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.
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Private data.
2.
Personal use.
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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