

4

Conceptual strategy for retrofit application on a street scale

49

4.1

Introduction

49

4.2

Retrofitting based on the green streetscape’s roles and benefits

50

4.2.1

Heat mitigation

50

4.2.2

Flood mitigation

54

4.2.3

Integrated solution

56

4.3

Future challenges

56

5

Conclusion

59

6

References

61

7

Appendix I.

71

© ILPÖ 2020

vi

List of Figures and Tables

List of Figures Figure 1. Urban greenery loss within Jakarta ................................................................ 2 Figure 2. Thesis research methodology ........................................................................ 4 Figure 3. Green streetscape elements limitation ......................................................... 20 Figure 4. Reconstruction of the concepts of green streetscape priority analysis ......... 25 Figure 5. Existing green space in Jakarta ................................................................... 27 Figure 6. Observation on Jakarta air temperatures by month in 2018 ......................... 28 Figure 7. The difference in Jakarta’s average air temperature in 2000 and 2019 ........ 28 Figure 8. Jakarta's monthly average of rainfall data 2009-2018 (mm) ......................... 30 Figure 9. Map of flood hazard in Jakarta based on events in 2013, 2014, and 2015 ... 30 Figure 10. Jakarta administrative boundaries ............................................................. 32 Figure 11. LST retrieval based on Lansat 8 OLI/TIRS image processing .................... 33 Figure 12. Identification of flood hazard workflow ....................................................... 36 Figure 13. Jakarta’s NDVI value ................................................................................. 38 Figure 14. LST retrieval for Jakarta based on Landsat 8 imagery process .................. 38 Figure 15. Substracted mean LST value based on respective subdistrict boundary .... 39 Figure 16. UHI score derived from Getis-Ord-Gi* analysis .......................................... 40 Figure 17. UHI cluster and outlier analysis (Local Moran I) based on subdistrict’s temperature ................................................................................................................ 41 Figure 18. DEM of Jakarta .......................................................................................... 42 Figure 19. Jakarta’s TWI distribution........................................................................... 42 Figure 20. Substracted TWI value based on subdistrict boundary using zonal statistics ................................................................................................................................... 43 Figure 21. TWI score derived from Getis-Ord-Gi* analysis.......................................... 44 Figure 22. Percentage of flood-prone areas in highly affected subdistricts within the year 2013-2017 in percentage ............................................................................................ 44 Figure 23. Number of incredibly young age population within Jakarta’s subdistrict ..... 46 Figure 24. Number of incredibly old age population within Jakarta’s subdistrict .......... 46 Figure 25. Very young population score derived from Getis-Ord-Gi* analysis ............. 47 Figure 26. Elderly population score derived from Getis-Ord-Gi* analysis .................... 47 Figure 27. Kapuk subdistrict land use 2019 ................................................................ 49 Figure 28. Kapuk subdistrict’s neighborhood division and its thermal stress analysis . 51 Figure 29. Recommendation on street trees planting in St. Kapuk Kayu Besar........... 51 Figure 30. Stormwater tree in Louisville ...................................................................... 51 Figure 31. Recommendation on road median planter planting in St. Pedongkelan Raya ................................................................................................................................... 52 Figure 32. Stormwater planter in Portland................................................................... 52 Figure 33. Recommendation on permeable parking lot in St. Royale Boulevard ......... 52 Figure 34. Permeable surface in Atlanta ..................................................................... 52 Figure 35. Recommendation on small-scale vertical greening in St. Masjid AlMunawarah................................................................................................................. 53 Figure 36. Green Village in East Jakarta..................................................................... 53

© ILPÖ 2020

vii

List of Figures and Tables

Figure 37. Kapuk subdistrict’s affected neighborhood on flood inundation 2013-2015 54 Figure 38. Recommendation on rain garden establishment in St. Royale Boulevard... 54 Figure 39. Traffic circle in Berkeley ............................................................................. 54 Figure 40. Recommendation on continuous vegetated swale in St. Pedongkelan Raya ................................................................................................................................... 55 Figure 41. Bioswale for street integration .................................................................... 55 Figure 44. Recommendation on pervious pavement installation in St. Rusun BCI Raya ................................................................................................................................... 56 Figure 45. Example on pervious pavement ................................................................. 56

List of Tables Table 1. Evidence-based evaluation and findings on street trees .................................. 9 Table 2. Evidence-based evaluation and findings on rain garden/bioretention planters ................................................................................................................................... 11 Table 3. Evidence-based evaluation and findings on bioswales .................................. 13 Table 4. Evidence-based evaluation and findings on permeable pavement ................ 14 Table 5. Green street element practice placement ...................................................... 16 Table 6. Case study and benefits on vertical greening implementation ....................... 17 Table 7. Summary of green streetscape infrastructure elements objectives ................ 20 Table 8. Green infrastructure integration to streets framework from countries around the world ........................................................................................................................... 21 Table 9. Subdistricts that affected for more than 50% of its area by high flood hazard level for 5 years (2013-2017) ...................................................................................... 45 Table 10. Subdistricts with hot spot and very hot spot cluster result for two aspects only combination (secondary areas) and three complete aspects (primary or priority area) 48 Table 11. Sites within Kapuk that hold potential for green streetscapes recommendation for heat mitigation ....................................................................................................... 51 Table 12. Sites within Kapuk that hold potential for green streetscapes recommendation for flood mitigation ...................................................................................................... 54

© ILPÖ 2020

viii

Abbreviation

Abbreviation The following abbreviations are used in this thesis: GSV = Google street view LST = Land surface temperature NDVI = Normalized difference vegetation index NDBI = Normalized difference built-up index OGS = Open green space UGS = Urban green system UHI = Urban heat island VGS = Vertical green system

© ILPÖ 2020

ix

Introduction

1 Introduction 1.1

Background

Developing countries are experiencing a rapidly growing rate of population, especially in urban areas. United Nations predicted that approximately 68% of the world population will reside in urban areas in 2050 (UN DESA, 2018). Urbanization is an inevitable process that leads to an increase in energy use, intensification of the built-up area as well as reduction of urban greenery (Pitakasari et al., 2010). Many emerging cities are placing more focus on expanding their grey infrastructure related to human-engineered service distribution such as wastewater treatment plants, pipelines, and reservoirs to cater to population demand. Often these grey infrastructures are designed as impervious surface and only offers stormwater runoff management— leaving all hazardous pollutants behind (Lukes & Kloss, 2008) which creates drawbacks and by function, it completely neglects the environmental aspects. Consequently, urban areas are more prone to climate change impacts such as urban flooding and extreme temperature increase due to their ecological capacity loss. Therefore, the integrated planning of green elements within the grey infrastructures is considered important.

Urban green infrastructure (UGI) is described as a network that connects natural and man-made green space that preserves biodiversity, provides ecosystem services and aesthetic values as well as benefits people’s wellbeing (Benedict & MacMahon, 2002).

Various components of UGI can be observed such as parks, urban gardens, urban forest, cemeteries, green roofs, green façade. Multifunctional green streetscapes design including roadside trees, flower beds, and tree pits. While providing a brand-new green infrastructure in vacant land is quite an obstacle for the dense urban area, incorporating transportation planning in the process of recognizing grey sites (such as streets and roads) that are suitable for green infrastructure development could be an option (BfN, 2017). Considering that streets and roads share a large amount of proportion in a densely built-up city, almost 25% (UACD, 2010), the application of green streets can be taken as an opportunity. Although green street infrastructure could be integrated into a broad range of designs, it is aiming for similar goals and multifunctional benefits: “…promote sustainable urban ecosystems by increasing vegetation with greater biodiversity, improving well-being by promoting more green space, and climate resiliency by treating stormwater and urban heat island effects.” (Im, 2019)

1.2

Problem statement

As cities striving from the intense stress of uncontrolled population growth and urban densification, streets could be an essential part of making cities more livable and sustainable as the compensation for green areas loss (Maria Rinaldi & Tan, 2019). In large populous developing cities like Jakarta and Mumbai— they possess even greater tasks and difficulties to implement a successful blue and green infrastructure (BGI).

© ILPÖ 2020

1

Introduction

Therefore, the implementation of BGI with a small scale and non-centralized approach is considered to be more suitable for this kind of city context (Dreiseitl & Wanschura, 2016).

Jakarta itself is one of the rapidly growing megacities in Southeast Asia with a total area of 662.3 km2, an average population density of 15,234 inhabitants/km2, and 48,952 inhabitants/km2 at its peak with a tropical climate and high precipitation. Despite the stipulation of acquiring 30% green open space (GOS), consists of 20% public and 10% private, from the total administrative area (UU No. 26 Year 2007 Spatial Planning, 2007), figure 1 shows that Jakarta green space has decreased from 24% to 9.9% of city area between 1989 and 2013 (Dreiseitl & Wanschura, 2016). This makes Jakarta vulnerable to rising temperature and urban flash flooding. A study of land-use changes in Jakarta observed that around 49.7% of GOS was transformed into built-up areas between 20002012 which leads to a long-term rise in the average temperature and the occurrence of urban heat island (UHI) (Rushayati et al., 2016). Meanwhile, DKI Jakarta is estimated to reach the hottest temperature in 2029, which is marked by an increase in temperature of 12.52ºC from 1940 (26.48ºC) to 2012 (39ºC) (Kautsar, 2018).

Earlier

1989

2004

2013

Figure 1. Urban greenery loss within Jakarta Source: NUS, Msc ISD, 2015

Moreover, along with the heavy precipitation and insufficient stormwater management system, urban flooding has become almost an annual event for Jakarta. Runoff is directly directed to poor condition sewer and creek, barely absorbed by the ground nor vegetation (Ainy et al., 2018) transporting the hazardous pollutants into the streams. The fastest solution to take might be by enlarging the drainage volume itself, however, it ended up failing to solve the problem regarding stormwater runoff in the streetscape (ibid). According to a study on Jakarta green plan, the absence of GOS master plan causes JCCG not to have guidance and a long-term plan that is applicable and measurable in achieving a total of 30% GOS target by 2030.

In some cases, green spaces are constructed for merely aesthetic purposes to gratify the city’s image while it is essentially further than that. The absence of direction in employing UGI usually occurs because city planning is not properly compensated and incorporated with the results of research on the green infrastructure itself, thus it is still not applied properly in urban design(Klemm et al., 2017) Therefore, there needs to be an understanding and a guideline as a framework in implementing the UGI application

© ILPÖ 2020

2

Introduction

that integrates with the existing grey infrastructure, especially in countries with a weak and unstable green policy as a response to tackle the impact of changing climate.

According to the Directorate of Settlement Area Development, one of the strategic measurements that can be carried out to achieve 30% of GOS within Jakarta city is by developing green corridors. The corridor can be established by planting large trees along with the green space potential such as streets, pedestrian, river border, the edge of the body of water and reservoirs, railroad border and can be used as motorized vehicle transportation and environmentally friendly city tourism routes (Kota Hijau, 2016).

Therefore, this paper focus will be put on the integration of UGI into the public space and existing grey infrastructure (in this case streetscape) to adapt to climate change impacts such as high urban temperatures and urban flood by considering several forms of successful implemented UGI in theory in a highly urbanized area and scrutinizing the most affected location to carry out the proposed green streetscape strategy. Specifically, by addressing Jakarta as a city in the tropics, challenges, and solutions to the framework might be different from the temperate climate regions where most integrated grey-green infrastructure studies are mostly conducted.

1.3

Objectives •

To have a comprehensive overview of earlier successful green streetscapes in global research and practices in diminishing climate change impacts in dense urban areas.

•

To deepen knowledge on established green streetscape framework and develop a conceptual strategy regarding the relevant implementation of the green streetscape for the city of Jakarta based on its concern and characteristics.

•

To screen potential locations in Jakarta for the improvement of green streetscapes implementation based on heat stress, flood hazard, and sensitive population.

1.4

Research questions •

How could streets, as grey infrastructure, be utilized as a part of UGI development to reduce the effect of heat exposure and urban flood?

•

How a sustainable streetscape framework could be developed for the urbanized area in a tropical city at street level as a response to climate change adaptation as Jakarta itself does not possess rigid policy and guidelines regarding UGI establishment?

•

Which area or location in the city of Jakarta is most appropriate to be focused on green streetscape development based on the streetscape framework and typology function?

© ILPÖ 2020

3

Introduction

1.5

Research methodology

Figure 2. Thesis research methodology Source: Author, 2020

This master thesis is set up to look up at several cases as the basis for the analysis which from that, recommendations for a designated framework for the case study area are drawn. Instead of going to the place, doing field research and questionnaire study, analysis is entirely done by desktop research by analyzing other documents and projects which encourage the establishment of a relevant framework. Therefore, the research methodology consists of three main sections as depicted in figure 2. The first one is theoretical framework development, wherein this part will be focused on the elaboration of theories that are related to the crucial roles of UGI, especially on the street level in adapting to the changing climate phenomenon in urban tracts, in particular concerning urban heat and urban flood management. The development of UGI itself is not a new notion, however, a relevant approach that fits the case study area’s condition and attributes are important in contributing to tackle a wide number of urban problems.

Research on literature, existing framework, and successful green streetscapes projects at the city level are examined.

Resulting from the development of the green streetscape framework, the second part is intended to show how the framework can be employed and integrated into the neighborhood and street-level regarding priority identification. Reciting from (Norton et al., 2015) research work, planning a UGI framework can be done in three scales; which two of them involve neighborhood scale and street scale: By determining the substantial adaptation criteria, the significant neighborhoods where UGI will be implemented are selected. Urban tracts that are most exposed to the climate change impact will be identified as a suitable location for UGI implementation. Priority analysis for urban green street implementation is done by identifying hot spots for climate concern and social aspects layers using a Geographical Information System (GIS) software. The urban

© ILPÖ 2020

4

Introduction

district that is identified as the greatest hot spots for all parameters will be selected.

Criteria that will be the basis of examining suitable location are land surface temperature, flood area map, surface imperviousness, vegetation cover, a buffer from most probably influential street, and the amount of sensitive population to the impacts. After establishing the potential areas in selected neighborhoods, the most affected street corridor will be analyzed further by observing the current street and canyon dimension as well as the building's characteristics via aerial imagery on Google Street View (GSV). Lastly, specific green street infrastructure typologies, tree selection, and design guidelines are proposed to the selected street by putting several aspects into account. While the neighborhood scale provides an integrative approach as the main idea, on the street level, further detailed and comprehensive solutions are offered. Conceptual graphics are used to illustrate the strategies.

1.6

Scope and limitation

Due to the current pandemic situation, a field visit to the case study area could not be done physically. Therefore, desktop research and Geographic Information System (GIS) analysis is carried out by utilizing the open public shapefiles and data which are provided by the local government. Moreover, observing the city and street-level characteristics can only be done by satellite imagery via tools such as google earth and open street maps. Lastly, a scoring system regarding the prioritization of creating sustainable urban green streetscapes should have to be done by conducting an interview with the respected professionals and executing stakeholder analysis.

© ILPÖ 2020

5

Theoretical Framework

2 Theoretical Framework 2.1

Urban area and climate challenges

A great number of populations residing in urban areas are studied to experience severe climate events much greater than people in the rural areas due to the absence of urban resiliency risk policy, critical infrastructure (UNISDR, 2011) as well as different environmental conditions. In contrast to rural areas that are still dominated by open green land, the occurring urbanization and densification in the city lead to an increase in the impervious built-up area. The level of urbanization concentration can trigger and worsen the prolonged surface air temperature and urban hydrology due to anthropogenic activities that draw out environmental pressure (Revi et al., 2014). This condition coupled with the foreseen climate change effects such as temperature rise and heavy rainfall causing the urban tracts to be more exposed to urban heating events and urban flooding (Kabisch et al., 2017). In one of the nature-based solution expert workshops held by the German Federal Agency for Nature Conservation, several city climate concerns that are highly mentioned by the participants consist of heat stress and flooding due to extreme events.

The conversion of land cover from vegetated areas to the construction of buildings and roads with impervious and solar captivating materials could lead to the modification of heat and mass exchange formation known as urban heat island (UHI), where urban areas experience warmer temperature than the surrounding rural areas (Runnalls & Oke, 2000). UHI phenomenon is an accumulation from the increasing use of poor solar energy reflecting pavements in a city, geometry of building and street canyon as well as deterioration or removal of green areas (Herath et al., 2018a). Meanwhile, the flooding phenomenon in urban areas is caused not only by geographical conditions and rate of precipitation but also by increasing human activities which has an impact on land-use change and modification of surface water bodies (Puczko & Jekatierynczuk-Rudczyk, 2020). The buildup of impermeable surface degrades the runoff infiltration process through the soil thus increasing the rainwater velocity in a large volume and accumulating into a flood (Rubinato et al., 2019). This condition is worsened by the presence of climate change that prompts higher rainfall precipitation occurrences.

