Data Synthesis Systems (Version 1.0) for World Water Resources

Data Holdings and Citations

 

0.0 General Information

0.1         Relief EDC DEM (6min resolution)

http://edcdaac.usgs.gov/gtopo30/gtopo30.html

GTOPO30 is a global digital elevation model (DEM) with a horizontal grid spacing of 30 arc seconds (approximately 1 kilometer). GTOPO30 was derived from several raster and vector sources of topographic information. Detailed information on the characteristics of GTOPO30 including the data distribution format, the data sources, production methods, accuracy, and hints for users, is found at the web site listed above.

 Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

 

1.0    Meeting Basic Needs

1.1        Population (6min resolution)

http://www.watsys.sr.unh.edu/SciencePaper

Vorosmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers. 2000. Global Water Resources: Vulnerability from Climate Change and Population Growth. Science 289: 284-288.

Global population data layers were constructed for the contemporary (1995) state using country-level demographic statistics from the WRI World Resources1996-97 Database (WRI 1997).  The contemporary urban and rural population data sets were developed by spatially distributing the WRI 1995 country level population data among DMSP-OLS nighttime stable-lights imagery (Elvidge 1997a) and ESRI Digital Chart of the World populated places points (ESRI 1993). Country-level urban population was evenly distributed among the DMSP-OLS city lights data set at 1-kilometer grid cell resolution with detectable lights in at least 10 per cent of the cloud free observations (Elvidge 1997b). Where available, the spatial extents of major city locations with known demographic data (Tobler 1995) were superimposed in the DMSP-OLS city lights data set to enhance the accuracy of the urban population distribution. Rural population was spatially distributed equally among the DCW populated places points falling outside of the DMSP-OLS city lights extent.  Total contemporary population is simply the sum of urban and rural population data sets gridded to the STN 6-minute river network.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

1.2        Runoff/Discharge Annual UNH/GRDC (6min resolution)

http://www.grdc.sr.unh.edu/index.html

http://www.grdc.sr.unh.edu/html/Data/index.html

Fekete, B.M., C.J. Vorosmarty, and W. Grabs. 1999. Global Composite Runoff Fields Based on Observed River Discharge and Simulated Water Balances.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

1.3        Access to SafeDrinking Water (country statistics)

http://www.wri.org/wri/index.html

http://earthtrends.wri.org/

WRI, World Resources: A Guide to the Global Environment 1998-99. World Resources Institute, 1998.

1.4         Access to Adequate Sanitation, People Served by Sewers, Sewerage Treatment (country statistics)

http://www.wri.org/wri/index.html

http://earthtrends.wri.org/

WRI, World Resources: A Guide to the Global Environment 1998-99. World Resources Institute, 1998.

1.5         Infant Mortality (country statistics)

http://www.wri.org/wri/index.html

http://earthtrends.wri.org/

WRI, World Resources: A Guide to the Global Environment 1998-99. World Resources Institute, 1998.

 

2.0   Securing the Food Supply

2.1         Precipitation (6min resolution)

http://climate.geog.udel.edu/~climate/html_pages/archive.html

http://climate.geog.udel.edu/~climate/html_pages/README.ghcn_ts.html

Willmott, C.J. and K. Matsuura. 2000. Terrestrial Air Temperature and Precipitation: Monthly and Annual Time Series (1950 - 1996) v.1.01.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

2.2         Evapotranspiration (6min resolution)

http://www.watsys.sr.unh.edu/WBMTop.html

Federer, C.A., C. J. Vorosmarty, and B. Fekete. 1996. Intercomparison of methods for potential evapotranspiration in regional or global water balance models. Water Resources Research, 32:2315-21.

Vorosmarty, C.J. and B. Moore III. 1991. Modeling basin-scale hydrology in support of physical climate and global biogeochemical studies: An example using the Zambezi River. Studies in Geophysics, 12:271-311.

