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Applications of satellite remote sensing data for estimating biogenic emissions in southeastern Texas
Authors:MS Feldman  T Howard  E McDonald-Buller  G Mullins  DT Allen  A Hansel  A Wisthaler
Institution:1. Laboratory of Forest Remote Sensing, Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, GR 68200, Orestiada, Greece;2. Laboratory of Forest Management and Remote Sensing, Department of Forestry and Natural Environment, Aristotle University of Thessaloniki, GR-54124, Thessaloniki, Greece;3. Department of Cadastre, Photogrammetry and Cartography, Faculty of Rural and Surveying Engineering, Aristotle University of Thessaloniki, GR-54124, Thessaloniki, Greece
Abstract:The sensitivity of biogenic emission estimates and air quality model predictions to the characterization of land use/land cover (LULC) in southeastern Texas was examined using the Global Biosphere Emissions and Interactions System (GloBEIS) and the Comprehensive Air Quality Model with extensions (CAMx). A LULC database was recently developed for the region based on source imagery collected by the Landsat 7 Enhanced Thematic Mapper-Plus sensor between 1999 and 2003, and field data for land cover classification, species identification and quantification of biomass densities.  Biogenic emissions estimated from the new LULC data set showed good general agreement in their spatial distribution, but were approximately 40% lower than emissions from the LULC data set currently used by the State of Texas, primarily because of differences in the biomass estimates of key species such as Quercus. Predicted ozone mixing ratios using the biogenic emissions produced from the new LULC data set were as much as 26 ppb lower in some areas on some days, depending on meteorological conditions. Satellite data and image classification techniques provide useful tools for mapping and monitoring changes in LULC. However, field validation is necessary to link species and biomass densities to the classification system used for accurate biogenic emissions estimates, especially in areas such as riparian corridors that contain dense spatial coverage of key species.
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