In the long run, this phenomenon will negatively influence the urban ecosystem and the population’s quality of life. Therefore, there must be some countermeasures to be taken to hinder the damaging effects. However, the actions of tackling changing climate occurrences are considered ineffective in large cities due to its characteristic that is identical with rapid population growth, dense built-up area, and lack of open green space.

(Derkzen et al., 2017). Built-up areas that are not compensated with man-made green space will create so many problems. People that recite in the more compacted neighborhood are found to be more exposed to the extreme heat and flooding impact.

Due to the limited availability of land in cities with a high-density population, implementing adaptation and mitigation measures such as UGI to the existing

© ILPÖ 2020

7

Theoretical Framework

impermeable spaces, such as streets, can be a natural based option to overcome the concern (Im, 2019). Retrofitting green infrastructure in the urban area can be carried out in several ways such as (1) constructing green or living walls to provide shading and cooling, (2) integrating vegetated swales and bioretention as part of streetscape and traffic calming scheme, (3) planting trees along transportation corridors. According to the green surge report, UGI itself is a wide range practice of developing green and blue infrastructure throughout urban areas which attempts to address and resolve several problems such as climate change adaptation, biodiversity protection, green economy advancement as well civic coherence increase that can be realized through four core principles namely combination of green-grey infrastructure, creation of green networks, delivery of multiple ecosystem services benefits as well as inclusive synergetic planning (Hansen et al., 2017).

2.2

Green-grey integration: streets as an opportunity for UGI

Streets normally represent a significant proportion of a city as various commercial, social, and leisure activities can be found there (Phillips et al., 2015). Streets can be utilized both for mobility continuity, ecological improvement, as well as urban resilience in densely built areas. The green infrastructure itself can be implemented as an integrated municipal scheme in a region or a city scale, neighborhood level to the building plots by involving private estate to commit to the application. Several researchers from around the world have recognized the benefits of UGI to the adverse effect of climate change.

A certain neighborhood climate setting could be naturally regulated by providing a suitable green infrastructure that matches its characteristics (Kabisch et al., 2016).

2.2.1 2.2.1.1

Green infrastructure streetscape typology Green streets and alleys

Green streets and alleys are a combination of several UGI elements in the categories of low impact development (LID) such as permeable pavements, bioretention, street trees, planter boxes as well as low landscaping which are integrated to a specific area, vicinity of a building and caters several benefits such as managing precipitation runoff, lowering urban heat and conserving energy use (CDOT, 2010). While vegetated surfaces— for instance, swales and bioretention serve to retain, delay, and filtrate stormwater runoff, street trees enhance neighborhood local climate by cooling off the temperature and regulate the wind speed.

Compared to the traditional alleys with impervious material surface, a street that is designated with green streets and alleys components such as rain gardens and planted trees tend to control stormwater runoff three to six times more efficiently (Foster et al., 2011). Moreover, conventional streets that are covered with dark material and lack of shaded tree canopy can lead to the increase of urban temperature as well as air quality degradation, therefore green street principles can enhance these circumstances.

© ILPÖ 2020

8

Theoretical Framework

Converting dark material to the permeable pavement or higher reflecting surface in an alley reduces the possibility of solar radiation absorption during the day that triggers the UHI phenomenon (NACTO, 2013). To obtain more comprehensive and evidence-based benefits on the green street application, table 1, 2, 3, and 4 summarize some of the research and modeling simulations conducted by academics from all parts of the world to evaluate the benefits of successful green elements application on the streets in an urban setting in different countries.

Street trees and tree pits In a systematic review on individual street trees carried out by (Bowler et al., 2010), it is concluded that surrounding air temperature is usually higher opposed to the temperature under tree canopies as the direct cooling effect of shading which is mainly determined by the (1) tree varieties—by the reason of distinct size and canopy feature, (2) quantity of planted trees—small groups of 3-4 trees are found to be more effective in increasing urban cooling performance than one single tree, (3) the ground where the individual trees are planted, low greening intervention is preferred rather than asphalt pavement, and lastly (4) street canyon orientation since building could also provide shading. Whereas indicators such as leaf area index, radius, and height of the tree shown to a little effect and no linear relationship in determining air temperature decrease performance (Souch & Souch, 1993). Meanwhile, the vital function of urban street trees to the hydrology cycle and runoff management includes (1) water loss via canopy intervention in which rainwater that falls into tree canopies will be evaporated back to the atmosphere, (2) evapotranspiration, where water is absorbed into the ground and transported as a liquid to the leaves which eventually escapes the plant in the form of water vapor and finally, (3) infiltration provision (Berland et al., 2017). In research dedicated to urban tree health, for the tress to reach the maximum ecosystem services value in reducing urban heat without generating excessive water footprint and adding supplementary irrigation system is by providing bare soil and permeable pavement area that match its canopy expansion (Vico et al., 2014) Table 1. Evidence-based evaluation and findings on street trees Source Melbourne, Australia (Thom et al., 2020)

© ILPÖ 2020

Research Measuring street tree’s capabilities in retaining stormwater runoff and water transpiration performance through 6m2 additional infiltration trenches that is installed and placed adjacent to the nine selected broad-canopy trees during spring and summer period.

Findings • A greater volume of stormwater is captured by integrating trees and infiltration drains; counted to 24% from annual impervious area runoff and 17% of it is transpired.

• Redirecting stormwater to the trees is also one way to naturally irrigates the vegetation, even though it does not necessarily increase trees' transpiration capacity.

• However, the fact that the trees transpire a substantial percentage of water annually indicates a significant

9

Theoretical Framework

London, UK (Taher et al., 2019)

Barcelona, Spain (Baró et al., 2019)

Colombo Metropolitan Region, Sri Lanka (Herath et al., 2018a)

Manchester, UK (D. Armson et al., 2013)

Modelling and performing numerical analysis on radiant temperature and surface temperature in two different street orientation in London city center with different street tree cover percentage and highly reflected pavement scenario using ENVI-NET software.

•

Assessing the amount of 200,000 street trees regulating service performances, namely air pollution abatement, heat mitigation, and runoff management gathered from 73 neighborhoods in 10 different streets in compact Barcelona city, Spain by utilizing Eco Tree tool.

Creating a numerical simulation on 4.58 ha area which is dominated by commercial and residential activities, using ENVI-NET software through several scenarios of urban green establishment in mitigating UHI. Identification of several best urban green practices is also carried out.

Nine experimental plots consist of a tree planted within an impervious surface, asphalt lot, and grass lot are placed at 5 different sites near South Manchester, the UK to evaluate each urban area runoff retention capability.

•

•

•

•

•

•

•

•

© ILPÖ 2020

volumetric decline of street stormwater runoff.

Trees are one of the Urban Green System (UGS) which is used to prevent solar radiation from reaching pavement surface and increase pedestrian thermal comfort in E-W street orientation.

Increasing the trees ratio scenario up to 25% could decrease the Physiological Equivalent Temperature (PET) by 3.080C and 5.840C for 50% tree cover.

The result shows that during 2015, Barcelona’s street trees played an important role in eliminating airborne contaminants up to 28,023 kg/year or equivalent to 143 g/year per tree, preventing stormwater runoff up to 52,668 m3/year or 270 l per tree, and lastly transpiring 840,408 m3 of water per year to the atmosphere or counted to 4301 l/year per individual tree.

Compared to the original scenario where the UHI effect is found (34.67 °C at the peak hour), simulation on tree planting on street curbs could reduce heat by 1.87°C, which is counted as a 5.39% temperature decrease).

Temperature reduction by street trees happen directly (shading) and indirectly (CO2 absorption, cooling effect by transportation process).

Asphalt possesses the highest urban surface runoff from the total rainfall, calculated at 62% during winter and 53% during summer.

Meanwhile, total runoff at trees along its pit plot counted only 26% and 20% from the total rainfall in winter and summer, respectively.

This concludes that the tree components could lessen the amount of runoff from the asphalt area up to 62%.

Grass produces almost no runoff since water infiltrates thoroughly.

10

Theoretical Framework

Utrecht, The Netherlands (Klemm et al., 2013)

Thermal comfort observation in nine different residential streets in Utrecht with three different scenarios: 1) street without tree canopies 2) street with tree canopies on both sides 3) street with trees and small gardens on both sides.

• Even though the result does not imply a huge difference at the first analysis due to several factors such as little percentage of tree cover, different street width, no adjustment for street orientation and aspect ratio, time inaccuracy due to moving observation— it shows that compared to street 1, the mean radiant temperature on street 2 is found be lower by 2.5 K.

Bioretention and rain garden A shallow basin-form of vegetation that collects rainwater and runoff from roofs, roads, and adjacent areas is called a rain garden. It is designated to capture and hold the runoff with an intermediate medium in the form of dense planting, which slows down stormwater and provides more time to be absorbed and infiltrated slowly into the surrounding soil or drained into the sewerage. Moreover, it is proven that urban cooling could also be regulated through bioretention evapotranspiration (Coutts et al., 2013).

Table 2. Evidence-based evaluation and findings on rain garden/bioretention planters Source Singapore, Singapore (Yau et al., 2017)

Research A preliminary calibrated hydraulic analysis is done by using the Storm Water Management Model (SWMM) to identify the effectiveness of ABC (Active, Beautiful, Clean) Water four types of designs elements in reducing peak flows and runoff volume for u within residential development in a tropical city, Singapore. Projects consist of 21 rain gardens, four vegetated swales, and two gravel swales.

Singapore, Singapore (Wang et al., 2017)

Understanding the performance of bioretention basins in the tropical city through flow and water-level calculation and real-time observation approach from April to November 2013 with

© ILPÖ 2020

Findings • Typical ABC water design features include four types namely rain gardens, vegetated and gravel swales show how all of them contribute to lowering peak flow and delaying runoff during 3-months and10- years storm events, however, coupled with gravel seams as storage and orifice outlet provides a more effective result.

• Typical ABC water design could reduce 3-month design storm maximum flow up to 37% meanwhile 13% for 10-year design storm.

• Predictably, rain gardens are more successful in lowering peak flow and the runoff coefficient is less significant rain occurrences.

• Based on tropical stormwater attributes and hydraulic statistics it might be stated that the rain garden at Balam Estate is practically competent for deferring peak flow even though the performance is not

11

Theoretical Framework

(Ebrahimian et al., 2019; Wadzuk et al., 2015)

San Francisco, USA (Gilbreath et al., 2015)

NE Siskiyou Street, Portland (The City of Portland BES, 2004)

© ILPÖ 2020

a total of 80 storm events.

The capability and efficiency of the rain garden at Balam Estate, Singapore in retaining runoff and eradicating contaminant load were monitored.

Both studies examine the evapotranspiration process in bioretention also portrays a significant role in decreasing rainwater runoff, however, it is poorly discussed in general.

The Cesar Chavez Streetscape Improvement Project consists of building bioretention planters along more than 800 meters of the highly impermeable street as well as adding bicycle lanes, curb extension to improve pedestrian crossing as well as other green landscape design. Monitoring was done during the rainy season (October 2014 to March 2015) A pilot project in the city of Portland in retrofitting vegetated filters into curb extension built for the street parkway. Measuring the advantages of this natural stormwater management is accomplished by observing the site's performance.

While collecting local precipitation and stormwater flows data are more complicated to execute, peak storm event simulation using hydrant, hose, and the

great when it comes to prolonging peak time and runoff volume delay.

• The rain garden is proven to be successful in removing pollutant load, specifically total suspended solid by 53%.

• Evapotranspiration ability in a rain garden is considered crucial in excess rainwater volume reduction.

• For example, the rain garden itself can retain up to 19%. But it all depends on the plant’s characteristics.

• For this reason, the selection of plants to build rain gardens based on parameters such as growth rate, leaf chlorophyll variation, and evapotranspiration rate is very influential.

• Out of 18 bioretention planters that were built on the most feasible sites, conditions at 7 planters were set as samples for simulation.

• The result reveals that the total stormwater volume flowing to the combined sewer system (CSS) was lowered to 53%, with the least performance was 31% on the smaller planter and up to 89% on the standardized planter size.

• Average peak flow rates were lowered from 35% to 50%, depending on the rain intensity.

• The vegetated curb extension delivers critical advantages for stormwater runoff.

• The maximum discharge was deferred 20 minutes and a reduction up to 80% peak flow of 25-year storm occurrence (indicates greatest rainfall intensity of 84.3 mm/hour during the initial quarter-hour of an extreme downpour) was spotted.

• Furthermore, runoff volume was reduced up to 85% for a 25-year rain event, even when the infiltration rate works minimally it still can hold

12

Theoretical Framework

portable water meter is carried out.

20% of combined sewer overflow (CSO) design storm.

Swale and bioswale Swale is part of an urban landscape in the form of a low and narrow trench that has slopes usually covered by grass, water plants, mulch, or native vegetation that is designed to concentrate and gradually filtrate stormwater to reduce surface runoff.

Bioswale is especially beneficial for areas with excessive rainwater runoff through its efficiency in delaying the overflow velocity and purifying the polluted water which is later stored as groundwater recharge (NACTO, 2017). A common application of a bioswale in urban areas is to intercept surface runoff from low permeability soils such as in parking lots, roads, and roofs in large quantities.

Table 3. Evidence-based evaluation and findings on bioswales Source Seoul, South Korea (Shafique et al., 2018)

Singapore, Singapore (Lim & Lu, 2016)

Sunshine Coast, Australia (Lucke et al., 2014)

© ILPÖ 2020

Research This study focuses on monitoring 2.1-meter-wide x 51-meter-long grass swale performance located in a parking lot at one of a notable stadium in Mapo-gu Seoul, South Korea. Swale's ability to retain stormwater and its soil water content were observed under different real rain events to identify whether the technology can hinder urban flash flood or not.

Singapore’s ABC (Active, Beautiful, Clean) Water Programs is the first LID implementation in tropical urban cities which consists of rain gardens, swales, constructed wetlands, etc. In this paper, its goals and performance in achieving successful practices are evaluated.

Four different swales' effectiveness in filtering out pollutants and their hydrological capabilities were measured using controlled field runoff

Findings • During 6 months of observation from May to October 2017, it is found that during small storm events (around 30 mm/hour), grass swale can absorb stormwater runoff between 40% to 75%.

• Meanwhile during bigger storm events (about 100 mm/hour), besides the soil moisture content increases from 35% to 57% due to more rainwater captured on the site, it also shows that the peak flow reduction is much less significant than in smaller rain occurrences.

• Swales or buffer is purposely constructed to cater to three functions, namely stormwater detention, conveyance, and lastly infiltration.

• Besides decreasing flow velocity and runoff volume to minimize the possibility of downriver erosion, vegetated swales also provide small solid residue or particles preremoval through natural treats.

• Effective pollutant removal especially for total suspended solids (TSS) up 80% at the beginning and total phosphorus (TP) up to 23%.

Therefore, designing long swales is not necessary since decent residue elimination happens in the first 10 m.

13

Theoretical Framework

simulation experiments.

Sunshine Coast Australia

Maryland, USA (Davis et al., 2012)

Hydraulic capacity of two grass swales in the median of highway in Maryland, USA were assessed during 52 rain occurrences within 4.5 years.

California, USA (Xiao & McPherson, 2011)

The runoff reduction, contaminant removal, and tree growth that were placed on both sides at the parking lot with a treatment site (including bioswale) were evaluated. The treatment area collected runoff from the adjacent eight parking spaces. Fifty rain events with an accumulated rate of 563.8 mm were occupied in this study.

• Swales are demonstrated to be successful in reducing 52% of overall discharge and decreasing the maximum flow rate up to 61%.

• During small rain events, green swales can capture 59% of rainfall in the regular Maryland year.

• On the other hand, grass swales were observed to be less efficient in reducing runoff volume during heavy rain events thus they can only presumably function as a medium to transport and slow down the movement of stormwater.

• The result shows that the bioswale with the base of engineered soil on the treatment site was able to retain runoff by 80% • Not only stormwater runoff reduction, but it was also discovered that bioswale could remove 95% of mineral, organic carbon as well as solid materials.

• The actual tree growth report could not be determined since the tree was not in a suitable condition to be observed, however, based on eye surveillance, the growth was somewhat improved.

Permeable pavement Instead of constructing pedestrian curbs with impervious material, porous pavements can be a healthier substitute for paving surfaces where rainfall can be captured and subsequently stormwater runoff can penetrate the adjacent soils or be discharged to the nearby drainage system. Few types of permeable pavement include open-pore pavers, pervious concrete, and pervious asphalt which are commonly constructed in parking lots, low-traffic roadways, or neighborhoods and. walking paths (Selbig, 2018).

Table 4. Evidence-based evaluation and findings on permeable pavement Source Kaohsiung, Taiwan (Huang & Chen, 2020)

© ILPÖ 2020

Research Five possible scenarios in mitigating urban heat islands in 23.9 ha tropical urban commercial district in Taiwan were assessed using ENVINET software. Simulation settings include the increase

Findings • In the first scenario, where the original asphalt pavement is modified to the permeable pavement, it can be derived that surface temperature was reduced by 7.90C and the air temperature was reduced by 1.30C.

