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Depletion of wetlands along the coastlines of United States (US) is a bigger environmental hazard. Urban sprawl along the coastlines is the major cause of this depletion, which is causing greater risk of landfall of hurricanes. In recent times, these hurricanes, which have landfalls hundreds of miles inland, destroy a lot of lives and other properties. The objective of this study was to study the change in wetlands in the 23 US Southeastern (SE) Coastal Counties of US over the years using remote sensing data and advanced image processing and geospatial algorithms. Another subobjective of this study was to determine the impact of Tsunami like high tides on these coastal counties due to global climate change and landscape mismanagement. Landsat imageries of 1989 and 2009 were collected for these 23 US SE Coastal Counties of South Carolina, Georgia, and Florida states. The imageries were mosaiced together to a single image for each year. Principal component analysis was conducted to obtain the best informative component band image comprised of all 7 bands. ERDAS Imagines ISODATA unsupervised classification algorithm was used to classify both years principal component band images with 50 classes each. WARD minimum variance technique was used to obtain the dendrogram that helped in merging classes having less variance in mean spectral reflectance values. Seven classes were obtained after merging the 50 classes of both images. These classes were flood plain, forest, high density urban, low density urban, wetlands, open water, and clouds. ArcGIS 9.3 software was used to perform the land-use change analysis over the 25 years from 1984 to 2009. An automated geospatial model was developed in ArcGIS Model Builder for this land-use change analysis. Thus, we were able to determine change of wetlands from1984 to 2009. The wetland classes were verified for accuracy using the NLCD land cover classified map of 1992 and GLUT 2005 data. Also, Photo Science Inc. classified 2008 Landsat imagery for Georgia was used to obtain the classification authenticity. The Change detection resulted in a total wetlands change of 1.9 million hectare out of a 4.7 million study area. Another study was conducted on the Georgia coastal counties to determine the area that will be inundated if high tides of 3 m, 5 m, and 10 m come to the Atlantic shores due to hurricanes as a result of the depleted coastline wetlands and the global climate change. The Digital Elevation Model (DEM) spatial data from National Elevation Dataset (NED) program was used in this analysis. It was found that 11.7%, 14.7%, and 32.52% of Georgia coastal counties will be under water with a 3, 5, and 10 meter high tides, respectively. Without precautionary measures, Little St. Simons, St. Marys and Dungeness cities in coastal Georgia would be completely flooded by a 3 meter wave. Finally, a study is in progress to process and obtain accurate and latest DEM from the LIDAR data procured in 2009 for these Georgia coastal counties. The new DEM would be used to obtain more accurate flooding information of these coastal counties which may happen due to wetland depletion in coastal areas and recent phenomena of global warming and climate change.