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Remote Sensing for Coastal Management
Controlling RunoffNonpoint source pollution that results from rainfall and runoff can harm the surrounding ecosystem, but certain types of land cover can buffer the effects. Land cover data derived from remote sensing can be used to help model the potential for pollution from storm water runoff. The Project: Carmans River, Long Island, New York
Because the Carmans River is close to New York City, its watershed is being developed as the population grows and nearby suburbs expand. As a result, nonpoint source pollution is increasing dramatically, leading to degraded fisheries and the closure of beaches and shellfish beds. Polluted storm water runoff is the most widespread water quality problem along the southern shore of Long Island. Applying Land Cover DataPollution potential models are used to predict and quantify the intensity of runoff for a particular landscape. Essentially, these models predict how much an area will contribute to pollution via storm water runoff. The amount of runoff after a storm is influenced by the ground's ability to absorb water (permeability), the type of soil, the topography of the land (i.e., relief, lowlands, hills), and cover conditions, such as vegetation types or pavement. Therefore, land cover data, combined with other physical and biological data, are an important component of a pollution potential model. The Carmans River area was selected as a test site to develop an application that determines pollution potential using land cover data developed from the Landsat Thematic Mapper using the NOAA Coastal Change Analysis Program (C-CAP) protocol (Dobson and others 1995).
C-CAP land cover data have up to 22 standard classes, including two developed classes. Using ancillary data, high intensity developed (urban) and low intensity developed (suburban) classes were differentiated into three classes: high intensity, medium intensity, and low intensity developed. The distinctions between the classes were based on the amount of impervious surfaces (surfaces that cannot absorb water) in each land cover type (e.g., paved roads, parking lots). These range from 100 percent impervious (parking lots and roads) to residential developments with grass-covered lawns and trees. The model incorporated spatial information (e.g., proximity to a vulnerable body of water), physical characteristics of each class, and storm runoff prediction curves (runoff estimates based on physical characteristics of land, such as soil type and vegetation) to pinpoint potential pollution problems, or "hotspots," along the Carmans River. The information generated from the Carmans River test site highlighted areas that may need additional management or remediation to reduce pollutant runoff. Two local governments along the South Shore have incorporated this information into townwide watershed management plans. After locating "hotspots," they can use special zoning restrictions, more stringent site reviews, and other actions to curtail nonpoint pollution and protect overall water quality. The ResultMany coastal managers are changing the way they manage nonpoint source pollution problems. Instead of only undertaking corrective measures, officials are moving toward prevention. Using runoff pollution potential models with land cover data, managers can create scenarios for future development, as well as permitting and land use scenarios, to estimate the impacts on sensitive water bodies. For More Information
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