14

Theoretical Framework

of vegetation cover ratio in streets and parks as well as permeable pavement application,

(Cheng et al., 2019)

Washington, USA (Jayakaran et al., 2019)

Nanjing, China (Hu et al., 2018)

© ILPÖ 2020

Porous asphalt (PA) was utilized for a 200 m-long cycle path and porous interlocking concrete brick (PICB) for a pedestrian walkway with the same length, where heavy traffic street is located adjacent to it. Below the previous pavement, tank water for infiltration storage was installed. Besides hydraulic capacity, the changes in surface temperature were also measured.

Level of contamination contained in stormwater discharge from both traditional impervious asphalt and pervious asphalts were observed in five years to detect the removal percentage from the later technology using real and artificial storm events.

Using hydrological simulation, the efficacy of three forms of permeable pavement: permeable asphalt (PA), permeable concrete (PC) and permeable interlocking concrete pavers (PICP) at a neighborhood level, set up specifically in local roads, parking areas and plazas

• This study also states that the cooling effect achieved by permeable pavement has worked three times greater than merely expanding green coverage ratio since the amount of water retained inside the pervious surface directly altered street temperature by approximately 11-200C. • During a longer period but small precipitation, runoff peak was decreased up to 55%, meanwhile, for huge and extreme rain events, peak runoff could be reduced by 16%.

• It was noted that runoff volume was on average reduced by 38%. + • PA revealed the highest infiltration rate while PICB was considerably prone to clogging. Especially after more than 15-month use.

• In summer, the temperature dropped to 3.90C for PA and 6.60C for PICB. • The analysis which was done in a parking area by redeveloping 0.32 ha previous asphalt shows that porous pavement functions like a large infiltration structure that efficiently eliminates thick particles, lead, zinc, TSS, motor oil, and diesel at the highest rates (rate of 98% for each pollutant removal was achieved.

• There was no significant pollutant removal efficiency between maintaining and unmaintained porous asphalt.

• Throughout 12 different scenarios in a 12-hour and 113.8 mm precipitation event, it has been proven that permeable concrete in an excellent situation (without particles clogging) was able to reduce water runoff up to 40%.

• The percentage of peak flow was also lowered by 42% under the same scenario as mentioned above.

15

Theoretical Framework

were assessed on mitigating urban flooding.

California, USA (Li et al., 2013)

this research aims to acknowledge the hydraulic activities and thermal cooling capacity of various permeable pavements in managing runoff and high temperature in both dry and wet climate. The test was done by examining the 4 m x 4 m area of six permeable pavements (PC and PICP) and three impermeable asphalt as comparisons.

• Flood mitigation strategy using permeable pavements reveals different results depending on the typology, where runoff was reduced the most using PC then followed by PA and PICP. • This study found that PICP so far retains the highest infiltration rate compared to permeable asphalt.

• Permeable pavement indeed could reduce the surface temperature by providing both reflective and evaporative cooling; however, it highly depends on the level of water available and the evaporation process. Under a wet scenario, the temperature was lowered down between 15-350C. • Even after the water has slowly evaporated, the surface temperature was still influenced by evaporative cooling marked by lowered temperature by 2-70C.

There are several ways to integrate green elements on street depending on the street typology and requirement (see table 5). On a smaller scale such as neighborhood streets, alley-greening activities can be organized and carried out by the residents or community.

Table 5. Green street element practice placement Source: (NACTO, 2017) Planting Green street Curb area/furnishing element offset/extension zone Street tree/ tree pit Bioretention planter Bioretention swale Permeable pavement

Pedestrian path & sidewalk

Parking lane Bicycle lane

Centre of transitway

Perceiving from all of the summary tables above, it can be understood that while North American and Western European countries have already included green urban development into their municipalities urban planning process as the parameter of resident’s quality of life, especially incorporating green elements to the public streets and residential alleys, there are only a few pieces of research regarding UGI placement in high-density Asian countries, especially for the developing ones.

© ILPÖ 2020

16

Theoretical Framework

2.2.1.2

Green façade and living wall/green wall

“A lack of greening possibilities in streets should be compensated with surface water, green façades, and permeable pavements”. Apart from implementing greening elements on the street and alley itself, constructing a green building element such as a vertical greening system (VGS), also relieves thermal comfort inside and outside the building.

Benefits from different literature are reviewed, for instance (1) adding green values to the dense urban area, (2) minimizing the effect of urban heating by absorbing the sunlight and through water evaporation by the plants, (3) improving people’s quality of life by filtering grainy particles and converting CO2 to O2, (4) reducing urban traffic noise, (5) increasing biodiversity by promoting habitats for animals and insects, and lastly (6) offering precipitation barrier by absorbing and filtering the rainwater which delays the water flow directly to the drainage pipes as well as reduces the peak discharge that leads to reducing the risk of flooding (Radić et al., 2019). Two different vertical greening systems are frequently misunderstood. The difference between a green façade and a living wall lies in the media and the types of plants that are utilized. Green façade occupies a system where the wall is covered with vines or other types of growing climbing plants supported by mesh structure meanwhile living wall is an arrangement of integrated vegetation panels that are placed on a wall or a frame structure, given a planting medium to grow plants which usually consists of the individual frame, crop panels, irrigation or watering and fertilization systems (Lassandro & Di Turi, 2017). In Hong Kong, coverage of a concrete wall with modular vegetated panels reduced exterior wall temperatures by up to 16°C in summer (Cheng et al. 2010). In terms of internal wall temperatures, a difference of more than 2°C was maintained even late at night, indicating that green walls can significantly reduce energy use for building cooling. Few papers are reviewed to gain a deeper understanding and evident-based study about VGS as a sustainable approach towards climate change (see table 6).

Table 6. Case study and benefits on vertical greening implementation

Source

Case study

Benefits

Colombo, Sri Lanka

Evaluating the heat reduction

Derived from three different simulation

(Herath et al.,

between the present

location in the tropical urban city,

2018b)

condition where the tropical

100% of green walls coverage of the

city is characterized by the

total wall area are proved to be

temperature of 27.88–

effective in decreasing temperature up

34.670C

to 2.030C for the case of building with

and three scenarios

where (T5) 50% of the

built cover from three sides and

building wall are covered with

asphalt road from one side and

green in E-W orientation; (T6)

1.590C for buildings with built cover

100% from the total wall area

from two sides, asphalt road from one

in E-W orientation; (T7)

direction, and paving for the other

Consistent portion from total

direction. Therefore, city greening is considered an efficient approach in

© ILPÖ 2020

17

Theoretical Framework

N-S oriented building wall by

enhancing city resilience towards

using ENVI-net simulation.

climate change by decreasing the building’s energy demand and altering local thermal comfort.

Rio de Janeiro,

The cooling performances of

A green roof and green wall certainly

Brazil (Wilkinson et

a combination of a green wall

increase the thermal mass and

al., 2017)

and green roof in the tropical

insulation value of a building. The

city were assessed by

experiment shows that during the

constructing a concrete and

daytime the temperature in the non-

cement-block prototype

vegetated module reached 40.20C,

covered with plants. The

meanwhile in the vegetated module

thermal attenuation

the temperature decreased to 36.60C.

performance is compared to the module without plant cover.

Jakarta, Indonesia

Comparing humidity and heat

The temperature at the peak hour (10

(Othman & Sahidin,

reduction inside and outside

am) was observed on a certain date

2016)

of two different buildings; (1)

and it showed that the maximum

equipped with vertical

outside temperature of a building

greening system (VGS)

without a green façade reached

façade and (2) not equipped

35.40C, meanwhile with the presence

with VGS, in a tropical

of vertical greening, the temperature

country, Indonesia by

measurement appeared to be 31.80C.

measuring both aspects

As for the difference between outside

quantitatively using

and inside temperature for building

thermometer and hygrometer

with vertical greening, 3.79% of indoor

as the tools.

heat reduction was discovered.

London, UK

This largest (approx. 350 m2)

This ambitious and huge project is

(Deezen, 2013)

green façade in London is

expected to reduce urban stormwater

designed to be able to tackle

runoff due to the huge proportion of

urban flooding. Ten thousand

sealed urban surfaces by the ability to

plants in total are planted on

store up to 10,000 liters of stormwater.

a 21-meter-high building wall.

Rainwater is stored on the roof and

As the Royal Horticultural

can be recycled to water the

Society recommended, all the

vegetated wall therefore it becomes

plants act as the best

sustainable. Besides reducing surface

pollinators to attract wildlife

runoff, additional benefits such as

such as bees, butterflies, and

trapping pollution, declining traffic

birds to the urban

noise, and improving the thermal

environment.

environment are also estimated.

Sarawak, Malaysia

Simulation using USEPA

The results reveal that synthesis

(Lau & Mah, 2018)

SWMM 5.1 by employing

precipitation data, used in Scenario 1,

certain specifications of a

2, and 3, decreased runoff by more

© ILPÖ 2020

18

Theoretical Framework

The aim is to

green wall at a 3-story

than half, at 55% on condition of one-

acknowledge the

commercial building. A factual

year ARI and 5 minutes of storm

effective solution

rainfall rate was incorporated

duration. Meanwhile, Scenario 4 also

for flash flooding in

into the assessment with four

shows a repetition of runoff reduction

the city center due

set-ups. Scenarios 1, 2, and 3

by half after the integration of the

to rapid

use the same designated

green wall using the observed rainfall

urbanization by

precipitation but different soil

data. Thus, it is verified that a green

cooperating green

types, average repeat

wall can be effectively used as an

walls as part of the

interval, and storm period

urban drainage system in reducing

urban drainage

respectively, meanwhile

surface runoff.

system to minimize

scenario 4 tests out the

rainwater flow and

effectiveness of green walls

runoff quantity.

using surveyed rainfall.

Vancouver,

The stormwater management

By increasing 15% of green elements

Canada

performance by green façade

on the building façade, it showed

(Roehr et al., 2008)

was assessed by carrying out

unsatisfactory results for the treatment

a quantitative observation in

of runoff. It was monitored that green

the downtown area using the

façade only contributed 6% to the

Curve Number (CN) method.

reduction of stormwater runoff.

2.2.1.3

Green corridors

Implying UGI along the existing linear assets delivers many advantages including enhancing transport infrastructure resilience and efficiency. Besides enhancing green components along the streets, it could also be done in other forms such as greening alongside railroad tracks which latter example has been commonly implemented throughout some European countries such as Germany and Netherland. According to the German Green Track Network publication, compared to the ordinary ballasted rail track greening improves water balance along with the greening areas by increasing the water retention capacity where more stormwater stored into the soil which eventually will be evaporated back to the air thus enhances air humidity and generates cooling effect (Kappis, 2013). Depending on the land cover, the prior research found that tracks that are covered with sedum and grass store average annual precipitation volume up to 50% and 70% respectively. In a pilot project conducted along a major railway corridor in Sydney, it is analyzed using i-Tree Eco software that different types of vegetation cover such as trees and shrubs provide significant stormwater runoff reduction (Blair et al., 2017).

2.2.2

Performance and limitation

Despite all the advantages, some constraints, and restrictions in implementing all green streetscape infrastructure are found and listed in figure 3 as well as a summary on green streetscape infrastructure objectives in table 7.

© ILPÖ 2020

19

Theoretical Framework

Click or tap heretrees to enter text.

Street

Low capability in delaying peak flow for large rainfall events

Rain garden/bioretention

Inadequate capability in storing and detaining stormwater runoff

Bioswales/strips

Not suitable for steep area

Pervious pavement

Require sufficient water and soil nutrient thus high maintenance Regular medium replacement

Green façade

Possible blockage Living wall Potential erosion Possible groundwater pollution

q transport corridor Green

Figure 3. Green streetscape elements limitation Source: Adapted from (Payne et al., 2019) Table 7. Summary of green streetscape infrastructure elements objectives Source: Adapted from (Moreton Bay Waterways and Catchments Partnership, 2006) Objectives indicator

ST

RG

BS

PP

GF

LW

GC

Shading provision Urban thermal cooling Peak flow reduction Runoff volume reduction /stormwater infiltration Groundwater recharge Pollution filtration

ST= Street Trees; RG= Rain garden; BS= Bioswales; PP=Permeable pavement; GF=Green façade; LW= Living wall; GR=Green corridor. = High performance

© ILPÖ 2020

= Medium performance

= Low performance

20

Theoretical Framework

2.2.3

Existing green streetscape framework review

Many studies and publications from academic urban planning fields to local governor institution policies have developed and configured the best framework to implement UGI practices to adapt and mitigate climate impacts. However, only a few focus on street green infrastructure applications.

Most of the detailed policies on sustainable streetscape infrastructure are established by developing countries in the European region, USA, and Australia. To obtain a detailed and comprehensive understanding of green streetscape enactment, various street UGI prioritization guidelines and strategies from various academic journals and regional policy documents are reviewed and presented in table 8.

Source Australia: Planning for Cooler Cities: A framework to prioritize green infrastructure to mitigate high temperatures in urban landscapes (Norton et al., 2015)

© ILPÖ 2020

Table 8. Green infrastructure integration to streets framework from countries around the world Goals Framework Methodology • To integrate UGI research with urban • A hierarchical five-step framework to prioritize urban public open space for design to develop the best implementation microclimate cooling so-called “Fit for place” UGI. guidelines.

• Three scales were applied: Neighbourhood scale, street scale, and micro-scale.

• Studies on land managers regarding the • Identify the priority of urban neighborhood based on heat exposure, vulnerability proper approach for UGI implementation (poor access to parks and public transport, elderly and young population that live in based on the climatic condition are rarely the low socio-economic area), and behavioral exposure (large numbers of active discussed. Therefore, focusing on the outdoor spaces such as public transportation transit, recreational areas, and integration of UGI into the urban elements schools). and public interaction to mitigate high • Characterize UGI and grey Infrastructure through visual surveys or aerial imaginary temperature and considers various UGI to determine area with sufficient vegetation and area that is still lacking from UGI types and the possible location is the main elements. aim.

• Maximizing the cooling effect from existing by identifying existing and potential • To increase the amount of vegetation to irrigation sources within the affected neighborhood. reduce urban air and surface temperature. • Streets that are most vulnerable and exposed to the adverse impacts are selected.

• To present a framework that elaborates Street orientation and geometries such as building height and street width, which prioritized place and UGI for heat reduction mainly contribute to the urban heating, are measured and listed down to have an by examining the relationship between idea of which type of UGI should be implemented. urban street geometry • Select new UGI with the goal of maximize vegetation canopy cover, reduce land • In countries with higher humidity, airflow surface temperature, and provide shaded tress for the pedestrian. can be considered as the guideline aspect. • Selected UGI implementation: Urban green open space (GOS), street trees, green façade, green roof.

21

Theoretical Framework

Canada: Green Streets Project Selection and Priority Analysis (Transport Services, City of Toronto, 2017)

• To maintain the efficient use of the street as a mobility corridor for all travel modes while managing the stormwater runoff.

• To guarantee all proposed infrastructure projects including railway lines, roads, or utility properly take the practice of green infrastructure into account.

• GIS priority screen: employing a multi-aspect scoring methodology, projects are ranked based on thematic benefits and one feasibility factor. The 5 co-benefit themes are: 1) Stormwater Management, 2) Social wellness, 3) Air quality, 4) Climate Resilience, 5) Tree Canopy Distribution • Stormwater management: green street project prioritizes area with i) a great percentage of impervious surface such as roads, building and other types of paved surface, ii) streets with most runoff contributes to sewer pipes discharging at combined sewer overflow near the environmentally significant area (ESA) • Urban tree canopy: Streets that lack green shade is counted as a priority and focus on mainly grey areas such as industrial and commercial land use.

• Air quality: prioritize area within the Traffic-Related Air Pollution (TRAP) zones e.g.

100 m from arterial road and 500 m from highway and area with a high density of vulnerable population such as health facilities, schools, childcare, and senior care centers.

• Social Wellness: prioritize areas with large population density and lowest accessibility to green open space per capita.

• Climate resilience: Areas with extreme heat exposure and flood-prone areas • Desktop analysis: selected green street projects are narrowed depends on additional considerations such as road space, type of drainage, allocation of existing and planned street trees, and soil viability.

USA: Green Infrastructure and Climate Change: Collaborating to Improve Community Resiliency (EPA, 2016)

Strategies on different case study cities area presented on this environmental protection against climate issue report, for example: • Albuquerque, New Mexico: Raise climate change awareness by studying green infrastructure possibilities to focus on continued flooding and hotter temperature problems and detecting prospective spots to locate GI where multiple people demands can be achieved.

Albuquerque, New Mexico: • The most assuring green implementation for tackling climate issues and flooding risk are reviewed, namely bioretention/bioswales, permeable pavement, tree planting, planter box, and water harvesting.

