In this blog for the Center Environmental and Security Program (ECSP), CIESIN deputy director Marc Levy talks with ECSP director Geoff Dabelko about using the Gridded Population of the World (GPW) data product to aid in combining population and geographic data.
The SEDAC Global Agricultural Cropland and Pasture data sets are presented in Food: An Atlas, which uses maps to explore global food distribution and production. The cropland and pasture data, originally developed by Ramankutty et al (2008), are transformed into cartograms, in which the land area of countries is replaced by extent of crops and pastures, by Benjamin Hennig to better visualize the magnitude of agricultural areas around the world.
In moist regions around the globe, fire activity is believed to be driven by drought frequency, whereas in dry regions, fire is thought to be limited by the amount of fuel available. Researchers recently tested these ideas by comparing global fire activity as detected by the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) sensor with measures of vegetation such as net primary productivity from the Human Appropriation of Net Primary Productivity (HANPP) data collection available from SEDAC and the Normalized Difference Vegetation Index (NDVI) derived from NOAA satellite data. Although fire activity is indeed limited by droughts in moist areas and by fuel in dry regions, human activities—specifically tropical rain forest deforestation and fire suppression policies in the western U.S.—also strongly influence fire activity.
Satellite data offer a particularly valuable perspective on PM2—small particles deriving mostly from burning fossil fuels and biomass, which can harm human health—because ground instruments may be unavailable or offer limited information, as is the case in China. With that in mind, researchers at Columbia University’s Earth Institute and Batelle Memorial Institute have developed maps based on satellite data that depict annual PM2.5 exposure in all of China’s provinces.