European Commission Joint Research Centre 1st Urbanization Workshop
Day 2, Session 1:
Tools and Methods for Global Urban Analysis
Ellen Hamilton
Lead Urban Specialist World Bank
Outline
• Global Agendas: SDG indicators
• Perspectives from World Bank as a data user
– Quick history
– What are we doing now?
• What next?
Image source: DGREGIO fine scale analysis of the whole European settlements using 2.5-m-res input image data (GMES/Copernicus CORE003 2012) 2
Credits: European Commission, DG Regional Development /Joint Research Centre
SDGs, Habitat III: The New Urban Agenda
Goal 11 - Make cities and human settlements safe, inclusive, resilient and sustainable.
• 11.1 By 2030, ensure access for all to adequate, safe and affordable housing and basic services and upgrade slums
• 11.2 By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all, 8improving road safety, notably by expanding public transport, with special attention to the needs of those in vulnerable situations, women, children, persons with disabilities and older persons
• 11.3 By 2030, enhance inclusive and sustainable urbanization and capacity for
participatory, integrated and sustainable human settlement planning and management in all countries
• 11.4 Strengthen efforts to protect and safeguard the world’s cultural and natural heritage
• 11.5 By 2030, significantly reduce the number of deaths and the number of people affected and decrease by [x] per cent the economic losses relative to gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situations
• 11.6 By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management
• 11.7 By 2030, provide universal access to safe, inclusive and accessible, green and
World Bank as user: What’s in it for us?
• Helps understand the evolution, drivers and impacts of urban form, and make better decisions about location of infrastructure projects which ‘lock in’ urban form.
• Allows easier, cheaper data collection in typically data-scarce environments.
• Allows comparability of trends in urbanization between cities/
countries.
• Allows better spatial targeting of the poor.
• Crowd-sourcing and open data makes beneficiaries part of data generation and application development, and creates public
dialogue around development issues.
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Past Work on Mapping Urbanization:
Some Examples
Measuring Global Urban Expansion c1990-2000
• 120-city sample
• MODIS 500m satellite
imagery
• Calculated
several metrics to describe the built form
Source: Angel et al (2005), The Dynamics of Global Urban Expansion, World Bank
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Measuring Urban Growth across East Asia c2000-2010
• Measured expansion of built-up area
between 2000 and 2010 across East Asia and the Pacific using MODIS 250m satellite imagery
• Used WorldPop population
distribution mapping
• Overlaid
administrative
boundaries (GADM)
• Competition for data analysis and
visualization
Measuring Urban Growth across South Asia c2000-2010
Night Time Lights (DMSP-OLS) data:
• A cost-effective
option for analyzing broad spatial
patterns of urban expansion and
economic growth in a data scarce
environment
• Intensity of lights is strongly correlated with economic
activity
• Helped to identify dozens of cities merging into urban corridors across borders
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Ongoing Work
• Simplified version of the OECD ‘core and hinterland’ approach
• Uses population size and density thresholds
• Currently being tested on Argentina data
Global Urban Definition (in progress)
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Inputs:
Global Human Settlement Layer (EC-Joint Research Centre)
• Automatic image information retrieval
• Possibility to process consistently global fine-scale information
• Multi-sensor, multi-scale
• Sustainable information production
• Information democratization
• Open, public and reproducible information
• Binary built and non-built layer using fully automated
classification (to extract human settlement data)
• Very high resolution radar missions: TerraSAR-
X/TanDEM-X: About 50-70m resolution output
• Global
Inputs:
Global Urban Footprint (DLR)
Source: High-Resolution Global Monitoring of Urban
Settlements, DLR 2013
Rome, IT
Inputs: WorldPop
• Spatial resolution: 100m
• Year(s): 2000-2020
• Cost: free to download existing layers
• Regularity of update: Ongoing
• Availability/documentation of input data: Yes
• Reproducible methods: Yes (with code)
Example of use: Sri Lanka (in progress)
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• GHSL ‘alpha’ version used to understand broad trends in urban growth as input into a Systematic Country Diagnostic
• WorldPop mapping to begin shortly, using GHSL as an input: allows population
distribution in conflict-affected areas that have no recent
census
Example of use: Argentina (in progress)
• GHSL ‘alpha’ version used to understand broad trends in urban growth, as input into an analysis of demographic
trends and urbanization
• WorldPop mapping using GHSL as an input recently completed
– Provides quantitative evidence of misalignment between official definitions of urban and where population densities really are
African Cities: Measuring Urban Change at the Metropolitan Scale
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Mapping city form and its evolution over time in 10 African cities:
• Nairobi, Dakar, Addis, Kigali, Lagos,
Maputo, Accra, Kinshasa, Dar es Salam, and Durban (TBC)
• VHR imagery; c2000–
2010
• Will combine earth observation with other layers from the city, geo-referenced household surveys, etc.
Kigali
Other examples (in progress)
• Nepal
• India
• Kazakhstan
• Kyrgyz Republic
• ECA Shrinking Cities Project
• Guatemala/Central America
• Argentina
• Sri Lanka
• Africa (huge demand)
PUMA – Platform for Urban Management and Analysis
An online geospatial tool which allows users with no prior GIS experience to
access, analyze and share urban spatial data in an interactive and customizable way.
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Can we commit to next steps?
• Short-term:
• Global Population Grid (1 km, by fall?)
• Consensus on universe of cities (can we agree on a shared definition?)
• Medium-term:
• Time series for population and built up area
• Using GHSL for SDGs