• Prospective parcel analysis to best implement green infrastructure practice consists of two phases: (1) Initial assessment is carried out based on physical characteristics such as minimum slope and house-hold size to gain the most cost-efficient execution. (2) Location prioritization: The GIS suitability mapping process is done by assigning different scores where the highest-ranking comes out as the most suitable site considering several parameters such as public ownership, a higher proportion of impervious area, proximity to parks, and school, and parcels with the foremost accessible space inside the right-of-way.

• Los Angeles, California: Identify the needs of groups of people who use transportation

© ILPÖ 2020

22

Theoretical Framework corridors to improve the City’s climate resiliency. Identifies a methodology and opportunities for prioritizing multi-use transportation corridors existing regional arterial streets, and concrete tributary channels for the design of multi-benefit stormwater storage and use projects.

Germany: Urban Green Infrastructure A foundation of attractive and sustainable cities: Pointers for municipal practice (BfN, 2017)

© ILPÖ 2020

• As cities densify, an action to compensate for the removed green space must be considered.

• Green infrastructure is as important as the other hard and social infrastructure as it affects people’s health and well-being.

• There is a need to connect the gap between the municipalities' practice and the fundamental objectives in protecting and enhancing city greening.

• Green infrastructure signifies a guideline that can be implemented at numerous spatial extents and adjusted to the municipality needs to accommodate stakeholders’ interests.

Los Angeles, California • Residents are divided into groups and challenged to brainstorm green infrastructure features for redesigning projects on several concerning streets to solve three main issues namely urban heat island, transportation corridor near riverbanks revitalization, and drought. A rendered graphical guideline where the selected multifunctional green infrastructures are planned to be located along the streets were developed and proposed.

The main idea of retrofitting green infrastructure and the urban setting consist of: (1) Determining targets, which green infrastructure benefit addresses the involved issue that is wanted to be resolved. In this case, climate change adaptation and resiliency improvement are the main priority.

(2) Finding opposite locations, it is not necessary to locate UGI only vegetated and wet areas, grey sealed sites offer equal potential including utility, societal, and means of transport infrastructure. If required, recording, and upgrading on existing transport and drainage system can be done to fit in the purposed UGI. Therefore, collaborating with the related municipal transportation department and incorporating UGI into the conceptual design for each streetscape is necessary.

(3) UGI must be deliberately planned and aimed at certain planning values, in this case, provide efficacy and create synergy between green and grey infrastructure (4) Listing down required qualitative enhancement for each UGI type (5) Defining tools, funding source, and stakeholder’s interests.

(6) Implementation by establishing base guidelines on the connection between elements and integration between grey and green infrastructure.

23

Theoretical Framework

2.3

Urban challenges for developing good green streetscape approaches

Reviewing all the possible green infrastructure components that can be implemented on the street at different levels helps to acknowledge which is the best practice to employ for the vital built environment especially for the designated case study area. The reviews will become the basis for the next step analysis and further proposal and suggestions for the framework. Quoting from (Norton et al., 2015), the framework works initially on identifying the major intersecting neighborhood areas which include related land-use such as settlement, social, commercial, industrial area, unoccupied lands, and transportation lines. Which later the evaluation will be focused on which urban tracts are considered the most susceptible to the impact of climate change. Once the aimed parts of the city are detected, smaller-scale analysis on certain streets such as communal spaces and commercial strips will be carried out. Types of green streetscape elements that can be added to the lacking streets will be suggested and recommended based on the spatial analysis results. Incorporating both broader and smaller scales to the framework is a vital part of determining the strategic integration of street UGI planning.

2.3.1

Exposure to climate change

One important determinant to assess which location should be prioritized is based on the degree of how negatively exposed an area by the hazards, which in this case, urban heat, and urban flooding. Urban tracts that are exposed to heat events can be characterized by land surface temperature (LST) (Inostroza et al., 2016). LST is utilized since Meanwhile, exposure to urban flooding is represented by flood-prone area maps.

2.3.2

Social vulnerability

Vulnerability is a condition that is determined by factors such as physical, social, and economic which resulted in the declining ability to cope with hazards. In this analysis, the social characteristics of the exposed population are chosen. The elderly and younger populations are more sensitive to the adverse impact of climate change in regards to their health conditions and ability to adapt to the specified phenomenon. Moreover, the population with disadvantage economic conditions and poor accessibility to public IGS are also considered susceptible.

2.3.3

Urban characteristics

Apart from looking at the perspective of how subjected and disturbed a place by changing climate effects, the characteristic of a city can also be viewed as parameters in determining priority locations. For instance, the higher the impervious percentage of an area, the greater the chance this specific spot might be prone to high temperature and flood events. Secondly, the closer a location to arterial and collector roads, the more the opportunity for the people in public space to be exposed to acute air quality and

© ILPÖ 2020

24

Theoretical Framework

pollution. And lastly, the slope of an area is also considered crucial as not every green streetscape technology is fit for a steep slope urban form.

Green streetscape prioritization framework summary

Neighborhood scale

Street scale

Surface Perviousness

Overall score: Prioritized

• Built-up area

location to develop green

• Open green space

streetscape

Tree Canopy Cover

Identify specific green

• Normalized Difference Vegetation

streetscape for hotspots locations within the

Index (NDVI)

selected street in regard Climate Resilience

to:

•

Flood inundation area

•

•

Urban heat island

Street dimension and orientation

•

Drainage dimension

•

Types of vegetation

Social-Wellness • Number of sensitive populations

• Accessibility to green space per

Proposed green streetscape typology example as

capita

solution for implementation

Air Quality • 100 m buffer from arterial roads & 500 m buffer from expressway • High density of vulnerable population

Slope

Figure 4. Reconstruction of the concepts of green streetscape priority analysis Source: Author’s own, adapted based on (Ainy et al., 2018; Norton et al., 2015; Transport Services, City of Toronto, 2017)

© ILPÖ 2020

25

Case study area: Jakarta

3 Case study area: Jakarta 3.1

Introduction

Special Capital Region of Jakarta (DKI Jakarta or Jakarta) provincial government consists of five administrative cities, namely North Jakarta, Central Jakarta, West Jakarta, East Jakarta, South Jakarta, and one administrative regency, Thousand Islands. Jakarta is the second most populous metropolitan city in the world with a total area of 664.01 km2 and 10,557,810 inhabitants with a growth rate above 3% per year (BPS-Statistics of DKI Jakarta Province, 2020a). More than 5% of 210 million of the total population in Indonesia live in this city which creates Jakarta an exceptionally dense city (McCarthy, 2003). As the capital city of Indonesia—the world’s largest island country, Jakarta will inevitably continue to develop demographically and economically. The local government confirms that the large-scale infrastructural issues that arise in Jakarta are mainly caused by rapid urbanization and city growth. A satellite observation on Jakarta’s land cover conversion reveals that the total of built-up area in Jakarta counted up to 80.96% from the total area in the range of 15 years from 1990 to 2015 and the open green space was reduced from 39.28% to 12.76% simultaneously (Danniswari et al., 2020). The available GOS in Jakarta is recorded by the local government. Figure 5 illustrates Jakarta’s current condition where only 5% (approximately 32.96 km2) of the total area of the city is claimed to be green (DKI Jakarta Provincial Government, 2020), although it has been stated in local government regulation that the provision of GOS must be at least 30% of the total administrative area. While other European cities such as Stockholm, Berlin, and Paris have an average of 80m2, 30m2, and 15m2 of green space per capita respectively, Jakarta barely possesses 7.8 m2 GOS per capita (Kirmanto et al., 2012). Also, Jakarta is yet not catered by proper drainage systems and waste treatment management, coupled with the lack of green space, the city is challenged with various severe problems.

Figure 5. Existing green space in Jakarta Source: (DKI Jakarta Provincial Government, 2020) modified by Author

© ILPÖ 2020

27

Case study area: Jakarta

Jakarta’s urban heat island

3.1.1

As stated in the urban challenges in changing climate report by the World Bank, exposure to global increasing temperature and urban heat island effect is also experienced by Jakarta hence, the city is at risk. Figure 6 indicates Jakarta’s 2018 air temperature observation results where the maximum and minimum temperatures are 350C and 230C respectively (BPS-Statistics of DKI Jakarta Province, 2018). A comparison of the temperature of a particular year observed relative to the normal period (in this case the period of 1981-2010) reveals that in 2019 Jakarta underwent the warmest year with an anomaly temperature value of 0.820C (BMKG, 2020). Furthermore, a dataset on average temperature from the years 2000 and 2019 was extracted from Indonesia’s meteorological, climatological, and geophysical official agency (see figure 7), where the increase in average air temperature in Jakarta in the range of 19 years could be noticed.

40

Observation on Jakarta air temperatures by month in 2018

Temperature (0C)

35 30 25 20 15 10 5 0 Jan

Feb

Mar

Apr

Maximum Temperature

May

June

July

Aug

Minimum Temperature

Sept

Oct

Nov

Dec

Average Temperature

Figure 6. Observation on Jakarta air temperatures by month in 2018 Source: (BPS-Statistics of DKI Jakarta Province, 2018)

Figure 7. The difference in Jakarta’s average air temperature in 2000 and 2019 Source: (BMKG, 2019)

© ILPÖ 2020

28

Case study area: Jakarta

Several types of research and satellite observations on LST in Jakarta have also been conducted to support the speculation of urban heat island phenomenon in the dense urban area (Danniswari et al., 2020), (Rushayati et al., 2016), (Ramdhoni et al., 2016), (Manik & Syaukat, 2015). These studies cover the relationship between the increase of built-up land and the increased surface temperature of the city compared to the surrounding area which is still classified as undeveloped. Through NASA global surface temperature database, it was found that during this 100 year of observation there was a constant average temperature rise of more than 1.50C in Jakarta and the occurrence could be worsened by the presence of changing climate event which leads to a projection of 10C and 30C temperature increase by 2030 and 2100 respectively (The World Bank, 2011).

3.1.2

Jakarta’s urban flooding

Indonesia is geographically located in the ITCZ (Inter Tropical Convergence Zone) which makes Indonesia poured over by rain throughout the year. Jakarta is located on the northwest coast of Java island, right next to the Java inlet, with a tropical and rainy climate, making Jakarta humid, especially during October to March (Cybriwsky & Ford, 2001). Annual flooding event is not a novel occurrence for Jakarta since it has happened for years and the extreme 5-year flood events where heavy flooding events in 1996, 2002, and 2007 took place could be witnessed.

It is inevitable that without any other interventions, firstly, Jakarta itself is highly prone to flooding due to the existence of 13 rivers across the city which all flows to the northern part of Jakarta and the latter implies that Jakarta lies on a vast flood plain. Secondly, the combination of a region’s high precipitation rate and poor absorption of rainwater runoff through the soil due to land-use shift. The characteristics of the largest flood events in the previously mentioned years were observed where >200 mm per month could lead to a flood in Jakarta’s lowland that usually takes place in February (Parlindungan Tambunan, 2018). Jakarta’s average rainfall data from 2009-2018 are illustrated as seen in figure 8. Thirdly, the fact that 40% of Jakarta’s land is situated below sea water level and the city suffers from inadequate water management infrastructure situates it on further disadvantages. Jakarta’s land is currently experiencing gradual downward settling as its sinking rate reaches approximately between 5 to 10 cm per year (Schmidt, 2015) due to the continuous deep underground water extraction (Takagi et al., 2017) and combined with the pressure from today’s skyscrapers construction and continuous urban settlement growth (Abidin et al., 2011). Lastly, the lack of flood management infrastructure, degrading sewer and drainage capacity caused by solid waste pollution as well as reduction of stormwater absorption due to deforestation largely contribute to Jakarta’s flooding (Steinberg, 2007). As GOS and wetlands were mostly replaced due to high property demand, upstream areas lost their function to retain and sink the direct runoff which exacerbates the water movement to the north (Daly & Testolini, 2019).

Without green areas to filter and hold the water, it would be difficult for groundwater to

© ILPÖ 2020

29

Case study area: Jakarta

be recharged at the required level. Figure 9 illustrates subdistricts that are most prone to flooding events where the red part is marked as the most negatively affected.

Jakarta's monthly average of rainfall data 2009-2018

399.78 400

372.185

Percipitation rate (mm)

350 300 250 183.87

200

144.995

150

162.1 114.315 121.6

105.6

100

91.66

185.41

114.035

51.125

50 0 Jan

Feb

March

April

May

June

July

Aug

Sep

Oct

Nov

Dec

Month Figure 8. Jakarta's monthly average of rainfall data 2009-2018 (mm) Source: (BPS-Statistics of DKI Jakarta Province, 2020b)

Figure 9. Map of flood hazard in Jakarta based on events in 2013, 2014, and 2015 Source: (Jakarta Provincial Government's Regional Disaster Management Agency, 2016)

© ILPÖ 2020

30

Case study area: Jakarta

3.1.3

Jakarta’s policy strategies towards the green city

As a developing city, Jakarta is currently undergoing massive infrastructure development throughout the decades. The continuous development of infrastructure will eventually affect the city's environmental balance and the population’s health if it is not counterbalanced with sustainable planning. A city's growth towards sustainable and green aspects are much needed if the country aims to be relevant to the global issues the world is facing. Several investment opportunities towards green infrastructure in Indonesia including green buildings, renewable energy, sustainable waste management, low-carbon transport, and sustainable water management have been widely discussed within the past 5 years, however, in reality, there is no strategy firmly established. One of the agendas in achieving sustainable city growth is by providing the citizen with decent and low-carbon public transportation as well as establishing more green space across the city. In 2004, the Governor of Jakarta began to expand a proper public transportation network in Jakarta by establishing the first bus rapid transit (BRT) that is known as Trans Jakarta. Recently in March 2020, Jakarta has announced the first official mass rapid transport (MRT) operation.

3.2

Methodology on green streetscape prioritization screening

A methodological framework to prioritize the development of green streetscape is developed based on several aspects of screening evaluation in Jakarta’s smallest administrative level namely urban communities/subdistrict level (kelurahan). There are approximately 267 urban communities in Jakarta from a total of five administrative cities or municipalities (see figure 10). Thousand islands administrative regency are not included as part of analysis since it is not counted as city or urban area.

Greenstreet prioritization screening is done through hot spot analysis in the parts of Jakarta’s subdistrict where are most threatened to the previously discussed concern, namely urban heat stress and flood hazard. On the other hand, hot spot analysis on the most sensitive population with a certain age range namely the cluster which mainly affected and exposed to both hazards is also assessed. Hot spot analysis is chosen as a method since it has been seen as an effective screening tool for identifying zones for detailed and comprehensive risk assessment (Jalayer et al., 2013). Moreover, since the analysis is not done directly in the field, interviews, and questionnaires related to relevant stakeholders could not be conducted, thus hot spot analysis from desktop processing through GIS software is best believed to be a clearer method than applying weighted scoring overly throughout the parameters.

The objective of the screening evaluation is to have a separation between interesting and uninteresting subdistrict in terms of exposure to climate change impact. A hot spot evaluation in a basis of the geographical description of an urban tract which includes the example of population structure, in this case, is the incredibly sensitive population of incredibly old and young age, the location in a hydrological system which conveys flood

© ILPÖ 2020

31

Case study area: Jakarta

the most as well as locations where the highest exposure to thermal overload are detected. First, maps of the hot spot of heat stress, the hot spot of flood hazard, and the hot spot of the sensitive population are generated. To find the subdistrict which has the combination of the three, evaluation is determined by the complete variety of these three combinations. An interesting area for the proceeding step is understood as classifications. Since the data are processed in raster, the mean value of the classified hottest pixels required to be aggregated by subdistrict boundary polygon by employing statistical as table tool which is used to combine the table with all the subdistrict level boundaries. In this case study, the subdistrict area that holds the most prominent aggregation value for all of the three categories are considered to be the primary place where attention and a special focus on developing green infrastructure as a response to the identified situation are crucial. Subdistrict which has aggregated value above a certain standard deviation is classified as extraordinary in terms of each aspect.

Figure 10. Jakarta administrative boundaries Source: Author, 2020

3.2.1

UHI hot spots recognition

Before determining the UHI pattern in the city of Jakarta, thermal surface distribution across the city firstly can be identified by applying various LST retrieval algorithms.

Software-based LST analysis is chosen while there is no complete ground temperature data measurement available for every district in Jakarta (temperature observation stations are only located in three measuring points which are inadequate for a comprehensive assessment). A review paper on LST acquisition methods published by (Sekertekin & Bonafoni, 2020) explains that LST can be derived from several different

© ILPÖ 2020

32

Case study area: Jakarta

methods namely Mono-Window Algorithm, Single-Channel Algorithm, Radiative Transfer Equation Method, and Split-Window Algorithm. In this thesis, a straightforward image processing calculation is employed where metadata of Band 10, 4, and 5 from Landsat 8 OLI/TIRS are utilized. Landsat 8 images can be easily and freely acquired from the UGSG website. Following the process, all calculations are computed using the raster calculator toolbox that is available in ArcGIS software. The methodology to obtain LST from similar preceding studies and research was carefully explored. The adapted working process of LST retrieval is illustrated in figure 11.

Landsat 8 OLI/TIRS band 10 path/row 122/064

Top of atmospheric . radiance (ToA) or Lλ

Landsat 8 OLI/TIRS band 4 path/row 122/064

Landsat 8 OLI/TIRS band 5 path/row 122/064

Normalized difference build-up index (NDVI)

Proportion of vegetation (Pv) ToA brightness temperature (BT)

Land surface emissivity (LSE) or ε

Land surface temperature (LST) Figure 11. LST retrieval based on Lansat 8 OLI/TIRS image processing Source: Author 2020, based on equations provided by (Avdan & Jovanovska, 2016; Reddy, S. N., & Manikiam, B, 2017; Weng et al., 2004) For calculating Jakarta’s LST, Landsat 8 satellite imageries in the path and row of 122 and 64 were retrieved on April 22, 2020. The satellite images need to be projected to WGS84 / UTM zone 48s using a raster projection tool to be on the same geographical definition as Jakarta. From figure 11, it can be noticed that only Band 10 is employed in this calculation to achieve LST value since Band 11 is hardly recommended to use due to its larger stray light effect which could influence the absolute calculation result (Barsi et al., 2014). Before retrieving the temperature value on each of individual pixels, first, the digital number (DN) from OLI/TIRS metadata are required to be converted to the top of atmospheric (ToA) spectral radiance using the band-specific radiance rescaling factor provided inside the metadata file itself using the equation number 1 (Avdan & Jovanovska, 2016).

© ILPÖ 2020

33

Case study area: Jakarta

𝐿𝜆 = 𝑀𝐿 ∗ 𝑄𝑐𝑎𝑙 + 𝐴𝐿 − 𝑂𝑖

(1)

Where Lλ is the ToA spectral radiance (Watts/(m2 • sr • μm)), ML and AL are bandspecific multiplicative rescaling factor and additive rescaling factor form the metadata respectively (in this case is band number 10). Qcal is the quantized and calibrated standard product pixel values (DN). Lastly, Oi is the bias correction value which was calculated at 0.29 (Barsi et al., 2014). 𝐵𝑇 =

𝐾2 − 273.15 𝐾1 𝑙𝑛 [( ) + 1] 𝐿𝜆

(2)

Second, ToA radiance is converted to brightness temperature (BT) using the thermal constants of Band 10 (K1 = 1321.08 and K2 = 777.89) contained inside the metadata file by employing formula number 2 (Avdan & Jovanovska, 2016). “The brightness temperature is the blackbody’s temperature that would emit an identical amount of radiation at a definite wavelength.” (Sekertekin & Bonafoni, 2020). The purpose of subtracting the BT result with 273.15 is to obtain the value in degree Celsius. 𝑁𝐷𝑉𝐼 =

(𝑁𝐼𝑅 − 𝑅𝐸𝐷) (𝑁𝐼𝑅 + 𝑅𝐸𝐷)

(3)

𝑃𝑣 = (

𝑁𝐷𝑉𝐼 − 𝑁𝐷𝑉𝐼𝑚𝑖𝑛 2 ) 𝑁𝐷𝑉𝐼𝑚𝑎𝑥 − 𝑁𝐷𝑉𝐼𝑚𝑖𝑛

(4)

Proceeding to the next step, to retrieve the land surface emissivity (LSE or 𝜀) or the ability of surface material to release energy as thermal radiation into the atmosphere, NDVI or normal difference vegetation index is calculated. NDVI is one of the parameters used to quantify the density of vegetation cover presents in an area. NDVI can be obtained by dividing the value of near-infrared reflectance (NIR or Band 5 of Landsat 8) minus visible reflectance (RED of band 4 of Landsat 8) with the value of NIR plus RED (see equation number 3). The range of NDVI values are computed between -1 and 1 where a value below and 0 indicates water bodies and built-up area, 0–0.2 indicates barren rock, sand, or soil cover, 0.2-0.5 indicates the mixture of soil and vegetation such as shrubs or agriculture, and lastly the value which is bigger than 0.5 indicates a high density of vegetation (Reddy, S. N., & Manikiam, B, 2017). Later, the obtained NDVI values are used to estimate the proportion of vegetation as stated in equation number 4. 𝜀 = 0.004 ∗ 𝑃𝑣 + 0.986

(5)

For finding land surface emissivity, the LSE (𝜀) method based on the NDVI threshold provided by (Sobrino et al., 2008) is applied to the calculation. More detailed justification for distinct threshold values assigned for each NDVI range can be investigated further in the cited study. Finally, the end calculation for LSE can be simplified and expressed by equation number 5 written above. 𝐿𝑆𝑇 =

© ILPÖ 2020

𝐵𝑇 𝐵𝑇 1 + (𝜆 ∗ ρ ) ln ε

(6)

34

Case study area: Jakarta

The final or emissivity-corrected LST value result can be determined by the formula number 6 (Weng et al., 2004), where λ is the wavelength of emitted radiance (11.5 µm), ρ is Planck’s constant (h =6.626 * 10–34 Js) multiplied by the velocity of light (c = 2.998 * 10-8 m/s) divided by Boltzmann constant (s = 1.38 * 10-23 J/K). In direct, ρ can be expressed by the value of 14380. Since the final LST retrieval still results in the form of 30*30 pixels raster data for the entire study area, zonal statistical as table tool in ArcGIS is required to acquire the respective average value LST based on each Jakarta’s subdistrict division.

Moreover, citing from a literature study that has been carried out in the second part of this thesis, the occurrence of the UHI phenomenon in an area is usually supported by the existing condition of a city of its impervious surface and land cover. Considering that Jakarta is an urban center that lacks green vegetation and open green space, the city will probably remain vulnerable to the urban heat island effect if there is no action undertaken. Therefore, the correlation between LST, NDVI, and the normalized difference built-up index (NDBI) also important to be studied to explore the influences of the green areas and the build-up land on UHI. Furthermore, the highest and lowest temperature shown by the LST analysis result itself might not directly hint at the occurrence of UHI. Features with the highest value are prominent, however, it might not be a statistically meaningful hot spot. Therefore, ArcGIS optimized hot spot analysis (Getis-Ord Gi*) is employed to support cluster analysis regarding spatial correlation studies. Hot spot analysis is a spatial cluster detection method that identifies spatially significant concentrations of high values and low values associated with geographically neighboring features (Getis, A., and Ord, J.K., 1992).

Therefore, a feature is counted as statistically significant if it is also surrounded by highly rated values (ESRI, 2010). Getis-Ord-Gi* tool produces results in different Z-scores which indicate the measure of standard deviations and represent the grouping relevance for a particular calculated distance according to confidence level (Ranagalage et al., 2018). The greater the positive Z-score, the more intense the clustering is to form a hot spot. Meanwhile, the smaller the negative Z-score, the more intense the cold spot clustering will be. Keeping in mind that this technique of cluster and outlier analysis will be carried out to detect hot spots for extraordinary subdistrict cases for all different analysis parameters: UHI, flood risk, and sensitive population for the entire analysis process in the following subchapters.

3.2.2

Flood hazard recognition

The possibility of stormwater overflow or runoff formation can be simply predicted by calculating the topographic wetness index (TWI), as it is one of the quick and crucial preliminary indices to predict flooding events. “TWI is used to quantify topographic controls on hydrological processes” (Sørensen et al., 2006). In one of the research regarding flood risks identification for land use planning in Wreck Creek, Australia, TWI was employed as the basis for determining areas which prone to inundation based on

© ILPÖ 2020

35

Case study area: Jakarta

its index value (Pourali et al., 2016). Conceptually, the TWI value describes the level of land wetness assumed to be associated with vulnerability to flooding hazards, especially the ones caused by inundation. TWI is rather a relative value rather than an absolute one so that it can be utilized as an index to identify areas that relatively much contribute to runoff formation from a watershed outlet as it differs considerably depending on the topography of the studied landscape. The equation of TWI was first developed by (Beven & Kirkby, 1979) as part of runoff modeling. TWI assessment is implemented through the utilization of Digital Elevation Model (DEM), which in this study, high-resolution 8-meter precision Indonesian DEM can be readily obtained from National Digital Elevation Model (DEMNAS). The equation for TWI calculation can be seen below (7) 𝛼 𝑇𝑊𝐼 = ln tan 𝛽 where α is the flow accumulation and β is slope values. The TWI values creation can be done by simply employing flow direction based on the DEM data, flow accumulation, slope function as well as raster calculator tool to compute the above equation in ArcGIS software. The result of the flow accumulation function is in the form of raster data which later has the accumulated flow value in a river network in each raster cell. A high TWI value indicates that the area has a high level of perceived exposure to flood hazards and is associated with a flat topography with high flow density.

DEMnas (8 m resolution)

Topographic wetness index (TWI)

Flow accumulation and slope

Spatial statistic tool mapping clusters

Jakarta’s flood event history

Attribute table data of significant flood history, percentage affected areas and the height of inundation from 2013-2017

Merge flood events with respective subdistrict

Identification of flood hazard Figure 12. Identification of flood hazard workflow Source: Author, 2020

© ILPÖ 2020

36

Case study area: Jakarta

Determining the priority location is done by aggregating the maximum TWI value with the respective subdistrict map. However, since potentially flooded areas cannot be solely concluded by geoprocessing. To achieve more actual and validated inspection, a justification is required. Hence, the areas in Jakarta which have experienced flood events are also identified to match the desktop analysis and real-life situation (Riadi et al., 2018).

Figure 12 illustrates how flood hazard recognition can be carried out.

3.2.3

Sensitive population distribution

Although identifying a certain location in urban areas that is most conceivably exposed to the highest temperature and flooding hazard can determine the importance level for green intervention, delivering the issue of climate change does not merely discussing mitigating the urban heat and flood risk itself, but also the quality of life and social justice for the population, especially the sensitive ones such as elderly and young children.

Elderlies are considered a sensitive population group since they may have possessed congenital diseases that can be exacerbated by thermal stress or flood hazard. This also applies to noticeably young children under 5 years of age who are still very vulnerable to external conditions. The definition of elderly itself according to Law (UU) No. 13 Year 1998 concerning Elderly Welfare, are people aged 60 years and over or often referred to as residents of non-productive age. Evaluating the vulnerability of a population to high temperatures and flood hazards, therefore, requires demographic census information provided by the local government.

3.2.4

Conceptual solution for retrofit application on street-scale

In the last chapter of this thesis, the conceptual streetscape strategy will be proposed to the selected subdistrict after establishing the extraordinary case area by placing setting several aspects into account. While the subdistrict scale provides an integrative approach as the main idea, on the street level, which will be analyzed further by observing the current street condition via aerial imagery on GSV, further detailed and comprehensive recommendations are offered. Recommendations or primary solutions are drawn based on green streetscape benefits and performances that have been discussing in the second chapter of this thesis.

3.3 3.3.1

The graphical spatial analysis result UHI hot spots recognition

LST distribution in Jakarta is retrieved using the formulas written in subchapter 3.2.1. and can be seen in figure 14. Looking at the NDVI result (figure 13), a correlation can be drawn that areas with low NDVI values (marked by red) are undeniably warm. Based on the satellite imagery process, the highest temperature in Jakarta reaches 31.80C and the lowest is 21.270C. The presence of greater vegetation cover in the Southern part of Jakarta makes the area notably cooler than in the Northern and Central Jakarta.

© ILPÖ 2020

37

Case study area: Jakarta

Figure 13. Jakarta’s NDVI value Source: Author, 2020

Figure 14. LST retrieval for Jakarta based on Landsat 8 imagery process Source: Author, 2020

© ILPÖ 2020

38

Case study area: Jakarta

The complete imagery process of each step mentioned in the methodology section can be seen in Appendix I. Since the final LST analysis results are still in the form of raster data, it is necessary to aggregate the data into the respective subdistrict administrative boundaries by computing the average surface temperature using zonal statistical as a table tool in ArcGIS software. Mean values are preferred while it is considered reasonable in representing the temperature of an area boundary as a whole. According to the accumulation of the mean values, numerous subdistricts in West and Central Jakarta and a few located in the eastern part of Jakarta have the greatest aggregated temperature (see figure 15).

Figure 15. Substracted mean LST value based on respective subdistrict boundary Source: Author, 2020

However, as it has been described in the previous subchapter that recorded high temperature in a district does not make it immediately preserved as a hot spot. Therefore, figure 16 demonstrates the percentage significance of places to be clustered as hot spots and cold spots by justifying the result with the spatial statistical tool. The output classification of the Getis-Ord-Gi* mapping cluster tool is based on the Z-score, which symbolizes measures of standard deviation. A positive Z-score signifies the original attribute value is higher than the mean value, meanwhile, a negative Z-score reveals the original attribute value is below the mean average. For example, if the result shows a Z-score of +2.58 it can be translated as +2.58 standard deviations away from the mean average. The clustering can also be interpreted as seven significance and confidence levels (Gi Bin) where Z-score < -2.58 is classified as a very cold spot with 99%

© ILPÖ 2020

39

Case study area: Jakarta

confidence, Z-score in the range -2.58 - -1.96 is classified as a cold spot with 95% confidence, -1.96 - -1.65 is classified as a cool spot with 90% confidence, -1.65 – 1.65 is classified as insignificant, 1.65 - 1.96 is classified as a warm spot with 90% confidence, 1.96 – 2.58 is classified as a hot spot with 95% confidence, and lastly Z-score >2.58 is classified as a very hot spot with 99% confidence. The UHI analysis based on the intensity of clustering is shown in figure 16.

Figure 16. UHI score derived from Getis-Ord-Gi* analysis Source: Author, 2020

In this UHI analysis, Local Moran I is correspondingly employed for additional justification to examine the outliers of the neighborhood by spatially grouping the features based on four categories: High-High (HH) is where features with high values are surrounded by other high values features, High-Low (HL) is where high-value features are surrounded by low-value features, Low-High (LH) is where low-value features are surrounded by high-value features and finally Low-Low (LL) where the clustering is less significant because it contains features with low values that are also surrounded by low-value features. In these four patterns, HH can be categorized as hot spots, and HL is characterized as an island because it implies that a certain feature possesses a thermal anomaly by showing an extraordinarily high temperature while its adjacent features’ mean temperature are all below the average value. Studying from figure 17, it can be said that besides all the subdistricts located in Central and Eastern Jakarta denoted in red (hotspot), the subdistrict that is labeled as HL outlier (Kapuk subdistrict) also forms an island phenomenon.

© ILPÖ 2020

40

Case study area: Jakarta

Figure 17. UHI cluster and outlier analysis (Local Moran I) based on subdistrict’s temperature Source: Author, 2020

3.3.2

Flood hazard recognition

Deriving from the national digital elevation model (DEMnas) from the Geospatial Information Agency, figure 18 shows how the topography of Jakarta appears. The southern part of Jakarta is located considerably higher than the northern part. In such a way that all water bodies flow to the north. From the DEM raster data processing, Jakarta’s TWI values are retrieved and can be observed from figure 19 where it ranges between 2 to 26. There is no practical representation of the index since it is a relative value, therefore the range largely depends on the topography characteristics of the corresponding studied region. The higher the value the greatest opportunity for inundation to form. High values of TWI imply a high potential for saturation and low values of TWI imply a low potential for saturation.

To identify which subdistrict is prone to flood inundation due to lower sloping, the values of TWI are integrated with the subdistrict boundary delineation. However, it is not both reasonable and coherent if the TWI value is aggregated as an average value since the TWI value is comparative and a high value in one location will inevitably affect the subdistrict in generating stormwater runoff. The substracted TWI values for each subdistrict border are presented in figure 20 by employing a zonal statistical tool corresponding to its greatest score. It is understood that the Northern part of Jakarta is more susceptible to floods event since the water flow from precipitation follows gravity and flows downhill where eventually surface runoff is formed.

© ILPÖ 2020

41

Case study area: Jakarta

Figure 18. DEM of Jakarta Source: Author, 2020 (retrieved from DEMnas, Geospatial Information Agency of Indonesia)

Figure 19. Jakarta’s TWI distribution Source: Author, 2020

© ILPÖ 2020

42

Case study area: Jakarta

Figure 20. Substracted TWI value based on subdistrict boundary using zonal statistics Source: Author, 2020

Following the prior step for the previous parameter on UHI analysis, to acknowledge which location the prominent TWI values are laid, the Getis-Ord-Gi* tool is once more employed to examine the TWI aspect’s significance. Several subdistricts namely Cilincing, Marunda, and Rorotan are classified as places where inundation might most likely occur with the confidence of 99%. Furthermore, from figure 21 it can also be identified subdistricts like Kapuk Muara, Pluit, Kapuk, Pejagalan, and Sukapura also hold huge opportunities to be inundated with the confidence of 95%.

