An Optical and SAR Based Fusion Approach for Mapping Surface Water Dynamics over Mainland China

Remote Sensing

Kenneth Grogan¹  Christian Tottrup¹  Daniel Druce¹  CecileM.M. Kittel¹  Xiaoye Tong²  Xia Lei³  Tao Guo³ 

[1] DHI GRAS, Agern Alle 5, 2970 Hørsholm, Denmark;Department of Geosciences and Natural Resource Management (IGN), University of Copenhagen, 1350 Copenhagen, Denmark;Piesat Information Technology Co., Ltd., Beijing 100000, China;

关键词: surface water mapping;    SAR and optical data fusion;    logistic regression;    water resource management;    sustainable development;   

DOI  :  10.3390/rs13091663

来源: DOAJ

【 摘 要 】

Earth Observation (EO) data is a critical information source for mapping and monitoring water resources over large inaccessible regions where hydrological in-situ networks are sparse. In this paper, we present a simple yet robust method for fusing optical and Synthetic Aperture Radar (SAR) data for mapping surface water dynamics over mainland China. This method uses a multivariate logistic regression model to estimate monthly surface water extent over a four-year period (2017 to 2020) from the combined usages of Sentinel-1, Sentinel-2 and Landsat-8 imagery. Multi-seasonal high-resolution images from the Chinese Gaofen satellites are used as a reference for an independent validation showing a high degree of agreement (overall accuracy 94%) across a diversity of climatic and physiographic regions demonstrating potential scalability beyond China. Through inter-comparison with similar global scale products, this paper further shows how this new mapping technique provides improved spatio-temporal characterization of inland water bodies, and for better capturing smaller water bodies (< 0.81 ha in size). The relevance of the results is discussed, and we find this new enhanced monitoring approach has the potential to advance the use of Earth observation for water resource management, planning and reporting.

【 授权许可】

Unknown