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Tools for urban analysis

Analysis of São Paulo’s spatial configuration and its implications in defining ploycentricity

Claudiu Forgaci

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Tools for urban analysis

Analysis of São Paulo’s spatial configuration and its implications in defining ploycentricity Final report on spatial modeling and analysis with GIS and Space Syntax

by: Claudiu Forgaci Jesus M. Garate Jose Lenin Garcia Ortiz Design & Planning Support Systems (AR9320) EMU Technology Course

dr. Akkelies van Nes, dl. Alexander Wandl, dr. ir. Rob van Nes

PREFACE

This paper represents our understanding of the tools introduced in the Technology course of the EMU programme and their applicability in our planning and design process. It is not just meant to show our ability to use the presented software, but also to prove that we are able to identify how planning and design issues can be efficiently addressed with them. Therefore, we will try to explain how the two tools, Space Syntax and GIS, helped us to support the strategy and projects developed during our studio work. Triggered by the issue of extreme social and spatial segregation, our strategy focuses on understanding the elements in São Paulo’s spatial configuration that led to this reality and, thus, defining a new polycentric, better connected metropolitan region, meant to evenly spread development across its territory. By dealing with a still developing metropolitan region, we had to consider that finding complete data for our analysis will be difficult. Shared by several municipalities, the urbanized area of São Paulo’s Metropolitan Region doesn’t have a coordinated statistical and spatial database yet. This is mainly the case of GIS, where the results are extremely dependent on available geographically referenced data. Consequently, a part of our analysis also relies on available mapping provided by local authorities and a visual-intuitive positioning of socio-economic data taken from Google Maps, Open Street Map and IBGE (Brazilian Institute of Geography and Statistics). This approach is effective mainly because of the large, metropolitan scale of our strategy, where geographical accuracy is not as important as identifying global development trends and principles.

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INTRODUCTION

Within the studio’s framework on mobility and urbanization we were given the case of Rodoanel, São Paulo’s new ring road and its consequences on the areas along its northern section. During our analysis and especially after our site visit we realized that a project of this scale needs to be supported by a general metropolitan strategy. We know that the main purpose of a ring road is to relieve the inner city of congestion, and to deviate freight and throughpassing traffic to the edge of the city. But what happens with this relieved inner state? How can we make sure that congestion will not be recycled in the future? Therefore we oriented our strategy towards the whole urbanized area of the São Paulo Metropolitan Region. (Figure 1)

Figure 1 Project task: São Paulo’s new ring road related to the general strategy

In a metropolitan area like São Paulo, where the transport system is mainly based on the road infrastructure and travel distances are very long, it is essential to develop a global, well interconnected network. Is this happening in the actual conditions of São Paulo’s road network? Are these sub-regions within the city well interconnected? Are the centralities from those sub-regions highly or poorly integrated in the local and global scale? These questions are addressed in order to answer the general query: Why the periphery, especially the Eastern region of São Paulo is underdeveloped and what can we do in order to reconnect it with the rest of the city? Is it about the transport services? Is it about infrastructure? Or is it about the general spatial structure of the city?

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Based on our observations on the Space Syntax analysis, there are two types of approach to these issues, further detailed in our strategic projects. First, centralities following the most integrated road structure of the city should be consolidated and functionally enriched. Second, areas which exhibit high functional opportunities, but seem to be poorly integrated in the city’s functional and spatial structure, will be further developed in order to improve their integration. Either way, we address a wide range of scales, from the large, metropolitan scale in developing our general strategy to the lower scale of local communities on the project level. The tools introduced in the Technology course, and especially the Space Syntax analysis proved to be very useful in understanding that accessibility from the peripheral areas of São Paulo to the expanded center is low, having direct repercussions on the quality of life of the inhabitants of the Metropolis. During the Technology course we were presented three analytical tools, meant to support our Planning and Design process: Depthmap for Space Syntax analyzes spatial configurations as networks of choices that describe connectivity and integration in the system; ArcGIS is a complete tool for geographically referenced data analysis, very useful to find facts for processes that sometimes can be very intuitive for a planner or an urban designer; In addition to these computer based tools, the introduction of transport networks concepts helped us to develop a general understanding about modal choices, transport and traffic services. Still, the richness lies in the combination of these tools. This way the street networks can be compared to the geographical data to predict the socio-economic effects of an intervention and to match the network’s characteristics to different activities from different parts of an urban area. In addition to transport concepts, the comparative analysis helped us to understand the spatial issues that São Paulo is facing today.

