Abstract
Climate change, increasing population and changes in land use are all rapidly driving the need to be able to better understand surface water dynamics. The targets set by the United Nations under Sustainable Development Goal 6 in relation to freshwater ecosystems also make accurate surface water monitoring increasingly vital. However, the last decades have seen a steady decline in in situ hydrological monitoring and the availability of the growing volume of environmental data from free and open satellite systems is increasingly being recognized as an essential tool for largescale monitoring of water resources. The scientific literature holds many promising studies on satellite-based surface-water mapping, but a systematic evaluation has been lacking. Therefore, a round robin exercise was organized to conduct an intercomparison of 14 different satellite-based approaches for monitoring inland surface dynamics with Sentinel-1, Sentinel-2, and Landsat 8 im-agery. The objective was to achieve a better understanding of the pros and cons of different sensors and models for surface water detection and monitoring. Results indicate that, while using a single sensor approach (applying either optical or radar satellite data) can provide comprehensive results for very specific localities, a dual sensor approach (combining data from both optical and radar satellites) is the most effective way to undertake largescale national and regional surface water mapping across bioclimatic gradients.
Original language | English |
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Article number | 2410 |
Pages (from-to) | 1-21 |
Number of pages | 21 |
Journal | Remote Sensing |
Volume | 14 |
Issue number | 10 |
DOIs | |
Publication status | Published - 2 May 2022 |
Bibliographical note
Funding Information:This study was executed in the context of the WorldWater project, funded by European Space Agency (ESA) under the EO Science for Society programmatic element of the 5th Earth Observation Envelope Programme (EOEP-5, 2017–2021). S. Liu and H. Zhou were funded by the National Key Research and Development Program of China (Grant No. 2018YFE0106500).
Publisher Copyright:
© 2022, MDPI. All rights reserved.
Funding
This study was executed in the context of the WorldWater project, funded by European Space Agency (ESA) under the EO Science for Society programmatic element of the 5th Earth Observation Envelope Programme (EOEP-5, 2017–2021). S. Liu and H. Zhou were funded by the National Key Research and Development Program of China (Grant No. 2018YFE0106500).
Funders | Funder number |
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EO Science for Society | |
European Space Agency | |
National Key Research and Development Program of China | 2018YFE0106500 |
National Key Research and Development Program of China |
Keywords
- data fusion
- SAR and optical data
- surface water dynamics
- Sustainable Development Goal 6
- water resource management