Analyzing short term spatial and temporal dynamics of water presence at a basin-scale in Mexico using SAR data

Abstract

The dynamic nature of continental water body covers is a main indicator of the status of this ecological capital and its trends on the land surface. With synthetic aperture radar (SAR), various water coverage processes can be identified using satellite data. This study proposes the use of a basin-level analysis with SAR images at a medium spatial resolution to perform a regional spatial-temporal analysis for detecting water presence. It develops a methodology to improve the separation of water bodies from other land covers by using a texture analysis, a support-vector machine classification, and the gray level co-occurrence matrix (GLCM). GLCM-mean texture parameter was found to offer sufficient texture information for separating the water class from the land class by providing a more homogeneous measurement of water bodies. The case under study is the Grijalva River Basin, Mexico, a region that requires more in-depth research so that the management of surface water coverage can be integrated with ecosystems, particularly those that are subject to intense human activity. The entire basin was mapped using a series of observations from Sentinel-1. This study produced a total of 36 water body maps with an acceptable classification accuracy of over 90% for each year studied (2016, 2017, and 2018). Water presence was also quantified, resulting in a set of maps containing regional detail, from which temporal data can be obtained on areas with water presence year-round and areas with seasonal flooding. Frequency maps with a 10-km unit cell as the spatial unit were used to detect trends and thereby identify water distribution patterns. The results show the importance of ongoing, basin-level quantifications of zones with dynamic water presence and those with stable water presence.

Keywords

• grijalva basin
• sentinel-1
• seasonal characterization
• texture information