Year: 2016
Type: report
Abstract: Freshwater resources are among the most basic requirements of human society. Nonetheless, global information about the space-time variations of the area of freshwater bodies, and the water stored in them, is surprisingly limited. We introduce a MODIS-based algorithm to map the global areal extent of surface water bodies at 500m spatial resolution at nominal eight-day intervals from 2000 to 2015. We demonstrate the algorithm construction and performance for five reservoirs on four continents with different shapes. The algorithm performs well compared to satellite radar altimetry and in situ height measurements, and in comparison with surface area estimates based on higher resolution Landsat data. We further present a summary of our global scale results over 69 reservoirs for which altimetry measurements are available, and show that our surface area estimates match well with relative height variations and show significant improvements over previous estimates. One of the main reasons for these improvements is a novel post-processing technique that makes use of imperfect labels produced by supervised classification approaches on multiple dates to estimate the elevation structure of locations that is used to enhance the quality and completeness of imperfect labels. However, the approach is still challenged in regions with frequent cloud cover, snow and ice coverage, or complicated geometries that require finer spatial resolution remote sensing data. The surface area estimates we describe here are publically available.
Authors: Ankush Khandelwal, Anuj Karpatne, Miriam E. Marlier, Jong‐Youn Kim, Dennis P. Lettenmaier, Vipin Kumar
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
Awards: DC: Medium: Collaborative Research: ELLF: Extensible Language and Library Frameworks for Scalable and Efficient Data-Intensive Applications, Collaborative Research: Understanding Climate Change: A Data Driven Approach, THE SCARCITY OF GLOBAL-SCALE WATER USE DATA LIMITS THE ABILITY OF THE LAND SURFACE SCHEMES USED IN EARTH SYSTEM MODELS TO REPRESENT THE EFFECTS OF WA, THERE IS AN URGENT NEED IN GLOBAL CLIMATE CHANGE SCIENCE FOR EFFICIENT MODEL AND/OR DATA ANALYSIS ALGORITHMS THAT CAN BE DEPLOYED IN DISTRIBUTED AND
OpenAlex ID: W3202333041