Using Multitemporal Remote Sensing Imagery and Inundation Measures to Improve Land Change Estimates in Coastal Wetlands
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Remote sensing imagery can be an invaluable resource to quantify land change in coastal wetlands. Obtaining an accurate measure of land change can, however, be complicated by differences in fluvial and tidal inundation experienced when the imagery is captured. This study classified Landsat imagery from two wetland areas in coastal Louisiana from 1983 to 2010 into categories of land and water. Tide height, river level, and date were used as independent variables in a multiple regression model to predict land area in the Wax Lake Delta (WLD) and compare those estimates with an adjacent marsh area lacking direct fluvial inputs. Coefficients of determination from regressions using both measures of water level along with date as predictor variables of land extent in the WLD, were higher than those obtained using the current methodology which only uses date to predict land change. Land change trend estimates were also improved when the data were divided by time period. Water level corrected land gain in the WLD from 1983 to 2010 was 1 km2 year−1, while rates in the adjacent marsh remained roughly constant. This approach of isolating environmental variability due to changing water levels improves estimates of actual land change in a dynamic system, so that other processes that may control delta development such as hurricanes, floods, and sediment delivery, may be further investigated.
KeywordsLand change Remote sensing Inundation Multitemporal Landsat
Continuing support during this analysis was provided by the US Army Corps of Engineers, New Orleans District Office, and the US Army Corps of Engineers Engineer Research and Development Center. Thoughtful reviews by Greg Steyer (US Geological Survey), Guerry Holm (Louisiana State University), Sally Yost, and Molly Reif (both of US Army Corps of Engineers) greatly improved an earlier version of this manuscript.
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