Vorosmarty, C.J., B. Moore, M.P. Gildea, B. Peterson, J. Melillo, D. Kicklighter, J. Raich, E. Rastetter, and P. Steudler. 1989. A continental-scale model of water balance and fluvial transport: Application to South America. Global Biogeochemical Cycles, 3: 241-65.

Both vertical and horizontal fluxes associated with the terrestrial water cycle are routinely simulated. The local water cycle is determined from climate and other biophysical drivers on discrete 0.5 x 0.5 degree (latitude x longitude) grid cells using the Water Balance Model (WBM). The WBM computes vertical components of the terrestrial water fluxes including change in soil moisture, evapotranspiration, and runoff. Full descriptions of the algorithms and required biophysical data sets are given in (Vörösmarty et al. 1989; Vörösmarty and Moore 1991; Federer et al. 1996).

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

2.3         Climatic Moisture Index (6min resolution)

Vorosmarty, C.J. and P.A. Green. 2001. Indicators of Emerging Water Scarcity: A Biogeophysical Approach Applied to Africa.  Report to the World Resources Institute.

Willmott, C.J., and J.J. Feddema. 1992.  A more rational climatic moisture index. Prof. Geographer 44: 84-87.

The method of Willmott and Feddema (1992) was applied relating potential evaporation to precipitation to generate a mapping of relative water scarcity from a climatic perspective at the 6-minute grid cell resolution. Most of Africa's continental area, 82%, shows negative indices, where drying potential exceeds wetting. The global total is 54%, reflecting much drier conditions across Africa. The mean moisture index for Africa is -0.52 while for the rest of the world it is -0.14.

2.4         Cropland (6min resolution)

http://edcdaac.usgs.gov/glcc/glcc.html

EROS Data Center (EDC) Distributed Active Archive Center (DAAC) Global Land Cover Characteristics Database Version 2.0 Based on 1 km AVHRR data (April 1992-March 1993).

The first version (Version 1.2) of the Global Land Cover Characteristics database was released to the public in November, 1997. Version 1.2 was produced as an International Geosphere Biosphere Programme-Data and Information System (IGBP-DIS) initiative lead by the Land Cover Working Group and has been subjected to a formal accuracy assessment (the IGBP DISCover classification).  Since this version was released, over 200 gigabytes of land cover data have been distributed from the EROS Data Center's anonymous ftp site. Many of the users of the land cover data set have provided feedback (that is, suggestions for additions and improvements).  A revised version of the database (Version 2.0) is now offered through the EDC web site.

Cropland extent was derived from the IGBP Land Cover Legend using the “Croplands” and “Cropland/Natural Vegetation Mosaic” classes. Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

2.5         Irrigation Use (6min resolution)

Vorosmarty, C.J. and P.A. Green. 2001. Indicators of Emerging Water Scarcity: A Biogeophysical Approach Applied to Africa. Report to the World Resources Institute.

The agricultural water demand layer was developed using water statistics for Africa provided by the FAO (Jippe Hoogeveen contact person, FAO/AGL, Rome Italy) at the subbasin level.  Irrigation water use within each subbasin as defined by FAO was evenly distributed across a 1-km resolution grid of cropland (Olsen, 1994) within each subbasin and resampled and registered to the 6-minute river network. We consider irrigated agriculture because it is a major component of water resource infrastructure that is subject to changes in the availability of net runoff. Rain-fed agriculture falls outside this definition.  Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

2.6         Fertilizer (6min resolution)

Green, P.A., Vorosmarty, C.J., and J.N. Galloway. 2002.  Loading of Reactive Nitrogen to the Land Mass of the Earth: A GIS-Based Spread Sheet Approach. In progress.

Country-level nitrogenous fertilizer consumption totals for 1995 were taken from the FAOSTAT Statistical Databases (http://apps.fao.org). These country-level values were evenly distributed among a 1 km resolution cropland dataset derived from the 1996 EDC global landcover dataset using the Olsen Global Ecosystems classification (http://edcdaac.usgs.gov/glcc/glcc.html). Each 1km cropland pixel within a country received an equal fraction of the total fertilizer consumption for that country (fertilizer in each pixel = Total country fertilizer/Number of pixels in country). The fertilizer consumption dataset set was then resampled to 6-minute resolution.

 

3.0   Protecting Ecosystems

3.1         Land Cover (6min resolution)

http://edcdaac.usgs.gov/glcc/glcc.html

EROS Data Center (EDC) Distributed Active Archive Center (DAAC) Global Land Cover Characteristics Database Version 2.0 Based on 1 km AVHRR data (April 1992-March 1993).

The first version (Version 1.2) of the Global Land Cover Characteristics database was released to the public in November, 1997. Version 1.2 was produced as an International Geosphere Biosphere Programme-Data and Information System (IGBP-DIS) initiative lead by the Land Cover Working Group and has been subjected to a formal accuracy assessment (the IGBP DISCover classification).  Since this version was released, over 200 gigabytes of land cover data have been distributed from the EROS Data Center's anonymous ftp site. Many of the users of the land cover data set have provided feedback (that is, suggestions for additions and improvements).  A revised version of the database (Version 2.0) is now offered through the EDC web site.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

3.2         Precipitation (6min resolution)

http://climate.geog.udel.edu/~climate/html_pages/archive.html

http://climate.geog.udel.edu/~climate/html_pages/README.ghcn_ts.html

Willmott, C.J. and K. Matsuura. 2000. Terrestrial Air Temperature and Precipitation: Monthly and Annual Time Series (1950 - 1996) v.1.01.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

3.3         Evapotranspiration (6min resolution)

http://www.watsys.sr.unh.edu/WBMTop.html

Federer, C.A., C. J. Vorosmarty, and B. Fekete. 1996. Intercomparison of methods for potential evapotranspiration in regional or global water balance models. Water Resources Research, 32:2315-21.

Vorosmarty, C.J. and B. Moore III. 1991. Modeling basin-scale hydrology in support of physical climate and global biogeochemical studies: An example using the Zambezi River. Studies in Geophysics, 12:271-311.

Vorosmarty, C.J., B. Moore, M.P. Gildea, B. Peterson, J. Melillo, D. Kicklighter, J. Raich, E. Rastetter, and P. Steudler. 1989. A continental-scale model of water balance and fluvial transport: Application to South America. Global Biogeochemical Cycles, 3: 241-65.

Both vertical and horizontal fluxes associated with the terrestrial water cycle are routinely simulated. The local water cycle is determined from climate and other biophysical drivers on discrete 0.5 x 0.5 degree (latitude x longitude) grid cells using the Water Balance Model (WBM). The WBM computes vertical components of the terrestrial water fluxes including change in soil moisture, evapotranspiration, and runoff. Full descriptions of the algorithms and required biophysical data sets are given in (Vorosmartyet al. 1989; Vorosmartyand Moore 1991; Federer et al. 1996).

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

3.4         Runoff (6min resolution)

http://www.grdc.sr.unh.edu/index.html

http://www.grdc.sr.unh.edu/html/Data/index.html

Fekete, B.M., C.J. Vorosmarty, and W. Grabs. 1999. Global Composite Runoff Fields Based on Observed River Discharge and Simulated Water Balances.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

3.5         Fertilizer (6min resolution)

Green, P.A., Vorosmarty, C.J., and J.N. Galloway. 2002.  Loading of Reactive Nitrogen to the Land Mass of the Earth: A GIS-Based Spread Sheet Approach. In progress.

Country-level nitrogenous fertilizer consumption totals for 1995 were taken from the FAOSTAT Statistical Databases (http://apps.fao.org). These country-level values were evenly distributed among a 1 km resolution cropland dataset derived from the 1996 EDC global landcover dataset using the Olsen Global Ecosystems classification (http://edcdaac.usgs.gov/glcc/glcc.html). Each 1km cropland pixel within a country received an equal fraction of the total fertilizer consumption for that country (fertilizer in each pixel = Total country fertilizer/Number of pixels in country). The fertilizer consumption dataset set was then resampled to 6-minute resolution.

