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Multi-temporal sub-pixel landsat ETM+ classification of isolated wetlands in Cuyahoga County, Ohio, USA
Citation:
Frohn, R. C., E. D'Amico, C. R. LANE, B. C. AUTREY, J. Rhodus, AND H. Liu. Multi-temporal sub-pixel landsat ETM+ classification of isolated wetlands in Cuyahoga County, Ohio, USA. WETLANDS. The Society of Wetland Scientists, McLean, VA, 32(2):289-299, (2012).
Impact/Purpose:
The goal of this research is to develop methods and indicators that are useful for evaluating the condition of aquatic communities, for assessing the restoration of aquatic communities in response to mitigation and best management practices, and for determining the exposure of aquatic communities to different classes of stressors (i.e., pesticides, sedimentation, habitat alteration).
Description:
The goal of this project was to determine the utility of subpixel processing of multi-temporal Landsat Enhanced Thematic Mapper Plus (ETM+) data for the detection of isolated wetlands greater than 0.50 acres in Cuyahoga County, located in the Erie Drift Plains ecoregion of northeast Ohio, USA. A previous study determined that segmentation and object-oriented analysis of Landsat ETM+ was useful for mapping forested and emergent marsh isolated wetlands in Alachua County, a county in the Southern Coastal Plain ecoregion in Florida, USA. However, the segmentation and object-oriented analysis method works best for isolated wetlands that have well-defined high-contrast boundaries between wetland and surrounding upland, which was not the case for the isolated wetlands of our study area. We developed a new methodology that incorporated multi-temporal Landsat ETM+ data, a Normalized Difference Vegetation Index mask, and a matched filtering method to map 10,625 acres of isolated wetlands in our 460 square mile study area. The matched filtering method determines the apparent abundance of wetlands at subpixel levels in the presence of spectrally mixed unknown background through a partial unmixing algorithm. The final overall accuracy of the classification was 87% with a Kappa coefficient of 0.85. Producer Accuracy for isolated wetlands was 88% and User Accuracy of isolated wetlands was 87%. The subpixel matched filtering method used in this research appears to provide an effective means for mapping isolated wetlands >0.50 acres, especially those with boundaries that are not easily detected, such as wetlands under a canopy.
