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Land Cover Classification for Snohomish County Critical Area Monitoring

Snohomish County in Washington State is required by the Washington State Growth Management Act to protect areas of critical area functions and values, including habitat. The county applies critical area regulations and implements non-regulatory environmental programs to achieve this protection, which is measured and supported by a county-adopted monitoring and adaptive management program. As a central element of the program, the county intends to use remote monitoring techniques to detect changes in impervious surfaces, wetlands, and riparian areas. The initial remote-sensing analysis reported here developed techniques and a protocol for mapping these critical habitats and generated a baseline map of the existing land cover. This project was undertaken by a collaborative team from Snohomish County and Battelle Pacific Northwest Division, which consisted of project leaders, remote-sensing analysts, biologists, a hydrologist, and a statistical analyst. The interdisciplinary team's objectives were to 1) develop a process for creating an accurate map of vegetation and impervious surfaces and 2) create a baseline map of vegetation and impervious surfaces. To provide an accurate estimate of critical areas, a computer-aided classification of vegetation was performed to characterize the amount, type, and location of vegetation in Snohomish County. This classification relied on high-resolution satellite (QuickBird and AVNIR-2) and Light Detection and Ranging digital elevation data with over 1000 field ground truth points to identify and map vegetation types. The resulting map was assessed to have an accuracy of 80%. The next steps to further improve the classification are outlined. The project resulted in highly accurate maps of impervious surfaces and vegetation cover for the mapped areas in the county. Through the baseline study, we have observed the effectiveness and challenges of using remote-sensing data in delineating vegetation cover and impervious surfaces. Using these techniques to classify and track changes in riparian forest vegetation, wetlands, and impervious surface is possible, but great care must be taken during field data collection, image calibration, and rule development. iii Acknowledgments The interdisciplinary expertise of the collaborative team is gratefully acknowledged. Our thanks to the Snohomish County Critical Area Regulations team—project leader Andy Haas, remote-sensing analyst Gi-Choul Ahn, and biologists Mike Rustay and Scott Moore; and the Battelle contracting team— remote-sensing analyst/project lead Jerry Tagestad, hydrologist Andre Coleman, statistical analyst