This study developed a Geographic Information System (GIS) framework using datasets such as light detection and ranging (lidar) data, soils, and land use/land cover for analyzing distribution and structure of over 10,000 coastal prairie wetlands (CPWs) around Galveston Bay, Texas, USA. Lidar data were used to estimate volumes and catchment areas. The CPWs were small (median 0.37 ha) with 72% of wetlands less than 1 ha in size. However, CPWs and their catchments occupy 40.8% of the land area within the study area. Field data from 12 CPWs were used to assess the accuracy of selected structural features. Error analysis suggests that relative elevation, land use/land cover and NWI datasets were reasonably accurate, while National Agriculture Imagery Program (NAIP) derived vegetation cover and Soil Survey Geographic Database (SSURGO) soils data were less reliable. This approach not only provides a detailed inventory of wetland resources, it also supports cumulative estimates of regional wetland functions that are critical to regional policy makers and wetland scientists. Additionally, correlations of geospatial datasets to field measurements should interest those who use geospatial datasets to estimate wetland condition.