METHODOLOGY

For Space Syntax we used the Segment Analysis since the Axial Analysis would have segregated short lines, which are made of many of São Paulo’s regions due to the curve traces of the unplanned streets patterns. The existing axial map for the Municipality of São Paulo was generated in GIS from road centerlines, while the rest of the lines were manually added. As a consequence, the Axial Analysis doesn’t show accurate results, since the two differently drawn parts of the map show different degrees of integration when put together. Segment Analysis takes into account this issue and makes the integration of joining segments more accurate. In the first part we performed a global analysis of the whole Metropolitan Region followed by a Low Radius Angular Analysis to find the routes with fewer deviations. These two analyses were performed in order to describe the global scale of São Paulo. After this we performed the low metric analysis to find the most integrated local centralities, and relate the different results. Further we compared the Space Syntax results with geographical statistical data. Unfortunately, GIS data is currently under survey, and therefore it is unavailable except for the street network of part of the Municipality of São Paulo and the boundaries among municipalities of the metropolitan area. To solve this problem we use data gathered during the field trip, the research stage, and local observation from Google Maps, Open Street Map and IBGE as well as available maps that showed the existing centralities within the city, clusters of activities and the location of the Expanded CBD, Human Development Index, income, transport, land use etc.. In the second part we performed the local analyses for our strategic interventions within the Metropolitan Area, comparing the existing and proposed situations. These analyses are going to be explained in a specific section of the report assigned to each intervention. 5


GLOBAL ANALYSIS

In order to define the general structure of the city we started with o global analysis of São Paulo’s street network. As we already assumed, there is high level of global integration concentrated in the expanded center of the city: the old core, Av. Paulista, Av. Faria Lima and the new business district positioned along Pinheiros river (Figure 2, angular analysis R5, graph 1 and 2). Based on the R5 angular analysis and also supported by a global angular analysis (Figure 2, angular analysis radius n, graph 3), we can clearly identify the main radial highway network of the metropolitan area.

Figure 2 Angular analysis R5: total depth (1) and integration (2); Choice radius n (3).

By comparing Integration with the main routes choice (Figure 2) we can deduce that the roads running to the east were constructed and designed as a way out of the city center and not to integrate the eastern region. By contrast in the expanded center and the region ABC (South-East), main routes are functioning as part of a globally wellintegrated network. When Figure 2 -total depth (1) and integration (2)- are compared with socio-economic data such as employment rate (Figure 3) we can identify that the most globally integrated areas in the city are those with higher employment rate. In addition, when these two figures are compared with the cultural facilities (Figure 4) – including universities and high educational level schools – the relation between highly integrated and locations of the facilities are proportionally related. Moreover, when Figure 2 - Choice radius n (3). Main routes whithin the city- is compared with the location of road marketing banners we can see that they match with the most highlighted routes within the city (Figure 5). These comparisons between the Segment Analysis and Socio-economic Data show clearly the monocentric structure of the city, where development is almost exclusively concentrated in the expanded center, and the importance of the industrial region ABC located in the South-Eastern area of São Paulo.

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Figure 3 Employment rate.

Figure 4 Cultural and Education Facilities

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Figure 5 Road’s Marketing Banners

According to this problem of an unbalanced city in terms of development, we proposed a strategy to reduce the gap between the segregated East and the highly integrated expanded center. In this metropolitan strategy the industrial region of ABC plays a very important role since it is the most integrated area in the eastern region, and could benefit other neighboring areas.

