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Social and Behavioral Sciences Commons™
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Articles 1 - 4 of 4
Full-Text Articles in Social and Behavioral Sciences
Near-Real-Time Global Biomass Burning Emissions Product From Geostationary Satellite Constellation, Xiaoyang Zhang, Shobha Kondragunta, Jessica Ram, Christopher Schmidt, Ho-Chung Huang
Near-Real-Time Global Biomass Burning Emissions Product From Geostationary Satellite Constellation, Xiaoyang Zhang, Shobha Kondragunta, Jessica Ram, Christopher Schmidt, Ho-Chung Huang
GSCE Faculty Publications
Near-real-time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near-real-time global biomass burning emission product from geostationary satellites (GBBEP-Geo) produced from satellite-derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second-generation satellites (Meteosat-09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport …
Prototype For Monitoring And Forecasting Fall Foliage Coloration In Real Time From Satellite Data, Xiaoyang Zhang, Mitchell D. Goldberg, Yunyue Yu
Prototype For Monitoring And Forecasting Fall Foliage Coloration In Real Time From Satellite Data, Xiaoyang Zhang, Mitchell D. Goldberg, Yunyue Yu
GSCE Faculty Publications
While determining vegetation phenology from the time series of historical satellite data has been widely investigated throughout the last decade, little effort has been devoted to real-time monitoring and short-term forecasting. The latter is more important for numerical weather modeling, ecosystem forecasting, forest and crop management, and health risk warning. In this study we developed a prototype approach for the real-time monitoring and short-term forecasting of fall foliage status (including low coloration, moderate coloration, near-peak coloration, peak coloration, and post-peak coloration) using temporal satellite observations. The algorithm combined the climatology of vegetation phenology and temporally available satellite observations to establish …
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 …