For the final stage of recognizing which subdistrict is most expected to be disrupted by highly flood events, a history of actual flood hazard incidents are observed for additional justification. Attribute data of major flood history, percentage affected areas in the prone subdistricts, and the height of inundation from 2013-2017 (see table 9) provided by Indonesian disaster management agency are integrated into the map below (see figure 23). The flood history and cluster pattern of most exposed subdistricts to flood is noticeably associated, where predominantly lays in Northern and Western part of Jakarta due to low elevation topography. From both procedures, significance clustering, and history flood map observation, it is concluded that Kapuk and Semper Timur are the two areas the severest affected by flooding in the last 5 years with a percentage of the area being submerged more than 50%.

© ILPÖ 2020

43

Case study area: Jakarta

Figure 21. TWI score derived from Getis-Ord-Gi* analysis Source: Author, 2020

Figure 22. Percentage of flood-prone areas in highly affected subdistricts within the year 20132017 in percentage Source: Author, 2020 based on data provided by (BPBD DKI Jakarta Province, 2018)

© ILPÖ 2020

44

Case study area: Jakarta

Table 9. Subdistricts that affected for more than 50% of its area by high flood hazard level for 5 years (2013-2017) Source: (BPBD DKI Jakarta Province, 2018) Subdistrict Kampung Melayu Tegal Alur Kapuk Rawa Buaya Semper Timur Dukuh Rambutan Kuningan Barat Kedoya Utara Bangka Pejaten Timur Pondok Labu Semper Barat Kembangan Utara Cililitan Rawa Terate Rawajati Jati Padang Duri Kosambi

3.3.3

% Area affected 100 98.67 96.25 85.84 84.59 71.04 69.98 69.89 62.70 61.15 57.93 57.93 56.42 56.01 55.25 54.66 51.98 51.79 51,03

Maximum inundation height (cm) 400 110 160 200 150 200 150 100 150 200 300 200 80 150 300 200 300 300 100

Sensitive population distribution

For sensitive population analysis, data on the number of extremely young and old citizens derived from Jakarta Central Statistic Agency for the year 2019 are employed and merged with the respective subdistrict. Figure 27 reveals subdistricts labeled in red as hot spots where locations such as Kapuk, Pulo Gebang, Tegal Alur, Cengkareng Timur, Duri Kosambi, and so forth show the result of Z-score more than +2.58 (classified as a very hot spot). Meanwhile, for the elderly population, subdistrict Pejagalan, Kapuk, Pluit, etc came out as the final result. These subdistricts are categorized as hot spots not only because they have an abundant amount of vulnerable populations, but also due to their stance that is surrounded by other notable subdistricts which are also inhabited by numerous sensitive populations. For both incredibly young and old population categories, subdistricts that are grouped as the very hot spot are Kapuk, Kapuk Muara, Cengkareng Barat, Cengkareng Timur, Pejagalan, Malaka Sari, and lastly Pondok Kopi.

© ILPÖ 2020

45

Case study area: Jakarta

Figure 23. Number of incredibly young age population within Jakarta’s subdistrict Source: Author, 2020

Figure 24. Number of incredibly old age population within Jakarta’s subdistrict Source: Author, 2020

© ILPÖ 2020

46

Case study area: Jakarta

Figure 25. Very young population score derived from Getis-Ord-Gi* analysis Source: Author, 2020

Figure 26. Elderly population score derived from Getis-Ord-Gi* analysis Source: Author, 2020

© ILPÖ 2020

47

Case study area: Jakarta

In the previous methodology section, it has been explained that locations that are screened and classed in the extreme significance cluster (in this case the value of +1.96 – 2.58 standard deviation away from mean value is classified as a hot spot with 95% confidence and >+2.58 standard deviation away from mean value is classified as a very hot spot with 99% confidence) for all categories will be reviewed in more detail for strategy implementation at the later stage in chapter 4. If the analysis is reviewed once more in terms of exposure to climate change alone, these two phenomena themselves, heat stress and flood are valid and inevitably alarming for all of the general population living in Jakarta. However, if those two strong impacts are coupled with the number of extremely sensitive inhabitants, a final location assumption on this screening phase can be consecutively drawn as the most prioritized example for green street infrastructure development. In this thesis, the most important area, where high values are obtained from all collective three parameters would be the primary or priority area. Where other places with only two combinations of highly rated resulting value would be also considered as important, but not as important as the primary place. After working through all the analysis processes, it turns out that there are no results that fit perfectly in every very hotspot clustering for all three aspects. Nevertheless, the areas considered most suitable and fulfilling for almost the three criteria is Kapuk district as it is clustered as an island (H-L) in terms of UHI, a hot spot in terms of flood hazard, and a very hot spot in terms of both extremely young and old populations. Therefore, in the following chapter, a conceptual strategy for retrofit application on a street-scale in Kapuk district will be carried out.

Table 10. Subdistricts with hot spot and very hot spot cluster result for two aspects only combination (secondary areas) and three complete aspects (primary or priority area) Source: Author, 2020 Subdistrict name(s) Kapuk, Semper Barat

Urban heat

Flood

Sensitive

island

hazard

population

✓

✓ ✓ ✓

✓ ✓

Kapuk, Kapuk Muara, Penjagalan, Pluit Kapuk

© ILPÖ 2020

✓

48

Conceptual strategy for retrofit application on street scale

4 Conceptual strategy for retrofit application on a street scale 4.1

Introduction

The conceptual strategy for retrofit application on a street scale will be elaborated systematically on the selected primary area that was elaborated in the previous chapter.

The priority area is where exactly on the map of Jakarta is considered important in terms of where more effort and human resources should be allocated to the plan. Since it is a huge question in strategic planning to have a structured guideline, therefore, the improvement and recommendation will be classified based on the types of green streetscape intervention’s benefits and performances contributing to each climate impact.

In the last chapter, the subdistrict namely Kapuk was chosen as the most problematic and conflicting area in terms of exposure to UHI impact, flood hazard as well as living residents at risk. Kapuk is one of the urban villages or subdistricts located in West Jakarta with a total area of 5.63 km2 and a high number of populations of 167,909 (2019), therefore the population density of this subdistrict is calculated at 29,823 inhabitants/km2.

The characteristics of Kapuk’s land use consist of densely populated settlement areas, industrial, enterprises, and commercial areas. Where the population in Kapuk mainly relies their economic activities and income on garments and textile industrial processing.

Figure 27. Kapuk subdistrict land use 2019 Source: Author based on (Cipta Karya, Spatial Planning Office and Land of DKI Jakarta Province, 2020)

© ILPÖ 2020

49

Conceptual strategy for retrofit application on street scale

Kapuk is densely dominated by both prestigious and informal settlements, therefore until today, there is still a huge social, health, and inequality gap between the two classes.

Kapuk itself consists of 16 neighborhoods (Rukun Warga, abbreviated as RW) which seven of them are categorized as neighborhoods that retain low socio-economic characteristics (Fitria & Setiawan, 2014). Due to its severely dense urban area, greenings in forms of open green space and community commonplace can be barely found in this subdistrict thus the temperature rise is noticeable. In 2019, the Indonesian Meteorology, Climatology, and Geophysical Agency (BMKG) also noted that West Jakarta is so far the hottest administrative city among the five others with the temperature reaching 340C during the day in October. The subdistrict environment which is influenced by industrial and commercial activities also make this area other passed by heavy vehicles and contributes greatly to the pollution that can degrade the health of its citizen.

Kapuk is also known as a flood-prone area due to several degrading environmental conditions such as water catchment area reduction and groundwater critical illegal extraction (JICA, 2012). Furthermore, inundation often occurs because of heavy rain, poor drainage, and flooding river. As a district that has always been heavily impacted by flood disasters due to inadequate drainage system, it was recorded that during the year 2015-2016 there were up to 14 affected neighborhoods out of 16 total neighborhoods with various flood inundation heights (maximum recorded 100 cm) and duration up to seven days (Augustine Adibroto et al., 2019). In the Kapuk subdistrict itself, there is no maintenance or normalization program from the local government for rivers, canals, embankments, ditches, drainages, nor reservoirs. Moreover, Kapuk is passed by the Cengkareng River (Kali Cengkareng) which is not maintained, indicated by river degradation from solid waste pollution and blackwater discharge from the surrounding activities.

4.2 4.2.1

Retrofitting based on the green streetscape’s roles and benefits Heat mitigation

In some earlier research, it is studied that urban heat island occurs within a city is mostly due to the land cover category and building geometry. However, changing street typology or the urban realm is not a simple task that requires a huge amount of cost and permission from different city planning departments. Therefore, enhancement approaches through employing small-scale, decentralized, and green-based intervention to the compacted urban area such as instances that have been reviewed in chapter two is considered as a suitable and fitting action. By looking through the possible places in retrofitting the urban street greening, in this case, public streets and roads, some potential solutions are suggested for the conflicted area. Where the settlement characteristic and commercial activities along the river need to be taken into account. It can be observed in figure 28 that RW 03, 11, 12, 13, 16 are the most exposed neighborhood to the thermal heat stress.

© ILPÖ 2020

50

Conceptual strategy for retrofit application on street scale

Figure 28. Kapuk subdistrict’s neighborhood division and its thermal stress analysis Source: Author, 2020 Table 11. Sites within Kapuk that hold potential for green streetscapes recommendation for heat mitigation Source: Author, 2020 based on Kapuk’s Google Street View 2019 Potential type of street greening intervention for urban thermal stress reduction (1) Shading provision Street trees along the collector roads

Figure 30. Recommendation on street trees

Figure 31. Stormwater tree in Louisville

planting in St. Kapuk Kayu Besar

Source: Louisville MSD (NACTO, 2017)

Street trees are one of the most flexible green streetscape elements that could be suited almost anywhere, such as office and commercial strips, urban parks, housing plots, parking areas, and rights of way. The provision of road-side trees canopy in urban areas helps to shade the paved exterior which will directly cool down the warm surface temperature. Shading provision from trees certainly will give more comfortable, pleasant, and secure feelings to the

© ILPÖ 2020

51

Conceptual strategy for retrofit application on street scale

pedestrian walking through the public places. However, several aspects are necessary to be addressed such as trees’ performance on providing advantages to the micro-climate largely depend on the age of the trees (the more mature, the better performance), the width of the canopy, and a sufficient vacant area for the tree roots to grow. Adequate irrigation is also crucial for tree’s health especially in the tropical climate’s hot dry season that lasts from March to mid-June in Indonesia. Mahogany and Indonesian bay leaf are two examples of trees that are favored and suitable to be planted by the side of the roads.

Tree pits or planters on the road median

Figure 32. Recommendation on road median

Figure 33. Stormwater planter in Portland

planter planting in St. Pedongkelan Raya

Source: (NACTO, 2017)

Tree pits help to direct the stormwater runoff from adjacent streets which later can be utilized as passive irrigation to the existing trees. The presence of vegetated road media also could soothe the traffic noise and provide a safer crosswalk for a pedestrian. Similar to planting street trees, the wide range of options of vegetation has to consider and contemplates on tree species with deep roots, resistant to puddles, and able to absorb and store the water within low soil permeability (Setyowati, 2007).

(2) Urban thermal cooling Pervious concrete block on walkways, commercial strips, and parking lots

Figure 34. Recommendation on permeable

Figure 35. Permeable surface in Atlanta

parking lot in St. Royale Boulevard

Source: (NACTO, 2017)

Instead of constructing non-permeable parking lots, pervious concrete or grass concrete block can be used as alternatives to reduce the heat absorbed and reflected by the pavement.

Replacing the impervious surface with the previous one directly contributes to people’s thermal comfort in occupying public spaces. Furthermore, the water that percolates through the paver blocks also indirectly offers a cooling process to the surface and air temperature. Since the

© ILPÖ 2020

52

Conceptual strategy for retrofit application on street scale

subdistrict is considered to have flat topography, it will not be a problem to install a pervious surface as it needs to be integrated with a place that does not have a slope of more than 5%.

Porous pavements are also great options to be installed on a residential common meeting place and kids playground. In the case of poor soil absorption, a connecting pipe to an adjacent drainage or sewer system is necessary.

Vertical potted garden on urban communities and VGS as governmental and industrial buildings façades .

Figure 36. Recommendation on small-scale

Figure 37. Green Village in East Jakarta

vertical greening in St. Masjid Al-Munawarah

Source: (Antonius, 2018)

Despite the advanced assembly and expensive technology of green façade or living wall that does not suit the parts of settlement areas in this subdistrict, a more moderate knowledge can be adapted from this typology by employing a simpler and more affordable vegetation greening system for residential areas. Self-built intermediate-height vertical potted gardens could be an option for retrofitting on a residential path. Meanwhile, commercial and light industrial buildings could be integrated with green façade as a new sustainable approach to capture exterior airborne contaminants as well as filter gas emission and solid matters. The provision of vegetation integration in built-up urban areas helps to reduce both air and surface temperature by the result of the transpiration process itself which the intercepted rainwater is released through the vegetation’s stomata. Greenings on buildings also block direct sunlight exposure to the building this automatically lowering the indoor’s temperature and offer more comfort to the people inside.

© ILPÖ 2020

53

Conceptual strategy for retrofit application on street scale

4.2.2

Flood mitigation

Figure 38. Kapuk subdistrict’s affected neighborhood on flood inundation 2013-2015 Source: Author, 2020 based on (BPBD DKI Jakarta Province, 2018) Table 12. Sites within Kapuk that hold potential for green streetscapes recommendation for flood mitigation Source: Author, 2020 based on Kapuk’s Google Street View 2019/2020 Potential type of street greening intervention for (1) Runoff flow reduction Rain gardens on the collector road curb extension and small-scale biofiltration/ community gardens for settlement

Figure 39. Recommendation on rain garden

Figure 40. Traffic circle in Berkeley

establishment in St. Royale Boulevard

Source: (MIG, n.d) on re:Street

While it has been widely stated that bioretention systemsoSource: have been successfully reduced stormwater peak volume in countries with temperate climates such as the United States and Australia, the peak flow reductions result depends heavily on the catchment area proportion, drainage construction, and rainfall rate frequency, depth, and durations. Therefore, the wide range of vegetation options that can adapt to various tropical climate’s rainfall characteristics is very much vital. The choice of

© ILPÖ 2020

54

Conceptual strategy for retrofit application on street scale

vegetation must be selected with the consideration that these plants are tolerant o temporary inundation and quickly adapted to different types of growing mediums. An earlier study on different effective plants for biofiltration or bioretention purpose has been carried out by (Payne et al., 2019), it is found that vegetation such as Cannaceae flowers, Ti plants, Lemon Grass, Seduduk plant, etc are suitable for collecting runoff as well as mineral removal.

(2) Peak flow reduction Swales with trees and thick vegetation along arterial roads by the riverside

Figure 41. Recommendation on continuous

Figure 42. Bioswale for street integration

vegetated swale in St. Pedongkelan Raya

Source: (NACTO, 2013)

As bio or vegetated swales can attenuate the stormwater flow rate, it is also a great intervention for pollution filtration, therefore, it will increase the quality of surface runoff water that infiltrates the soil, hence improved the quality of restored groundwater recharge for the population’s demand purpose. Trees planted along the continuous swales are expected to catch and divert the runoff from surrounding roads and pedestrian pavements. Tree leaves or vegetation canopies help to divert the rainfall in which direct runoff flow and formation on the ground can be avoided. Besides, the more variety of vegetation in a swale (it varies from trees, shrubs, and grasses), the more effective the delaying process of surface runoff rate will be.

(3) Groundwater recharge Rainwater harvesting for urban community and industrial area

Figure 42. Recommendation on constructing

Figure 43. Bioswale in Portland for water harvesting

rainwater tanks in St. Pedongkelan Raya

Source: (Greywater Action, 2014)

In the eastern part of Kapuk district, where majorly dominated by the industrial, densely builtup area and buildings percentage are also very high, green space is almost not available in this entire area. Starting from this condition, the idea of rainwater harvesting tanks construction is established. The on-site and non-centralized rainwater tank can be built inside or above the

© ILPÖ 2020

55

Conceptual strategy for retrofit application on street scale

ground to accommodate the building’s roof runoff. Construction in both residential and industrial areas can be carried out with the agreement of the urban community itself or out of the awareness of the industrial estate owners.

Permeable asphalt on arterial and local roads, driveways, and pathways

Figure 43. Recommendation on pervious

Figure 44. Example on pervious pavement

pavement installation in St. Rusun BCI Raya

Source: (NACTO, 2013)

The suitable typology of green streetscape infrastructure in terms of the ecological function of surface runoff filtration with a relatively narrow location can be applied to the use of local road surface covering materials using low runoff coefficient materials of 50-60% such as gravel and grass block (Angelia, 2017).

