Where Are the Data?

Where Are the Data?Sources and Challenges in the Population–Climate Change

Relationship

Mark R. Montgomery

Stony Brook University and Population Council

August 22, 2013

Where Are the Data?

Environmental Threats

Sudden-onset extreme weather events: Flooding, fromhurricanes and typhoons as well as heavy inland precipitation

Women, children, and elderly disproportionately harmed

Gradual-onset conditions: In arid regions, increasing waterscarcity with implications for rural and urban dwellers(especially the poor) and for rural-urban migration.

Where Are the Data?

Social Science Research on Adaptation in Low-IncomeCountriesWhere’s Our Comparative Advantage?

Estimating numbers and characteristics of the poor and vulnerableexposed to sudden-onset and gradual-onset environmental risks.

Developing new methods for recording localized, smaller-scaledisasters

Forecasting population growth in risky areas

Engagement at the country level increasingly important asinternational funds for disaster risk adaptation become available

Community-level interventions: Disaster risk reduction. Sensitive toneeds of women, adolescents, the elderly, and the poor. Create linksto local government

Provision of quantitative data to humanitarian and developmentagencies.

Where Are the Data?

Consider Residents of Cities and Towns

Poor countries are approaching urban majorities

Some extreme-weather events (e.g., flooding) repeatedlystrike city-dwellers, harming lives and livelihoods

Apart from national censuses, demographers collect little orno city-specific data

Majority of urban residents live in small- and intermediate-sizecities. Mayors and planners operate with little information ontheir populations; limited abilities to anticipate risks and guidelocal development

Where Are the Data?

Spatially-Specific Data Are EssentialWeather and climate risks differ by location within a country

Where Do We Find Such Spatially Detailed Information?

National censuses collect fine spatial detail—but in poorcountries are rarely mapped and disaggregated

Sample surveys are samples, too small to reliably portrayspecific locations

But censuses, survey programs, and a host of researchinitiatives are generating streams of spatially-codeddata—much of this from outside demography proper

There is vastly more spatial data available today than fiveyears ago!

Where Are the Data?

Who is at Risk? Mapping Demographic Data

1 Sub-national census and survey (DHS, MICS) data on populationnumbers and composition

2 High resolution population density rasters, from Andy Tatem’s team

3 DHS sampling cluster coordinates fairly precise spatially

4 Measures of city population size (UN Population Division;www.geonames.org; others)

5 Measures of city spatial extents (night-time lights, Viirs,LandSat, even higher-resolution)

Where Are the Data?

Sub-National BoundariesDHS site providing shapefiles to debut in early September 2013

Where Are the Data?

Ghana’s Population Density and Proxies for It2010 raster (AfriPop) and 2009 NOAA lights

0

100

200

300

400

500

600

Where Are the Data?

Inland Flooding Risks in GhanaEstimates from the Dartmouth Flood Observatory Models

Where Are the Data?

Current and Future Urban ExposureUN Cities Database: Time-series of Population by City

Where Are the Data?

Small and Large Cities from www.geonames.orgMany More Small Cities (but only one time-point apiece)

Where Are the Data?

DHS Urban Clusters, Surveys from 1993 to 2008

Where Are the Data?

Estimates of City Exposure to Flooding RisksBalk et al. (2013) for Asia, IUSSP Session Tomorrow

City population at riskCoastal Hazards (LECZ) Inland Flooding

Estimates (000s) for year 2000

- 2,000 4,000 6,000

Dhaka

Wuhan

Bangkok

Shanghai

Tokyo

Quezon City-Manila

Ho Chi Minh City

Tianjin

Delhi

Kolkata

Nanjing

Shenzhen

Pusan

Hangzhou

Changsha

Palembang

Patna

Phnum Penh

Zhenjiang

Ha Noi

Where Are the Data?

Conclusions

Demographers and other social scientists have much tocontribute on climate change adaptation and disaster riskreduction

We’ve not yet engaged with these issues, hampered by the(perceived) lack of spatially-coded demographic data

The situation is rapidly improving—essential descriptions ofexposure to risk are now possible

But nothing substitutes for spatially disaggregated censusdata. Fine disaggregation and mapping of census data shouldbe the norm for national statistical agencies.

How can we make that happen?