A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data


In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

Publication DOI: https://doi.org/10.1016/j.rse.2013.10.008
Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences > Sustainable environment research group
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Remote sensing of environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pekel, J-F, Vancutsem, C, Bastin, L, Clerici, M, Vanbogaert, E, Bartholomé, E & Defourny, P, 'A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data' Remote sensing of environment, vol. 140 (2014) DOI http://dx.doi.org/10.1016/j.rse.2013.10.008
Uncontrolled Keywords: MODIS ,water surface detection,time series analysis,color space transformation,HSV,spatial and temporal dynamics,multi-temporal,multi-spectral,pixel-based image analysis
Publication ISSN: 1879-0704
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https://www.sci ... 3763?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2014-01-01
Published Online Date: 2013-11-04
Authors: Pekel, J.-F.
Vancutsem, C.
Bastin, L. (ORCID Profile 0000-0003-1321-0800)
Clerici, M.
Vanbogaert, E.
Bartholomé, E.
Defourny, P.



Version: Accepted Version

Access Restriction: Restricted to Repository staff only

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