Figure 6 Local integration: metrical R500m

In order to complete the image of the city’s spatial structure and more accurately relate it to pedestrian movement, local integration needs to be taken into account as well. By performing the metrical R500m analysis, we managed to highlight the local polycentric spatial configuration of the city. This way we can support our initial observation that the São Paulo Metropolitan Region is a complex, alternating patchwork of rational and organic street networks (Figure 6). By overlapping it with the metropolitan road network, we can clearly conclude that the highways act like a network of barriers, separating these totally different patches of spatial configuration. This part of the analysis will be further developed in one of our projects dealing with the issue of spatial segregation and urban patches.

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SANTO ANDRE INDUSTRIAL STRIP Claudiu Forgaci

Figure 7 Industrial sites developed along major radial infrustructure. Highlighted study area : Santo Andre industrial strip.

The Santo Andre industrial strip is one of the areas chosen for our strategic interventions. As already highlighted in our global analysis, it is one of the globally most integrated areas along the city’s radials (Figure 2, graph 1). By overlapping the position of the industrial areas with the previously identified main road network, we can clearly see that industry is highly dependent on major high-capacity road and rail infrastructure (Figure 7). The intervention focuses on completing this radial connectivity with a circular connection, in order to improve the global integration of the Eastern Region. Also, by improving transport and traffic services along the region and by adding new local connections, the two sides of the strip, currently isolated one from each other, can be reconnected.

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Figure 8 South-Eastern region: Integration R500, R2000 and R5000

In the first part I looked at the whole South-Eastern region outside São Paulo’s administrative boundaries. As I point it out in Figure 8, the low radius of 500m, the mid-radius of 2000m and the large 5000m exhibit different patterns: on a low scale, walkability seems to be concentrated in small centralities, scattered around the region; with a 2000m radius, the graph starts to show traces of radial connectivity, characteristic to the whole metropolitan region of São Paulo, while on a larger radius the area Based on on-site observations and these analyses we can draw the preliminary conclusion that this part, as well as other peripheral parts of the metropolitan region, is mainly car-oriented and discourages slow local integration. To support this assumption, I will further investigate the region with the angular analysis and step depth.

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The low radius (R5) angular analysis turned out to be useful in highlighting more precisely the radials, which are not only more integrated, but also with the less angular deviations. Moreover, by running a step depth analysis for the highlighted tangential route (yellow line), it is surprisingly more connected on the other (again radial) direction, rather than along its trajectory. (Figure 9) As a result, these investigations prove the necessity for tangential (circular) reconnection of the region. This way, the dominance of the radial development could be balanced with improving sub-regional connections. More exactly, as part of the strategy’s goals, this region needs to be improved with an evenly distributed, interconnected and integrated network. This rationality applies to both the local-pedestrian level and the global-car based connections. The existing fast connections will be improved, while slow connections need to be created all along the industrial strip.

Figure 9 South-Eastern region: Integration angular R5 and Step Depth

On a closer look, the study area, part of one of the main radial developments introduced in our global analysis, acts like a barrier in the spatial configuration of the city. The private land of the industrial strip, the eight-lane highway in the north and the commuter rail line in the south make up this strong disconnection between north and south (Figure 10). The aim of the strategic intervention is to overcome this obstacle, to improve fast connections (Figure 10b, red) and to introduce new local - pedestrian connections (Figure 10b, yellow).

Figure 10 Santo Andre Industrial Strip: Barriers (a) and connections (b).

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Figure 11 Santo Andre industrial strip: Barriers. Source: Google street view.

In the current situation, the spatial segregation between the upper and lower side of the strip is clearly visible. Connections are only made by fast, highway connections, thus excluding any kind of pedestrian connection. By adding a pedestrian-friendly street network to one of these fast connections, the global integration of the area is significantly increased. Both the highways and the lower scale pedestrian streets are better integrated in the region.

Figure 12 Intervention area: new connections. Global angular analysis, integration: (1) existing situation, (2) proposed situation.

