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Full-Text Articles in Physical Sciences and Mathematics
Projected Surface Raidiative Forcing Due To 2000-2050 Land-Cover Land-Use Albedo Change Over The Eastern United States, Christoper A. Barnes, David P. Roy, Thomas R. Loveland
Projected Surface Raidiative Forcing Due To 2000-2050 Land-Cover Land-Use Albedo Change Over The Eastern United States, Christoper A. Barnes, David P. Roy, Thomas R. Loveland
GSCE Faculty Publications
Satellite-derived contemporary land-cover land-use (LCLU) and albedo data and modeled future LCLU are used to study the impact of LCLU change from 2000 to 2050 on surface albedo and radiative forcing for 19 ecoregions in the eastern United States. The modeled 2000–2050 LCLU changes indicate a future decrease in both agriculture and forested land and an increase in developed land that induces ecoregion radiative forcings ranging from −0.175 to 0.432 W m−2 driven predominately by differences in the area and type of LCLU change. At the regional scale, these projected LCLU changes induce a net negative albedo decrease (−0.001) and …
Sensitivity Analysis Of The Gems Soil Organic Carbon Model To Land Cover Land Use Classification Uncertainties Under Different Climate Scenarios In Senegal, Amadou M. Dieye, David P. Roy, N. P. Hanan, S. Lui, M. Hansen, A. Toure
Sensitivity Analysis Of The Gems Soil Organic Carbon Model To Land Cover Land Use Classification Uncertainties Under Different Climate Scenarios In Senegal, Amadou M. Dieye, David P. Roy, N. P. Hanan, S. Lui, M. Hansen, A. Toure
GSCE Faculty Publications
Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat …