Journal
ENVIRONMENTAL RESEARCH LETTERS
Volume 4, Issue 4, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1748-9326/4/4/044003
Keywords
urban systems; cities; urbanization; land cover; ecoregions; global monitoring; remote sensing; decision trees; machine learning; data sets
Funding
- NASA [NNX08AE61A]
- NASA [NNX08AE61A, 102885] Funding Source: Federal RePORTER
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Although only a small percentage of global land cover, urban areas significantly alter climate, biogeochemistry, and hydrology at local, regional, and global scales. To understand the impact of urban areas on these processes, high quality, regularly updated information on the urban environment-including maps that monitor location and extent-is essential. Here we present results from efforts to map the global distribution of urban land use at 500 m spatial resolution using remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our approach uses a supervised decision tree classification algorithm that we process using region-specific parameters. An accuracy assessment based on sites from a stratified random sample of 140 cities shows that the new map has an overall accuracy of 93% (k = 0.65) at the pixel level and a high level of agreement at the city scale (R-2 = 0.90). Our results (available at http://sage.wisc.edu/urbanenvironment.html) also reveal that the land footprint of cities occupies less than 0.5% of the Earth's total land area.
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