3.6         Nitrogen Loads (6min resolution)

Green, P.A., Vorosmarty, C.J., and J.N. Galloway. 2002. Loading of Reactive Nitrogen to the Land Mass of the Earth: A GIS-Based Spread Sheet Approach. In progress.

Global, continental, regional, and coastline-specific estimates of nitrogen loadings onto the continental land mass are derived by applying a mass balance assessment of nitrogen loads to the landscape providing an accounting of nitrogen sources, uptake, transport and leakages to the terrestrial and riverine systems. Nitrogen loads to the land mass include sewered and non-sewered human wastes, atmospheric deposition, fixation from natural vegetation and cropland, industrial fertilizers, and livestock emissions. We consider atmospheric N deposition, industrial fertilization, and N fixation and their subsequent redistribution across the continental land mass. This redistribution results from the interception of atmospheric N inputs by (a) the growth, harvesting and transport of crops, (b) the growth, harvesting and transport of feed and forage for livestock, (c) the production and transport of animal products, (d) and the loss of N through sewered and non-sewered human populations. We have assumed for this work that potential exports are equal to atmospheric inputs across natural ecosystems and managed forests.  Losses due to denitrification and sequestration will therefore be articulated in basin-scale semi-empirical model of nitrogen flux.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

 

4.0   Sharing Water Resources

4.1         Political Boundaries

http://www.esri.com/data/catalog/esri/esri_aw.html

Environmental Systems Research Institute, Inc. 1996. ArcWorld Supplement. Redlands, CA.

ArcWorld 1:3M contains features for the land areas of the world, including maps of 1996 country boundaries, roads, railroads, rivers, lakes, and major cities; and index maps such as latitude-longitude grids, a Landsat satellite image scene index, and others. ArcWorld 1:3M also has more than 500 attributes for countries covering demographics, education, economic indicators, food production and nutrition, health, the labor force, and natural resources. Many of the attributes are present for multiple years so you can analyze trends.

4.2         Inflows/Outflows

4.3         Upstream/Downstream Demands

4.4         Demand/Q (6min resolution)

http://www.watsys.sr.unh.edu/SciencePaper

Vorosmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers. 2000. Global Water Resources: Vulnerability from Climate Change and Population Growth. Science 289: 284-288.

Datasets for population and domestic and urban water demand (Vörösmarty et al. (2000, 2001)) were resampled from the original 1-km resolution and registered to the 6-minute river network. The agricultural water demand layer was developed using water statistics for Africa provided by the FAO (Jippe Hoogeveen contact person, FAO/AGL, Rome Italy) at the subbasin level. Irrigation water use within each subbasin as defined by FAO was evenly distributed across a 1-km resolution grid of cropland (Olsen, 1994) within each subbasin and resampled and registered to the 6-minute river network.  We consider irrigated agriculture because it is a major component of water resource infrastructure that is subject to changes in the availability of net runoff. Rain-fed agriculture falls outside this definition.

 

5.0   Managing Risks

5.1         Nitrogen Loads (6min resolution)

Green, P.A., Vorosmarty, C.J., and J.N. Galloway. 2002. Loading of Reactive Nitrogen to the Land Mass of the Earth: A GIS-Based Spread Sheet Approach. In progress.

Global, continental, regional, and coastline-specific estimates of nitrogen loadings onto the continental land mass are derived by applying a mass balance assessment of nitrogen loads to the landscape providing an accounting of nitrogen sources, uptake, transport and leakages to the terrestrial and riverine systems. Nitrogen loads to the land mass include sewered and non-sewered human wastes, atmospheric deposition, fixation from natural vegetation and cropland, industrial fertilizers, and livestock emissions. We consider atmospheric N deposition, industrial fertilization, and N fixation and their subsequent redistribution across the continental land mass. This redistribution results from the interception of atmospheric N inputs by (a) the growth, harvesting and transport of crops, (b) the growth, harvesting and transport of feed and forage for livestock, (c) the production and transport of animal products, (d) and the loss of N through sewered and non-sewered human populations. We have assumed for this work that potential exports are equal to atmospheric inputs across natural ecosystems and managed forests.  Losses due to denitrification and sequestration will therefore be articulated in basin-scale semi-empirical model of nitrogen flux.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

5.2         Drought (6min resolution)

Vorosmarty, C.J. and P.A. Green. 2001. Indicators of Emerging Water Scarcity: A Biogeophysical Approach Applied to Africa.  Report to the World Resources Institute.