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GIS ANALYSIS

In order to complete the analysis of São Paulo’s spatial configuration, I will turn to two analytical methods in GIS. First, I will illustrate a simple but highly relevant method to identify affected areas bordering the highways of São Paulo. Due to insufficient spatial data, I will illustrate the method with the case of Rotterdam. Second, I will analyze the spatial consequences of building the new metro line proposed in the general strategy. Affected areas along highways As already presented, high speed connections (highways) cover the whole metropolitan area, having negative impact on the quality of life, especially in their vicinity. Therefore, I will look at the highway network and buildings, especially housing, surrounding them. This is an important analysis in the case of my intervention, as a great amount of low quality housing is directly facing the industrial strip, and by highlighting the affected areas it is easy to identify areas that have to be functionally converted. But since the buildings of São Paulo are not available in geographic formats, this method cannot be accurately applied. Information can only be attained by overlapping the highway network with a given buffer (processed in GIS) with a non-geographically referenced map of the buildings (satellite map, autocad 2d map etc.), thus conclusions can only be rather visual then quantifiable. However, I would like to illustrate this method with the case of Rotterdam, where all the GIS data was available. The following illustrations highlight a part of Rotterdam’s highway network, the buildings within a given buffer distance, all these related to the housing and housing-related functions in the area. (Figure 13) Figure 13 Buildings influenced by high-speed traffic

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Network Analysis – Service Areas around Metro Stations Having a primary role in the global strategic intervention, connections are as important as centralities. Moreover, connections between large centers end up in creating other, local centers along their trajectory, on lower scales. In our intervention, this is precisely the case of the new sub-regional metro line. It connects the new major centralities but also encourages the development of small centralities around its stations. The previous Space Syntax analysis helped to develop the arguments for new local connections in the intervention area in order to achieve a better integration of the neighborhoods around the Santo Andre industrial strip. I showed that by adding a new local road structure, the spatial integration of the area has a considerable growth. However, Space Syntax only takes into account the spatial configuration of the city. But how does a new metro line (invisible in the Space Syntax analysis) improve the accessibility and how does it add to the vitality and walkability of the area? This information can be extracted by analyzing the network structure of the area with GIS. The only input features needed are the existing road centerlines and the position of the new metro stations with specific service areas (Figure 14).

Figure 14 Samples of the Network dataset - road structure (a) and the Facilities with Service Areas - Metro stations (b)

The analysis consists of comparing the service area around one of these stations before and after the intervention. The main goal of the project was to create slow, pedestrian friendly connections meant to enhance the qualities of local public space. Therefore, two specific radiuses were used for illustrating the station’s influences on local walkability: -

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The smaller, 500m radius, representing the maximum distance that pedestrians might walk around the station while using the public functions attached to it. This is the most intense area around the station and it is useful in locating public and especially commercial activities compatible with the proposed intermodal node. The larger, 1000m radius, considered as the maximum distance that people might walk to get to the station. This distance allows us to define the maximum area that could be developed with housing and services that are still accessible and don’t need additional public transport.

On larger distances, I considered that it is more likely that people would choose public transport. Therefore, this aspect was excluded from the analysis. 14


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Figure 15 Network Analysis: Service Areas around metro stations - existing situation.

For this analysis a larger sample of the Santo Andre industrial area was studied, thus including a section of the metro line with eight stops. In order to coherently integrate this analysis with the previous steps and to facilitate further conclusions, the outlined area is the same as the one analyzed with Space Syntax. At the same time, it is important to study a larger number of occurrences of the metro stations, so that the study becomes more comprehensive and, therefore, specific spatial patterns might be discovered. After running the network analysis with the service areas around metro stations on the existing situation, we can identify four types of service areas (Figure 15) with the following characteristics: -

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Areas within the existing residential urban fabric (1) have a relatively even distribution in all directions from the metro station. These are nodes that characterize the area of Corinthias-Ithaquera studied in one of the other projects of the strategy. Service areas which are next to industry, dominated mainly by highways (2) have a linear and smaller catchment area because of the reduced number of connections with neighboring urban areas. Areas around fast connections across the industrial strip have a medium-sized service area (3), thus describing a partially spread, partially restricted area along the highways. Areas within the urban fabric, but still at the intersection of highways (4), are more expanded on the direction of the highways and weakly connected to the rest of the street network.

