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

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...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2021-05, Vol.13 (9), p.1663
Main Authors: Druce, Daniel, Tong, Xiaoye, Lei, Xia, Guo, Tao, Kittel, Cecile M.M., Grogan, Kenneth, Tottrup, Christian
Format: Article
Language:English
Subjects:
Climate change
Ecosystems
Freshwater resources
Hydrology
Image resolution
Inland waters
Landsat
Landsat satellites
logistic regression
Mapping
Monitoring
Regression models
Remote sensing
Resource management
SAR and optical data fusion
Satellite imagery
Surface water
surface water mapping
Sustainable development
Synthetic aperture radar
Water monitoring
water resource management
Water resources
Water resources management
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Summary: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.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs13091663