Linking Remote Sensing Estimates of Land-Cover to Census Statistics on Land-Use for the Coterminous United States


There are two primary sources of information for studies of large-scale land-cover and land-use, space-borne remote sensing and ground-based census statistics, each with advantages and disadvantages. Regional remote sensing products typically provide high spatial resolution ($\sim$1 km$^{2}$) maps of {\it land-cover} (e.g., deciduous {\it vs.} evergreen forest). Census statistics provide more information on {\it land-use} (e.g., grazed {\it vs.} non-grazed forested land), but at lower spatial resolution; data are typically aggregated by political units like counties ($\sim$10$^{2}$ -10$^{4}$ km$^{2}$), states ($\sim$10$^{4}$ -10$^{5}$ km$^{2}$), or nations ($\sim$10$^{4}$ -10$^{7}$ km$^{2}$). Neither of these sources of information alone is sufficient for applications, such as terrestrial ecosystem modeling, that require spatially-explicit information on land-use. However, a synthesis of these two data sources may provide the necessary information. Here we develop a correlation between (1) the IGBP DISCover 1-km remote sensing land-cover map of the coterminous U.S. and (2) state-level statistics from the USDA Major Land Uses dataset. We evaluate the consistency between these two views of the U.S. landscape. We also generate a hybrid land-use product: an 0.5$\deg$x0.5$\deg$ land-use map for the coterminous U.S.


Earth Sciences, Earth Systems Research Center

Publication Date


Journal Title

EOS, Transactions American Geophysical Union, Fall Meeting, Supplement


American Geophysical Union Publications

Document Type

Conference Proceeding