Water scarcity values per 6-minute grid cell were calculated as the water demand (domestic, industrial, and agricultural) within the grid cell divided by the 30-year low flow recurrence of discharge for the grid cell. The distribution of population living above or below the water scarcity threshold of 0.4 for the 30-year low flow recurrence interval is shown.  Large populations are showing severe water stress under the 30-year low flow conditions. The difference between mean conditions (2-year recurrence) and the 30-year low-flows is noticeable, for example, in Nigeria and its large cities. The total population living above the 0.4 threshold under mean conditions is 185 million, while under low-flow it rises to 291 million. The corresponding totals for 10-year and 20-year recurrence are 255 and 275 million, respectively. These statistics constitute an indicator of temporal vulnerability to relative water scarcity and show a population that is as high risk.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

 

6.0   Valuing Water

6.1         Domestic Water Demand (6min resolution)

http://www.watsys.sr.unh.edu/SciencePaper

Vorosmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers. 2000. Global Water Resources: Vulnerability from Climate Change and Population Growth. Science 289: 284-288.

National and sectoral water use statistics were from World Resources: A Guide to the Global Environment 1998-99 (World Resources Institute, Washington, DC, 1998). The mean reporting year was 1995, but the range was from 1970 to 1995. National statistics were normalized to year 1995 by applying usage trends recorded in corresponding regional time series (Shiklomanov 1996). Domestic water demand was computed on a per capita basis for each country and distributed geographically with respect to the 1-km total population field. Datasets for domestic water demand (Vörösmarty et al. (2000, 2001)) were resampled from the original 1-km resolution and registered to the 6-minute river network.

6.2         Industrial Water Demand (6min resolution)

http://www.watsys.sr.unh.edu/SciencePaper

Vorosmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers. 2000. Global Water Resources: Vulnerability from Climate Change and Population Growth. Science 289: 284-288.

National and sectoral water use statistics were from World Resources: A Guide to the Global Environment 1998-99 (World Resources Institute, Washington, DC, 1998). The mean reporting year was 1995, but the range was from 1970 to 1995. National statistics were normalized to year 1995 by applying usage trends recorded in corresponding regional time series (Shiklomanov 1996). Datasets for industrial water demand (Vörösmarty et al. (2000, 2001)) were resampled from the original 1-km resolution and registered to the 6-minute river network.

6.3         Agricultural Water Demand (6min resolution)

Vorosmarty, C.J. and P.A. Green. 2001. Indicators of Emerging Water Scarcity: A Biogeophysical Approach Applied to Africa. Report to the World Resources Institute.

The agricultural water demand layer was developed using water statistics for Africa provided by the FAO (Jippe Hoogeveen contact person, FAO/AGL, Rome Italy) at the subbasin level.  Irrigation water use within each subbasin as defined by FAO was evenly distributed across a 1-km resolution grid of cropland (Olsen, 1994) within each subbasin and resampled and registered to the 6-minute river network. We consider irrigated agriculture because it is a major component of water resource infrastructure that is subject to changes in the availability of net runoff. Rain-fed agriculture falls outside this definition.  Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

 

7.0   Governing Water Wisely

7.1         Runoff (6min resolution)

http://www.grdc.sr.unh.edu/index.html

http://www.grdc.sr.unh.edu/html/Data/index.html

Fekete, B.M., C.J. Vorosmarty, and W. Grabs. 1999. Global Composite Runoff Fields Based on Observed River Discharge and Simulated Water Balances.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