But why don’t we move the metro stations within the most locally integrated areas, even though they might be less integrated on global scale? On one hand, metro stations have to be positioned in the most accessible spots in order to serve as many ‘users’ as possible. On the other hand, it is essential to position them along the main existing infrastructure (the highway in this case). In order to fulfill both conditions, the highway network has to be 15


downgraded, where possible, and supported with new and more local connections. The proposal develops one of these nodes by adding new local connections to the area around the metro station (Figure 16).

Figure 16 Proposal: new connections (a) defined by the proposed road pattern (b).

The following map shows the updated service area for the node developed in the strategic project. As a consequence, the service area becomes evenly spread in all directions, covering a relatively maximum area within the limits of the two radiuses. Also, one of the strengths of the proposal is the fact that it uses the whole service area of the metro station. (Figure 17)

Figure 17 Network Analysis: Service Areas around metro stations - proposed situation

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A CRITICAL OVERVIEW

Each tool allowed us to analyze the city’s spatial configuration from a different angle. By combining the Space Syntax analysis with the GIS Network Analysis, both based on principles learned about transport networks, a more comprehensive result could be achieved. These tools have specific strengths but also some flaws: -

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Space Syntax describes the urban spatial configuration and focuses on pedestrian behavior. Public transport or motorized traffic is not covered. Also, in the specific case of São Paulo where the highway network spreads all over the city, it is very difficult to define a correct road network that takes into consideration all the (numerous) bridges or elevated sections (unlinks), from an aerial view. So, because we don’t have a complete knowledge or mapping of such a large metropolitan area, we cannot guarantee that all unlinks were provided in our axial/segment maps. Therefore we have to mention that the study is approximated and differences between our results and reality might occur. GIS was very helpful in completing the Space Syntax analysis with information which is not covered by the former. The network analysis takes into account additional aspects, such as facilities with specific service areas around them, allowing us to study the position of metro stations and their influences on local vitality and walkability. Still, GIS has its own flaws as well. It is difficult to process and extract relevant information for areas where geographically referenced data is poorly available. In our case, the network analysis was based and developed from a single shapefile of the road center lines and an additional, manually drawn point file containing the proposed metro stops. We don’t know the date when the file was created and the road network is incomplete, therefore this analysis is also an approximation of reality. The two previous tools described above are only useful when they answer a coherent spatial question. More exactly, a good knowledge of the urban issues of the study area is necessary in order to fully get the advantages of the analysis. Here, the knowledge gained about transport and traffic modeling, principles about modal choices and trips were very useful to identify and address the right questions.

CONCLUSION

To summarize, São Paulo has a highly integrated city center on global level but extremely segregated local centralities. This is clearly visible in its socio-economic aspects. Therefore, economic activities are mainly concentrated in the expanded center, while mono functional housing areas define the periphery. Main infrastructural elements, following a radial structure, connect this center with the edge of the city and connect it with the outside. Additionally, industry is concentrated along these radials in continuous strips, thus creating barriers between the housing areas along its two sides. This way, we might say that there is a large difference between the extreme vitality of the center and the mono functionality of the edge. Our strategy aims to address these issues, by finding the opportunities in locally integrated sub-centralities all across the city and by creating or improving the connections between them. Improvements in traffic and transport services but also functional and social revitalization of the sub-regions are the main actions taken in order to achieve this. We have to mention that, at the metropolitan scale of our strategy we found that it is more appropriate to work with regions, rather than buildings or blocks. Therefore, the precise geographic location of socio - economic activities are only relevant on a smaller scale, on the projects scale.

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Analysis of São Paulo’s spatial configuration and its implications in defining ploycentricity