Category:åÊMonitoring Wetlands and Mitigating Floods
Project Team: Great Lakes Climate II
Team Location: NASA Langley Research Center ÛÒ Hampton, Virginia
Authors:
Emily Adams
Idamis Del Valle Martinez
Miriam Harris
Stephen Zimmerman
Rodney Meyer
Mentors/Advisors:
Dr. Kenton Ross (NASA DEVELOP National Program)
James Favors (NASA DEVELOP National Program)
Past/Other Contributors:
Janice Maldonado Jaime
Lydia Cuker
Kathy Currie
Lacey Freese
Pamela King
Daniel Marx
Abstract:
The Laurentian Great Lakes region of North America include several types of coastal wetlands (e.g., swamps and marshes) that support a high diversity of biota. The health of these ecosystems is important for ecological communities and economic industries, which benefit from fisheries and tourism. Great Lakes wetlands have been estimated to provide more than $10,000 per acre in economic and ecosystem services. The effects of climate change, including variations in temperature, precipitation, and evapotranspiration, could impact the water level of the Great Lakes directly, and therefore, the development and survival of coastal wetlands. Increasing environmental pressures from rising populations, invasive species, and pollution also will negatively affect these wetlands if they are not managed appropriately. An updated land cover classification was developed, using a Random Forest classification method, to evaluate and monitor changes in the wetlands around Georgian Bay and the Southern portion of Lake Ontario. NASA Earth observation data from Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) provided historical images and current images to classify land cover. Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data provided digital elevation model (DEM) data, from which slope was calculated. Resultant land cover classifications were validated with ground truth data. Additionally, TOPEX/Poseidon Jason-1 and Ocean Surface Topography Mission (OSTM)/Jason-2 radar altimeters and in situ water gauge data served as a resource for tracking water levels over time. This methodology offers a more cost-effective approach to monitoring wetlands in the region.
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