4.2.3

Integrated solution

Carrying out a complete review on potential retrofitting green streetscape infrastructure on the chosen area based on its exposure level is the aim of this thesis. However, we shall not forget that besides contemplating on environmental and land use planning issues, human comfort on the streets is also a top priority. Therefore, the street UGI planning must also be followed by decent street elements such as crosswalks, sufficient urban lighting, urban furniture, and secure bicycle lane to improve the population’s wellbeing. So that a real integrated planning approach can be achieved.

4.3

Future challenges

Identification of interesting areas where the green streetscape is required to be employed has been done in the previous chapter as well as the retrofitting conceptual potential solution on street-level has been proposed earlier. However, this preliminary screening and recommendation cannot be merely carried out if there are no government and community desire to change the current damaging situation. The most important of all is the urgency of the government towards development that prioritizes green goals.

Technical and financial regulations regarding the establishment and maintenance of green infrastructure integration must be strengthened and taken critically. If not, Jakarta will continue to be gradually degraded and fail to build its resilience. Educational engagement through the younger generation on how important are ecological values to

© ILPÖ 2020

56

Conceptual strategy for retrofit application on street scale

urban areas also needs to be emphasized. After all, Jakarta as a developing city needs to start paying more focus and attention to sustainable development.

Jakarta as a developing city must consolidate its regulation on decreasing green spaces completely and deliver a serious penalty if it is being violated. And also as a capital city, Jakarta needs to start restoring more decent water drainage management, especially in the slums area so it could be connected and integrated with the progression and evolution of green infrastructure development. Moreover, street green infrastructure design guidelines were all originally invented and proposed in developed countries with more temperate climates. Therefore, its performance and success must be reconsidered and cannot be merely translated into a tropical region condition. For instance, bioretention basins which were designed based on annual recurrence interval (ARI) in the USA will not fit the heavy rainfall events in tropical countries like for example Singapore and Indonesia, therefore for further detailed technical guidelines, UGI in tropical cities needs to be planned based on water quality volumed and depth (VWQ and VWD) as parameters (Wang et al., 2017). Another concern that needs to be considered is the knowledge of the types of trees and vegetation that can survive the hot temperatures of tropical climates with intense rainfall and humidity must be investigated and chosen carefully. Technological guidelines and handbooks for the dense tropical cities themselves are very much required to be developed by the experts.

© ILPÖ 2020

57

Conclusion

5 Conclusion Development of green infrastructure which cannot be necessarily carried out on a brandnew urban tract could be incorporated with grey infrastructure elements, such as streets and roads, as an alternative resolution especially in a dense urban area like in this case, the city of Jakarta, Indonesia. Jakarta itself still does not possess any framework or guidelines on green infrastructure planning and lacks green spaces maintenance policy.

Therefore, this thesis reviews the streetscape prioritization framework in global practices which later could be applied in the selected case study area by carrying out two levels of screening (subdistricts and street level) to give potential initial recommendations on green streetscape infrastructure within the prone subdistricts due to cumulative climate change impacts.

Out of 267 subdistricts in Jakarta, several names appeared as potential locations for green streetscape retrofitting assessed and judged by the severity of climate change impacts experiences by these sites. One particular subdistrict, namely Kapuk, is taken as an example for potential solutions and suggestions in integrating streets with possible small-scale UGI. Not only considering the severe climate impacts on the urban areas the inhabitants at risk are also taken into account to create a more comprehensive evaluation. This thesis arose with the expectation of urban planners could utilize the preliminary screening and suggestion as a first move in reckoning and contemplating on sustainable development.

In brief, green infrastructure offers many advantages for cities, not only in terms of mere aesthetic but for the urban areas to become more sustainable. Replacing or equipping parts of built-up areas with green infrastructure might not completely alter and solve the issue, however, it certainly helps cities to regain their ecological values. For instance, planting trees along the streets and decreasing the total impervious area in a city could lead to the city’s surface temperature decrease and the building’s energy use reduction due to micro thermal cooling. The development of green infrastructure based on stormwater runoff management also provides the opportunity to minimize the formation of inundation as soil ground regains its ability and capacity to infiltrate surface runoff, although nevertheless, it will never eliminate the flooding events. As a mitigation measure, green street infrastructure also plays a role in improving water bodies’ quality.

Moreover, green streetscape planning should be part of integrative urban planning and incorporation with transportation planning as it also caters to walkability and movement of people in general to support sustainable living. Consequently, planning should not be looking only at one aspect nor perspective (e.g., transport corridor or land use planning itself), however, needs to start including environmental concern in the implementation as greener and better streetscape could also lead to a healthier, more decent and comfortable life. In conclusion, effective green streetscape infrastructure delivers resiliency and self-reliance both at a neighborhood and street level.

© ILPÖ 2020

59

References

6 References Abidin, H. Z., Andreas, H., Gumilar, I., Fukuda, Y., Pohan, Y. E. & Deguchi, T. (2011).

Land subsidence of Jakarta (Indonesia) and its relation with urban development.

Natural Hazards, 59(3), 1753–1771. https://doi.org/10.1007/s11069-011-9866-9 Ainy, C. N., Harlan, D. & Hanan, H. (2018). Stormwater management approach to increase the quality of urban streetscape in Sudirman Street, Bogor City. IOP Conference Series: Earth and Environmental Science, 179, 12019. https://doi.org/10.1088/1755-1315/179/1/012019 Angelia, T. (2017). Green open space development concept as an ecological function to absorb rainwater in Rungkut district, Surabaya city [Master thesis]. Institut Teknologi Sepuluh November, Surabaya. http://repository.its.ac.id/44404/7/3215205003-Master_Thesis.pdf Antonius, I. (2018). Taking a peek at the beauty of Kampung Hijau in the East Corner of Jakarta. https://www.liputan6.com/news/read/3644768/foto-mengintip-asrinyakampung-hijau-di-sudut-timur-jakarta?page=1 Augustine Adibroto, T., Wijayanti, P., Pratama Adhi, R. & Nugroho, R. (2019).

Preliminary study on socio-economic aspect towards Jakarta climate-resilient (case study: Cengkareng District, West Jakarta and Penjaringan District, North Jakarta).

IOP Conference Series: Earth and Environmental Science, 314, 12035. https://doi.org/10.1088/1755-1315/314/1/012035 Avdan, U. & Jovanovska, G. (2016). Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data. Journal of Sensors, 2016(2), 1–8. https://doi.org/10.1155/2016/1480307 Baró, F., Calderón-Argelich, A., Langemeyer, J. & Connolly, J. J. T. (2019). Under one canopy? Assessing the distributional environmental justice implications of street tree benefits in Barcelona. Environmental science & policy, 102, 54–64. https://doi.org/10.1016/j.envsci.2019.08.016 Barsi, J., Schott, J., Hook, S., Raqueno, N., Markham, B. & Radocinski, R. (2014).

Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration.

Remote Sensing, 6(11), 11607–11626. https://doi.org/10.3390/rs61111607 Benedict, M. & MacMahon, E. (2002). Green Infrastructure: Smart Conservation for the 21st Century.

Berland, A., Shiflett, S. A., Shuster, W. D., Garmestani, A. S., Goddard, H. C., Herrmann, D. L. & Hopton, M. E. (2017). The role of trees in urban stormwater management. Landscape and Urban Planning, 162, 167–177. https://doi.org/10.1016/j.landurbplan.2017.02.017 Beven, K. J. & Kirkby, M. J. (1979). A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant. Hydrological Sciences Bulletin, 24(1), 43–69. https://doi.org/10.1080/02626667909491834 BfN. (2017). Urban Green Infrastructure: A Foundation of attractive and sustainable cities.

© ILPÖ 2020

61

References

https://www.bfn.de/fileadmin/BfN/planung/siedlung/Dokumente/UGI_Broschuere_En g.pdf Blair, J., Roldan, C., Ghosh, S. & Yung, S.-H. (2017). Greening Rail Infrastructure for Carbon Benefits. Procedia Engineering, 180, 1716–1724. https://doi.org/10.1016/j.proeng.2017.04.334 BMKG. (2019). Online data: BMKG database center. Meteorology, Climatology, and Geophysical Agency. http://dataonline.bmkg.go.id/akses_data BMKG. (2020). Extreme climate change: Anomaly analysis of annual average air temperature. Meteorology, Climatology, and Geophysical Agency. https://www.bmkg.go.id/iklim/?p=ekstrem-perubahan-iklim Bowler, D. E., Buyung-Ali, L., Knight, T. M. & Pullin, A. S. (2010). Urban greening to cool towns and cities: A systematic review of the empirical evidence. Landscape and Urban Planning, 97(3), 147–155. https://doi.org/10.1016/j.landurbplan.2010.05.006 BPBD DKI Jakarta Province. (2018). Subdistricts according to high flood hazard levels. https://bpbd.jakarta.go.id/assets/attachment/document/ BPS-Statistics of DKI Jakarta Province. (2018). Jakarta Air Temperatures by Month and Observation Station, 2018. Statistics Indonesia. https://jakarta.bps.go.id/dynamictable/2020/03/23/467/1-2-2-suhu-udara-jakartamenurut-bulan-dan-stasiun-pengamatan-2018.html BPS-Statistics of DKI Jakarta Province. (2020a). DKI Jakarta Province in Figures 2020.

BPS-Statistics of DKI Jakarta Province.

BPS-Statistics of DKI Jakarta Province. (2020b). Rainfall in Jakarta by month and observation station. Statistics Indonesia. https://jakarta.bps.go.id/dynamictable/2020/03/23/469/1-2-4-curah-hujan-di-dkijakarta-menurut-bulan-dan-stasiun-pengamatan.html CDOT. (2010). The Chicago Green Alley Handbook: An Action Guide to Create a Greener, Environmentally Sustainable Chicago. Chicago Department of Transportation. https://www.chicago.gov/content/dam/city/depts/cdot/Green_Alley_Handbook_2010. pdf Cheng, Y.-Y., Lo, S.-L., Ho, C.-C., Lin, J.-Y. & Yu, S. (2019). Field Testing of Porous Pavement Performance on Runoff and Temperature Control in Taipei City. Water, 11(12), 2635. https://doi.org/10.3390/w11122635 The City of Portland BES. (4. August 2004). Flow Test Report: Siskiyou Curb Extension. City of Portland Bureau of Environmental Services. http://www.portlandonline.com/shared/cfm/image.cfm?id=63097 Coutts, A. M., Tapper, N. J., Beringer, J., Loughnan, M. & Demuzere, M. (2013).

Watering our cities. Progress in Physical Geography: Earth and Environment, 37(1), 2–28. https://doi.org/10.1177/0309133312461032 Cybriwsky, R. & Ford, R. L. (2001). City Profile: Jakarta, Cities, Vol. 18, Artikel 3, 199– 210. https://doi.org/10.1016/S0264-2751(01)00004-X

© ILPÖ 2020

62

References

D. Armson, P. Stringer & A.R. Ennos (2013). The effect of street trees and amenity grass on urban surface water runoff in Manchester, UK. http://dx.doi.org/10.1016/j.ufug.2013.04.001 Daly, P. & Testolini, P. (2019). A Responsible Urban Rejuvenation of Jakarta. CTBUH Journal 2019(IV), 8.

Danniswari, D., Honjo, T. & Furuya, K. (2020). Land Cover Change Impacts on Land Surface Temperature in Jakarta and Its Satellite Cities. IOP Conference Series: Earth and Environmental Science, 501, 12031. https://doi.org/10.1088/17551315/501/1/012031 Davis, A. P., Stagge, J. H., Jamil, E. & Kim, H. (2012). Hydraulic performance of grass swales for managing highway runoff. Water research, 46(20), 6775–6786. https://doi.org/10.1016/j.watres.2011.10.017 Derkzen, M. L., van Teeffelen, A. J.A. & Verburg, P. H. (2017). Green infrastructure for urban climate adaptation: How do residents’ views on climate impacts and green infrastructure shape adaptation preferences? Landscape and Urban Planning, 157, 106–130. https://doi.org/10.1016/j.landurbplan.2016.05.027 DKI Jakarta Provincial Government. (2020). Information on green space of DKI Jakarta province. DKI Jakarta Provincial Government. https://jakartasatu.jakarta.go.id/portal/apps/opsdashboard/index.html#/d4432a1cc03 1400c8e8f610345022f81 Dreiseitl, H. & Wanschura, B. (June 2016). Strengthening Blue-Green Infrastructure in Our Cities: Enhancing Blue-Green Infrastructure & Social Performance in High Density Urban Environments. https://www.zu.de/lehrstuehle/soziooekonomik/assets/pdf/Ramboll_Woerlen-etal_BGI_Final-Report_small-1.pdf Ebrahimian, A., Wadzuk, B. & Traver, R. (2019). Evapotranspiration in green stormwater infrastructure systems. The Science of the total environment, 688, 797– 810. https://doi.org/10.1016/j.scitotenv.2019.06.256 EPA. (2016). Green Infrastructure and Climate Change Collaborating to Improve Community Resiliency.

ESRI. (2010). Hot Spot Analysis (Getis-Ord Gi*) (Spatial Statistics). https://pro.arcgis.com/en/pro-app/tool-reference/spatial-statistics/hot-spotanalysis.htm Fitria, N. & Setiawan, R. (2014). Identification of Environmental Characteristics Slum Settlements in Kapuk Village, West Jakarta. Journal of Technology ITS, 3 No. 2.

10.12962/j23373539.v3i2.7290 Foster, J., Lowe, A. & Winkelman, S. (February 2011). The Value of Green Infrastructure for Urban Climate Adaptation. Washington, DC. The Center for Clean Air Policy. http://ccap.org/assets/The-Value-of-Green-Infrastructure-for-UrbanClimate-Adaptation_CCAP-Feb-2011.pdf Getis, A., and Ord, J.K. (1992). The Analysis of Spatial Association by Use of Distance Statistics, 24, 189–206. https://doi.org/10.1111/j.1538-4632.1992.tb00261.x (Geographical Analysis).

© ILPÖ 2020

63

References

Gilbreath, A. N., Hunt, J. A. & McKee, L. J. (2015). Cesar Chavez Streetscape Improvement Project Report: Case Study Site and Technical Reports. https://www.sfei.org/documents/cesar-chavez-streetscape-improvement-projectreport-rainy-season-2014-15 Greywater Action. (2014). Rainwater Harvesting – Sourcing the Rain. https://greywateraction.org/rainwater-harvesting/ Hansen, R., Rall, E., Chapman, E., Rolf, W. & Pauleit, S. (2017). Urban Green Infrastructure Planning: A Guide For Practitioners. Practitioners’ guide to urban green infrastructure planning, based on research in European cities as part of the EU FP7 project. GREEN SURGE. http://greensurge.eu/working-packages/wp5 Herath, H.M.P.I.K., Halwatura, R. U. & Jayasinghe, G. Y. (2018a). Evaluation of green infrastructure effects on tropical Sri Lankan urban context as an urban heat island adaptation strategy. Urban Forestry & Urban Greening, 29, 212–222. https://doi.org/10.1016/j.ufug.2017.11.013 Herath, H.M.P.I.K., Halwatura, R. U. & Jayasinghe, G. Y. (2018b). Modeling a Tropical Urban Context with Green Walls and Green Roofs as an Urban Heat Island Adaptation Strategy. Procedia Engineering, 212, 691–698. https://doi.org/10.1016/j.proeng.2018.01.089 Hu, M., Zhang, X., Siu, Y., Li, Y., Tanaka, K., Yang, H. & Xu, Y. (2018). Flood Mitigation by Permeable Pavements in Chinese Sponge City Construction. Water, 10(2), 172. https://doi.org/10.3390/w10020172 Huang, J.-M. & Chen, L.-C. (2020). A Numerical Study on Mitigation Strategies of Urban Heat Islands in a Tropical Megacity: A Case Study in Kaohsiung City, Taiwan. Sustainability, 12(10), 3952. https://doi.org/10.3390/su12103952 Im, J. (2019). Green Streets to Serve Urban Sustainability: Benefits and Typology.

Sustainability, 11(22), 6483. https://doi.org/10.3390/su11226483 Inostroza, L., Palme, M. & La Barrera, F. de (2016). A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity, and Adaptive Capacity for Santiago de Chile. PloS one, 11(9). https://doi.org/10.1371/journal.pone.0162464 Jalayer, F., Risi, R., Paola, F., Iervolino, I., Giugni, M., Topa, M., Yonas, N., Nebebe, A., Kibassa, D., Cavan, G., Renner, F. & Lindley, S. (2013). GIS-based Identification of Urban Residential Hotspots to Flooding and the Quantification of the Uncertainties for two African Citiesanalysis method with nonlinear dynamic analysis.

