Articles | Volume 19, issue 9
https://doi.org/10.5194/hess-19-3755-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-3755-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A review of applications of satellite SAR, optical, altimetry and DEM data for surface water modelling, mapping and parameter estimation
UNESCO-IHE Institute for Water Education, Delft, the Netherlands
I. Popescu
UNESCO-IHE Institute for Water Education, Delft, the Netherlands
A. Mynett
UNESCO-IHE Institute for Water Education, Delft, the Netherlands
Department of Civil Engineering, Technical University Delft, Delft, the Netherlands
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- Integrating remote sensing derived indices and machine learning algorithms for precise extraction of small surface water bodies in the lower Thoubal river watershed, India M. Hibjur Rahaman et al. 10.1016/j.jclepro.2023.138563
- Super-resolution for terrain modeling using deep learning in high mountain Asia Y. Jiang et al. 10.1016/j.jag.2023.103296
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Short summary
Hydrological data collection is a challenge for the scientific community, especially as some events e.g. floods occur in un-gauged rivers or infrequently.
Some such events are however recorded by satellites.
Using satellite remote sensing in estimating surface water parameters has its limitations, but recent improvements in sensor specifications, expansion in research methods and knowledge of satellite data have increased its utilization.
The review is on modelling and mapping with RS.
Hydrological data collection is a challenge for the scientific community, especially as some...