An approach for global monitoring of surface water extent variations using MODIS data

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.