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This study investigated the use of a geographic object-based image analysis (GEOBIA) approach with the incorporation of object-specific grey-level co-occurrence matrix (GLCM) texture measures from a multispectral Ikonos image for delineation of deciduous, evergreen, and mixed forest types in Guilford Courthouse National Military Park, North Carolina. A(More)
Dr. Madden announced that the Chattanooga ASPRS Mid-South Regional Meeting will take place in Chattanooga, TN over Fall Break. The final schedule will be released soon. Contact her for additional information. Sergio reminded the Chapter members that the ASPRS Awards Applications are due early this year. Submit your complete application no later than October(More)
The Sunda Banda Seascape (SBS), located in the center of the Coral Triangle, is a global center of marine biodiversity and a conservation priority. We proposed the first biophysical environmental delineation of the SBS using globally available satellite remote sensing and model-assimilated data to categorize this area into unique and meaningful biophysical(More)
Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species' distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate(More)
The distribution of West Nile virus (WNV) is dependent on the occurrence of both susceptible avian reservoir hosts and competent mosquito vectors. Both factors can be influenced by geographic variables such as land use/landcover, elevation, human population density, physiographic region, and temperature. The current study uses geographic information systems(More)
Using forest inventory data and Landsat ETM+ data, linear fixed-effects models and linear mixed-effects models are developed based on the allometric growth model. The surface area of the normalized difference vegetation index (NDVIsa) is developed from the triangulated irregular network (TIN) with the aid of image-processing and the three-dimensional(More)
The automated interpretation of remotely sensed data is still performed largely on the basis of per-pixel image classification, i.e., the statistical analysis of each pixel's spectral value. The conventional per-pixel classification approaches, however, may have limitations to be considered when used with very high resolution imagery because these(More)