Jayakaran, A., Knappenberger, T., Stark, J. & Hinman, C. (2019). Remediation of Stormwater Pollutants by Porous Asphalt Pavement. Water, 11(3), 520. https://doi.org/10.3390/w11030520 JICA (2012). The Simulation Study on Climate Change in Jakarta Indonesia: Final Report. https://openjicareport.jica.go.jp/pdf/12150934.pdf Kabisch, N., Korn, H., Stadler, J. & Bonn, A. (2017). Nature-Based Solutions to Climate Change Adaptation in Urban Areas. Springer International Publishing. https://doi.org/10.1007/978-3-319-56091-5

© ILPÖ 2020

64

References

Kabisch, N., Stadler, J., Korn, H. & Bonn, A. (2016). Nature-based solutions to climate change mitigation and adaptation in urban areas. BfN-Skripten: Bd. 446. Bundesamt für Naturschutz. https://www.bfn.de/0502_skriptliste.html Kappis, C. (2013). Effect and Function of Green Tracks. Berlin, Germany.

Grüngleisnetzwerk. http://www.gruengleisnetzwerk.de/images/downloads/effects.pdf Kautsar, L. (2018). Analysis of Transjakarta's Crossing Bridge (JPO) as an Alternative Integration of Infrastructure with Green Open Space Through the Utilization of Geographic Information System (GIS) and Its Implementation in DKI Jakarta. http://dx.doi.org/10.24895/SNG.2017.2-0.450 Kirmanto, D., Ernawi, I. S. & Djakapermana, R. D. (2012). Indonesia Green City Development Program: an Urban Reform, 48th ISOCARP Congress, 13. http://www.isocarp.net/data/case_studies/2124.pdf Klemm, W., Lenzholzer, S., Heusinkveld, B. & van Hove, B. (Hg.) (2013). Towards green design guidelines for thermally comfortable streets.

Klemm, W., Lenzholzer, S. & van den Brink, A. (2017). Developing green infrastructure design guidelines for urban climate adaptation. Journal of Landscape Architecture, 12(3), 60–71. https://doi.org/10.1080/18626033.2017.1425320 Kota Hijau. (2016). Strategy for increasing green open space. http://sim.ciptakarya.pu.go.id/p2kh/knowledge/detail/strategi-peningkatan-ruangterbuka-hijau Lassandro, P. & Di Turi, S. (2017). Façade retrofitting: from energy efficiency to climate change mitigation. Energy Procedia, 140, 182–193. https://doi.org/10.1016/j.egypro.2017.11.134 Lau, J. T. & Mah, D. Y. S. (2018). Green Wall for Retention of Stormwater, Pertanika J. Sci. & Technol. 26 (1): 283 - 298, 17. https://www.researchgate.net/publication/322921333 UU No. 26 Year 2007 Spatial Planning (2007).

Li, H., Harvey, J. T., Holland, T. J. & Kayhanian, M. (2013). Corrigendum: The use of reflective and permeable pavements as a potential practice for heat island mitigation and stormwater management. Environmental Research Letters, 8(4), 49501. https://doi.org/10.1088/1748-9326/8/4/049501 Lim, H. S. & Lu, X. X. (2016). Sustainable urban stormwater management in the tropics: An evaluation of Singapore’s ABC Waters Program. Journal of Hydrology, 538, 842–862. https://doi.org/10.1016/j.jhydrol.2016.04.063 Lucke, T., Mohamed, M. & Tindale, N. (2014). Pollutant Removal and Hydraulic Reduction Performance of Field Grassed Swales during Runoff Simulation Experiments. Water, 6(7), 1887–1904. https://doi.org/10.3390/w6071887 Lukes, R. & Kloss, C. (December 2008). Managing Wet Weather with Green Infrastructure Municipal Handbook: Green Streets. https://www.epa.gov/sites/production/files/201510/documents/gi_munichandbook_green_streets_0.pdf Manik, T. K. & Syaukat, S. (2015). The impact of urban heat islands: assessing vulnerability in Indonesia. https://pubs.iied.org/pdfs/10721IIED.pdf

© ILPÖ 2020

65

References

Maria Rinaldi, B. & Tan, P. Y. (2019). Urban Landscapes in High-Density Cities: Parks, Streetscapes, Ecosystems. https://issuu.com/birkhauser.ch/docs/urban_landscapes_in_high_density_ci McCarthy, P. (2003). Urban Slums Reports The case of Jakarta, Indonesia. World Bank. https://www.ucl.ac.uk/dpu-projects/Global_Report/pdfs/Jakarta.pdf MIG, I. (n.d). Green infrastructure case studies: Traffic circles. Zugriff am 10 Decemer 2020, verfügbar unter https://www.restreets.org/case-studies/traffic-circles Moreton Bay Waterways and Catchments Partnership (1. Juni 2006). Water Sensitive Urban Design: Technical Design Guidelines for South East Queensland. https://www.planning.org.au/documents/item/8031 NACTO. (2013). Urban Street Design Guide. Island Press/Center for Resource Economics. 10.5822/978-1-61091-534-2 NACTO. (2017). Urban Street Stormwater Guide. Island Press/Center for Resource Economics. 10.5822/978-1-61091-814-5 Norton, B. A., Coutts, A. M., Livesley, S. J., Harris, R. J., Hunter, A. M. & Williams, N. S.G. (2015). Planning for cooler cities: A framework to prioritise green infrastructure to mitigate high temperatures in urban landscapes. Landscape and Urban Planning, 134, 127–138. https://doi.org/10.1016/j.landurbplan.2014.10.018 Othman, A. R. & Sahidin, N. (2016). Vertical Greening Façade as Passive Approach in Sustainable Design. Procedia - Social and Behavioral Sciences, 222, 845–854. https://doi.org/10.1016/j.sbspro.2016.05.185 Parlindungan Tambunan, M. (2018). Characteristic of rainfall in the flood period in DKI Jakarta in 1996, 2002, and 2007. MATEC Web of Conferences, 229, 2012. https://doi.org/10.1051/matecconf/201822902012 Payne, E., Fowdar, Harsha, Marthanty, Rika Dwinanti, Pawitan, H., Marsudiantoro, D. & McCarthy, D. (14. August 2019). Application of Green Infrastructure for Water Management in Bogor: A Review. The Australia-Indonesia Centre. urbanwater.australiaindonesiacentre.org Phillips, C., Stevenson, P., Aquino, A., Chen, G., Ikezoe, P., Langlois, L., Varat, A., Hirsch, A., Olea, C., Thomas, J., Satterwhite, G., Goyal. Manish, Kraai, R., Morris, D. & Wier, M. (March 2015). Walkfirst Streetscape Prioritization. San Francisco. https://sfgov.org/sfplanningarchive/walkfirst-phase-3-streetscape-prioritization Pitakasari, A. R., Lasan, J., Ming Leong, K., Dewa, K., Jariya, S. & Vinh, T. (2.

November 2010). Creating Green Space in Urban Areas: Community Garden Project in Jakarta, Indonesia. https://www.iatssforum.jp/forum/docs/report_47.pdf Pourali, S. H., Arrowsmith, C., Chrisman, N., Matkan, A. A. & Mitchell, D. (2016).

Topography Wetness Index Application in Flood-Risk-Based Land Use Planning.

Applied Spatial Analysis and Policy, 9(1), 39–54. https://doi.org/10.1007/s12061014-9130-2 Puczko, K. & Jekatierynczuk-Rudczyk, E. (2020). Extreme Hydro-Meteorological Events Influence to Water Quality of Small Rivers in Urban Area: A Case Study in Northeast Poland. Scientific reports, 10(1), 10255. https://doi.org/10.1038/s41598020-67190-4

© ILPÖ 2020

66

References

Radić, M., Brković Dodig, M. & Auer, T. (2019). Green Facades and Living Walls—A Review Establishing the Classification of Construction Types and Mapping the Benefits. Sustainability, 11(17), 4579. https://doi.org/10.3390/su11174579 Ramdhoni, S., Rushayati, S. B. & Prasetyo, L. B. (2016). Open Green Space Development Priority Based on Distribution of air Temperature Change in Capital City of Indonesia, Jakarta. Procedia Environmental Sciences, 33, 204–213. https://doi.org/10.1016/j.proenv.2016.03.071 Ranagalage, M., Estoque, R., Zhang, X. & Murayama, Y. (2018). Spatial Changes of Urban Heat Island Formation in the Colombo District, Sri Lanka: Implications for Sustainability Planning. Sustainability, 10(5), 1367. https://doi.org/10.3390/su10051367 Reddy, S. N., & Manikiam, B (2017). Land Surface Temperature Retrieval from LANDSAT data using Emissivity. 12(20), 9679-9687 (International Journal of Applied Engineering Research).

Revi, A., D.E. Satterthwaite, F. Aragón-Durand, J. Corfee-Morlot, R.B.R. Kiunsi, M. Pelling, D.C. Roberts & W. Solecki. (2014). Urban areas. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability: Part A: Global and Sectoral Aspects.

Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.

Riadi, B., Barus, B., Widiatmaka, Yanuar, M. J. P. & Pramudya, B. (2018). Identification and delineation of areas flood hazard using high accuracy of DEM data. IOP Conference Series: Earth and Environmental Science, 149, 12035. https://doi.org/10.1088/1755-1315/149/1/012035 Roehr, D., Laurenz, J. & Kong, Y. (2008). Green Envelopes: Contribution of Green Roofs, Green Facades, and Green Streets to Reducing Stormwater Runoff, CO 2 Emissions, and Energy Demand in Cities. In N. She & M. Char (Hg.), Low Impact Development for Urban Ecosystem and Habitat Protection (S. 1–8). American Society of Civil Engineers. https://doi.org/10.1061/41009(333)13 Rubinato, M., Nichols, A., Peng, Y., Zhang, J.-m., Lashford, C., Cai, Y.-p., Lin, P.-z. & Tait, S. (2019). Urban and river flooding: Comparison of flood risk management approaches in the UK and China and an assessment of future knowledge needs.

Water Science and Engineering, 12(4), 274–283. https://doi.org/10.1016/j.wse.2019.12.004 Runnalls, K. E. & Oke, T. R. (2000). Dynamics and Controls of the near-surface Heat Islands of Vancouver, British Columbia. Physical Geography, 21(4), 283–304. https://doi.org/10.1080/02723646.2000.10642711 Rushayati, S. B., Prasetyo, L. B., Puspaningsih, N. & Rachmawati, E. (2016).

Adaptation Strategy Toward Urban Heat Island at Tropical Urban Area. Procedia Environmental Sciences, 33, 221–229. https://doi.org/10.1016/j.proenv.2016.03.073 Schmidt, C. W. (2015). Delta Subsidence: An Imminent Threat to Coastal Populations.

Environmental health perspectives, 123(8), A204-9. https://doi.org/10.1289/ehp.123A204

© ILPÖ 2020

67

References

Sekertekin, A. & Bonafoni, S. (2020). Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation. Remote Sensing, 12(2), 294. https://doi.org/10.3390/rs12020294 Selbig, W. R. (2018). Evaluating the Potential Benefits of Permeable Pavement on the Quantity and Quality of Stormwater Runoff. www.usgs.gov/science/evaluatingpotential-benefits-permeable-pavement-quantity-and-quality-stormwater-runoff?qtscience_center_objects=0 Setyowati, D. L. (2007). Assessment of land suitability evaluation for settlements using Geographic Information System (GIS), Geography Journal FIS - UNNES. https://journal.unnes.ac.id/nju/index.php/JG/article/view/111/113 Shafique, M., Kim, R. & Kyung-Ho, K. (2018). Evaluating the Capability of Grass Swale for the Rainfall Runoff Reduction from an Urban Parking Lot, Seoul, Korea.

International journal of environmental research and public health, 15(3). https://doi.org/10.3390/ijerph15030537 Sobrino, J. A., Jimenez-Munoz, J. C., Soria, G., Romaguera, M., Guanter, L., Moreno, J., Plaza, A. & Martinez, P. (2008). Land Surface Emissivity Retrieval From Different VNIR and TIR Sensors. IEEE Transactions on Geoscience and Remote Sensing, 46(2), 316–327. https://doi.org/10.1109/TGRS.2007.904834 Sørensen, R., Zinko, U. & Seibert, J. (2006). On the calculation of the topographic wetness index: evaluation of different methods based on field observations.

Hydrology and Earth System Sciences, 10(1), 101–112. https://doi.org/10.5194/hess-10-101-2006 Souch, C. A. & Souch, C. (1993, September). The effect of trees on summertime below canopy urban climates:: a case study Bloomington, Indiana., Artikel Journal of Arboriculture 19(5). http://joa.isaarbor.com/request.asp?JournalID=1&ArticleID=2581&Type=2 Steinberg, F. (2007). Jakarta: Environmental problems and sustainability. Habitat International, 31(3-4), 354–365. https://doi.org/10.1016/j.habitatint.2007.06.002 Taher, H., Elsharkawy, H. & Newport, D. (2019). The Influence of Urban Green Systems on the Urban Heat Island Effect in London. IOP Conference Series: Earth and Environmental Science, 329, 12046. https://doi.org/10.1088/17551315/329/1/012046 Takagi, H., Fujii, D., Esteban, M. & Yi, X. (2017). Effectiveness and Limitation of Coastal Dykes in Jakarta: The Need for Prioritizing Actions against Land Subsidence. Sustainability, 9(4), 619. https://doi.org/10.3390/su9040619 Thom, J. K., Szota, C., Coutts, A. M., Fletcher, T. D. & Livesley, S. J. (2020).

Transpiration by established trees could increase the efficiency of stormwater control measures. Water research, 173, 115597. https://doi.org/10.1016/j.watres.2020.115597 Transport Services, City of Toronto. (2017). Green Streets Project Selection & Priority Analysis.

© ILPÖ 2020

68

References

https://www.arcgis.com/apps/Cascade/index.html?appid=5dc6a7d4f70344558c42c5 e667999487 UACD. (2010). Low impact development: A Design Manual for Urban Areas. University of Arkansas Press. http://uacdc.uark.edu/work/low-impact-development-a-designmanual-for-urban-areas UN DESA. (16. Mai 2018). 68% of the world population projected to live in urban areas by 2050, says UN [Press release]. New York. https://www.un.org/development/desa/en/news/population/2018-revision-of-worldurbanization-prospects.html UNISDR. (2011). Global Assessment Report on Disaster Risk Reduction 2011 – Revealing Risk, Redefining Development. Geneva, Switzerland. UNISDR Secretariat.

Vico, G., Revelli, R. & Porporato, A. (2014). Ecohydrology of street trees: design and irrigation requirements for sustainable water use. Ecohydrology, 7(2), 508–523. https://doi.org/10.1002/eco.1369 Wadzuk, B. M., Hickman, J. M. & Traver, R. G. (2015). Understanding the Role of Evapotranspiration in Bioretention: Mesocosm Study. Journal of Sustainable Water in the Built Environment, 1(2), 4014002. https://doi.org/10.1061/JSWBAY.0000794 Wang, J., Chua, L. H. C. & Shanahan, P. (2017). Evaluation of pollutant removal efficiency of a bioretention basin and implications for stormwater management in tropical cities. Environmental Science: Water Research & Technology, 3(1), 78–91. https://doi.org/10.1039/C6EW00285D Weng, Q., Lu, D. & Schubring, J. (2004). Estimation of land surface temperature– vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467–483. https://doi.org/10.1016/j.rse.2003.11.005 Wilkinson, S., Feitosa, R. C., Kaga, I. T. & Franceschi, I. H. d. (2017). Evaluating the Thermal Performance of Retrofitted Lightweight Green Roofs and Walls in Sydney and Rio de Janeiro. Procedia Engineering, 180, 231–240. https://doi.org/10.1016/j.proeng.2017.04.182 The World Bank. (2011). Jakarta Urban Challenges in a Changing Climate: Mayors' Task Force On Climate Change, Disaster Risk & The Urban Poor. Jakarta.

Xiao, Q. & McPherson, E. G. (2011). Performance of engineered soil and trees in a parking lot bioswale. Urban Water Journal, 8(4), 241–253. https://doi.org/10.1080/1573062X.2011.596213 Yau, W., Radhakrishnan, M., Liong, S.-Y., Zevenbergen, C. & Pathirana, A. (2017).

Effectiveness of ABC Waters Design Features for Runoff Quantity Control in Urban Singapore. Water, 9(8), 577. https://doi.org/10.3390/w9080577

© ILPÖ 2020

69

Appendix

7 Appendix I. Land surface temperature complete process Top of Atmospheric Radience (ToR) from Jakarta’s Landsat 8 imagery processing

Brightness temperature (BT) from Jakarta’s Landsat 8 imagery processing

© ILPÖ 2020

71

Appendix

The proportion of vegetation (Pv) from Jakarta’s Landsat 8 imagery processing

Land surface emissivity (𝜀) from Jakarta’s Landsat 8 imagery processing

© ILPÖ 2020

72