7.2         Discharge (6min resolution)

http://www.grdc.sr.unh.edu/index.html

http://www.grdc.sr.unh.edu/html/Data/index.html

Fekete, B.M., C.J. Vorosmarty, and W. Grabs. 1999. Global Composite Runoff Fields Based on Observed River Discharge and Simulated Water Balances.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

 

8.0   Water for Industry

8.1         Discharge (6min resolution)

http://www.grdc.sr.unh.edu/index.html

http://www.grdc.sr.unh.edu/html/Data/index.html

Fekete, B.M., C.J. Vorosmarty, and W. Grabs. 1999. Global Composite Runoff Fields Based on Observed River Discharge and Simulated Water Balances.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

8.2         Industrial Water Demand (6min resolution)

Vorosmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers. 2000. Global Water Resources: Vulnerability from Climate Change and Population Growth. Science 289: 284-288.

National and sectoral water use statistics were from World Resources: A Guide to the Global Environment 1998-99 (World Resources Institute, Washington, DC, 1998). The mean reporting year was 1995, but the range was from 1970 to 1995. National statistics were normalized to year 1995 by applying usage trends recorded in corresponding regional time series (Shiklomanov 1996). Domestic water demand was computed on a per capita basis for each country and distributed geographically with respect to the 1-km total population field. Datasets for industrial water demand (Vörösmarty et al. (2000, 2001)) were resampled from the original 1-km resolution and registered to the 6-minute river network.

 

9.0   Water for Energy

9.1         Discharge (6min resolution)

http://www.grdc.sr.unh.edu/index.html

http://www.grdc.sr.unh.edu/html/Data/index.html

Fekete, B.M., C.J. Vorosmarty, and W. Grabs. 1999. Global Composite Runoff Fields Based on Observed River Discharge and Simulated Water Balances.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS. 

9.2         Energy by Country (country statistics)

http://www.wri.org/wri/index.html

http://earthtrends.wri.org/

WRI, World Resources: A Guide to the Global Environment 1998-99. World Resources Institute, 1998.

10.0        Ensuring Knowledge Base

10.1    GRDC Station Data

10.2    Education Expenditures (country statistics)

http://www.wri.org/wri/index.html

http://earthtrends.wri.org/

WRI, World Resources: A Guide to the Global Environment 1998-99. World Resources Institute, 1998.

10.3    Literacy (country statistics)

http://www.wri.org/wri/index.html

http://earthtrends.wri.org

WRI, World Resources: A Guide to the Global Environment 1998-99. World Resources Institute, 1998.

 

11.0        Water and Cities

11.1    Sanitation/Sewerage (country statistics)

http://www.wri.org/wri/index.html

http://earthtrends.wri.org

WRI, World Resources: A Guide to the Global Environment 1998-99. World Resources Institute, 1998.

11.2    Urban Population (6min resolution)

http://www.watsys.sr.unh.edu/SciencePaper

Vorosmarty, C.J., P. Green, J. Salisbury, and R.B. Lammers. 2000. Global Water Resources: Vulnerability from Climate Change and Population Growth. Science 289: 284-288.

Global population data layers were constructed for the contemporary (1995) state using country-level demographic statistics from the WRI World Resources1996-97 Database (WRI 1997).  The contemporary urban and rural population data sets were developed by spatially distributing the WRI 1995 country level population data among DMSP-OLS nighttime stable-lights imagery (Elvidge 1997a) and ESRI Digital Chart of the World populated places points (ESRI 1993). Country-level urban population was evenly distributed among the DMSP-OLS city lights data set at 1-kilometer grid cell resolution with detectable lights in at least 10 per cent of the cloud free observations (Elvidge 1997b). Where available, the spatial extents of major city locations with known demographic data (Tobler 1995) were superimposed in the DMSP-OLS city lights data set to enhance the accuracy of the urban population distribution.

Data has been resampled to the 6-minute grid cell resolution using standard GIS algorithms for inclusion in the DSS.

11.3    Water Availability


© Copyright: United Nations Educational, Scientific and Cultural Organization. All rights reserved
Contact e-mail at UNESCO/IHP and UNH