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Title: Large lake gauging using fractional imagery
Authors: Park, Edward
Lewis, Quinn W.
Sanwlani, Nivedita
Keywords: Engineering::Environmental engineering
Issue Date: 2018
Source: Park, E., Lewis, Q. W., & Sanwlani, N. (2019). Large lake gauging using fractional imagery. Journal of Environmental Management, 231, 687-693. doi:10.1016/j.jenvman.2018.10.044
Journal: Journal of Environmental Management
Abstract: Large floodplain lakes provide riparian habitat, are sediment and nutrient sinks, help control flow connectivity and flooding along rivers, and are both used by humans and strongly impacted by human activity. However, water level in many remote large floodplain lakes, especially in developing countries, is often monitored inconsistently or not at all. In this study, a novel method for estimating large lake water level using passive, optical remote sensing data combined with any digital elevation model (DEM) is presented. The method obtains water level estimates at 30 m2 resolution using Landsat, in this case in conjunction with SRTM elevation data, nested within a 240 m2 grid "fishnet". A probabilistic mean of elevation values for all water-designated pixels (between 5% and 95% filled within each grid) produces lake water levels often accurate to within ±50 cm of gauged reference data on Lake Curuai in the Amazon River and Tonle Sap Lake along the Mekong River. The method is relatively insensitive to cloud cover, especially as lake size increases. This study is the first to use solely passive optical remote sensing data for water level estimation and thus could be used to produce accurate, long-term estimations of water level in many large lakes globally. The use of optical sensors to obtain lake water level is both an important complement and potential alternative to methods that use active sensors.
ISSN: 0301-4797
DOI: 10.1016/j.jenvman.2018.10.044
Rights: © 2018 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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