Crowdsource presentation MaCT - Social Data

MASTER IN CITY & TECHNOLOGY DIGITAL TOOLS AND BIG DATA - 3nd Term 2019/2020 FACULTY DIEGO PAJARITO

Digital tools and big data

Group 1

Digital tools and big data

Landfill Advantages1.Location data of various urban services 2.Quick GeoJson export to use with GIS software.

Waste disposal

Recycle type centre

Limitations1.Issues regarding downloading customized map 2.Challenges with specfic tags-

Waste transfer station References: http://overpass-turbo.eu/s/U2A

How feasible is this data set

power=generator with generator:source =wast e: Power generator from waste inside an incineration plant.

How this quick analysis relate to Urban Design?

The quick analysis can help to understand existing infrastructure in the city such as waste management system.

From the waste collection to upcycle process, this data is a hint to see the potential of each urban area.

For example, the industrial area should be around the upcycle factory. We can design and decision-making more efficient.

Available tags ●

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Waste basket Social data and urban design

amenity=waste_disposal - A medium size disposal bin, typically for bagged up household or industrial waste. May be in the street, but not primarily for use by passing pedestrians. amenity=recycling + recycling_type=container: A container that accepts waste for recycling. amenity=recycling + recycling_type=centre: A centre/facility that accepts waste for recycling. amenity=waste_transfer_station: A location that accepts, consolidates and transfers waste in bulk, usually from government or commercial collections. landuse=landfill: A site for the disposal of waste materials by burial. bin=*: to indicate that a facility contains a bin.

References: http://overpass-turbo.eu/s/U2A

Group 2

Digital tools and big data

Relevance for Urban Planning

Analysis for the current Situation during the COVID-19 Helps in policy-making

Advantages: Timefactor is given and shows the change during the dierent Phases.

Issues: Missing data for analysis in neigborhoodscale (Map on the left is smallest scale)

Madrid traďŹƒc density mobility

References: https://movement.uber.com/explore/madrid/mobility-heatmap/query?lat.=40.418017 5&lng.=-3.7051779&z.=13.5&lang=en-US

Change of mobility (driving, Transit, walking) Global vs. Spain

How feasible is this data set

Source: https://www.apple.com/covid19/mobility

FEB

Total amount of travels between towns (13-17 April)

References: https://www.eldiario.es/economia/Espana-normalidad-movilidad-Semana-Santa_0_102014 8656.html https://cnecovid.isciii.es/covid19/#declaraci%C3%B3n-agregada

Social data and urban design

APR

Group 3

Digital tools and big data

How this quick analysis relates to Urban Design?

When designing a new urban project, one may need to focus more on the resilience to COVID. For example, building a Senior Home in a less densely populated area or making sure the infrastructure and materials are resistance to viruses (ex. Deterrent materials).

More opportunities to provide tools for the safety of citizens. For example, more places with disinfectant or public fountains to wash hands.

References: link

Social data and urban design

COVID-19 contagion and deaths data uses: ● ● ● ●

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References: http://aquas.gencat.cat/ca/actualitat/ultimes-dades-coronavirus/mapa-per-abs/

How feasible is this data set

Detection of new cluster of contagion Decision making of protocol Social orchestration De-escalation plan and correlation with new cases/deaths Future response to disasters and management (nearby emergency hospitals/shelters Reconversion of public spaces during emergency situations

COVID API

How feasible is this data set

COVID API

https://api.covid19api.com/summary

How feasible is this data set

Group 4

Digital tools and big data

Moving Objects Data Data from moving objects is highly useful when analyzing urban movement. (i.e. traďŹƒc, pedestrian ow)

1.

Free, open data.

1.

Private data.

2.

Personal use.

2.

API allows for integrating into app.

Further analysis.

Digital tools and big data

API 1.

Create Developer Account

2.

Make requests with access tokens

3.

Visualize

How feasible is this data set

Social data and urban design

References: https://www.strava.com/heatmap

Group 5

Digital tools and big data

Cadastral data is the most accurate and granular representation we can get in analyzing Barcelona or any site.

How feasible is this data set

Data structure: not user-friendly

How feasible is this data set

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An important tool in providing a meaningful understanding about the urban fabric

How feasible is this data set

OPEN & PUBLIC SPACES (CADASTRAL)

Social data and urban design

OPEN & PUBLIC SPACES (CADASTRAL) +

WIKILOC Pedestrian Bicycle

References: https://www.wikiloc.com/wikiloc/download.do?id=41152002

Social data and urban design

MASTER IN CITY & TECHNOLOGY DIGITAL TOOLS AND BIG DATA - 3nd Term 2019/2020 FACULTY DIEGO PAJARITO