Therefore, SES research requires a detailed understanding of where people live in relation to environmental factors. Socio-environmental systems (SES) are highly complex and key to the assessment of their dynamics, including the provisioning of ecosystem services and risks posed by environmental hazards and public health outcomes, is linking people to the environment with which they interact 3. There is growing awareness that solutions to pressing challenges in environmental science require characterizing interactions and feedbacks between social and natural systems 1, 2. The dataset, known as the U.G.L.I (updatable gridded lightweight impervious) population dataset, compares favorably against other population data sources, and provides a useful balance between resolution and complexity. The methodology is updatable using the most recent Census data and remote sensing-based observations of impervious surface area. The workflow dasymetrically distributes Census block level population estimates across all non-transportation impervious surfaces within each Census block. With this data release, we provide a 30-m resolution population estimate for the contiguous United States. However, timely acquisition of such data at sufficient spatial resolution can be problematic, especially in cases where the analysis area spans urban-rural gradients. In the United States, Census data is the most common source for information on population. Assessment of socio-environmental problems and the search for solutions often require intersecting geospatial data on environmental factors and human population densities.
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