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Estimating impervious cover and riparian zone condition in New England watersheds.
Citation:
Morgan, J., N. Detenbeck, S. Rego, AND Y. Wang. Estimating impervious cover and riparian zone condition in New England watersheds. Presented at Northeast Arc Users Group, Amherst, MA, May 13, 2014.
Impact/Purpose:
Under EPA’s Green Infrastructure Initiative, a variety of research activities are underway to evaluate the effectiveness of green infrastructure in mitigating the effects of urbanization and stormwater impacts on stream biota and habitat. Effectiveness of both site-scale stormwater best management practices and landscape-scale natural green infrastructure are being assessed. The percentage of impervious cover in a watershed is a known stressor on stream biota and habitat. Preliminary analyses, using impervious cover estimates from the 30-meter resolution National Landcover Dataset (NLCD), have indicated that biotic communities are being impacted at much lower levels of watershed imperviousness than previously reported in the literature. It is likely that the 30-meter resolution NLCD data are underestimating impervious cover, particularly in suburban areas where impervious surfaces can be masked by vegetation and trees. Other analyses have found that the condition of forested buffer zones can help to mitigate the effects of urbanization, even when the natural functions of riparian zones are altered by stormwater drainage infrastructure. The purpose of this research is to improve EPA’s assessments of impervious cover and riparian zone condition by conducting high resolution image analysis using GIS, genetic algorithms, and 1-meter resolution imagery from the National Agricultural Imagery Program (NAIP) program. The products of the research include the optimization of riparian zone condition and impervious cover estimates using NAIP data and ancillary data sets such as road networks, National Wetlands Inventory (NWI) data, the National Hydrography Dataset (NHD), LiDAR, and E911 data. Classification accuracy assessment will compare the improved classifications to previously established impervious area and riparian zone estimates. These improved estimates will be used to evaluate critical riparian zone widths required for mitigation of urbanization effects at varying spatial resolutions, as well as to evaluate macroinvertebrate, fish, and periphyton model and threshold accuracy. The results of the project will help to better inform management strategies and regulation of development for suburban and urban areas.
Description:
Under EPA’s Green Infrastructure Initiative, research activities are underway to evaluate the effectiveness of green infrastructure in mitigating the effects of urbanization and stormwater impacts on stream biota and habitat. Preliminary analyses, using impervious cover estimates from the 30-meter resolution National Landcover Dataset (NLCD), have indicated that biotic communities are impacted at lower levels of watershed imperviousness than those traditionally reported in the literature. However, NLCD data are likely underestimating impervious cover, particularly in suburban areas where impervious surfaces can be masked by tree cover. Concurrent analyses have found that the condition of forested buffer zones can help to mitigate the effects of urbanization, even when the natural functions of riparian zones are altered by stormwater drainage infrastructure. Higher resolution estimates of impervious cover and riparian zone condition may provide a more accurate depiction of stream ecosystem responses to urbanization. However, fine scale classifications are difficult at broad spatial extents. Methodologies were developed to improve classification accuracy using imagery from the National Agricultural Imagery Program (NAIP) program, LIDAR data, GIS, and genetic algorithms. An accuracy assessment was conducted and compared to classifications of previously established estimates from state and local high-resolution data sets. These improved estimates will be used to evaluate riparian zone widths required for mitigation of urbanization effects at varying spatial resolutions, and to evaluate if prior biotic community thresholds change. This presentation focuses on a case study in Burlington, VT and highlights the challenges of working with high resolution spatial data over broad spatial extents.