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http://dx.doi.org/10.7780/kjrs.2018.34.5.7

Methodology to Apply Low Spatial Resolution Optical Satellite Images for Large-scale Flood Mapping  

Piao, Yanyan (Department of Geoinformatic Engineering, Inha University)
Lee, Hwa-Seon (Department of Geoinformatic Engineering, Inha University)
Kim, Kyung-Tak (Korea Institute of Civil Engineering and Building Technology)
Lee, Kyu-Sung (Department of Geoinformatic Engineering, Inha University)
Publication Information
Korean Journal of Remote Sensing / v.34, no.5, 2018 , pp. 787-799 More about this Journal
Abstract
Accurate and effective mapping is critical step to monitor the spatial distribution and change of flood inundated area in large scale flood event. In this study, we try to suggest methods to use low spatial resolution satellite optical imagery for flood mapping, which has high temporal resolution to cover wide geographical area several times per a day. We selected the Sebou watershed flood in Morocco that was occurred in early 2010, in which several hundred $km^2$ area of the Gharb lowland plain was inundated. MODIS daily surface reflectance product was used to detect the flooded area. The study area showed several distinct spectral patterns within the flooded area, which included pure turbid water and turbid water with vegetation. The flooded area was extracted by thresholding on selected band reflectance and water-related spectral indices. Accuracy of these flooding detection methods were assessed by the reference map obtained from Landsat-5 TM image and qualitative interpretation of the flood map derived. Over 90% of accuracies were obtained for three methods except for the NDWI threshold. Two spectral bands of SWIR and red were essential to detect the flooded area and the simple thresholding on these bands was effective to detect the flooded area. NIR band did not play important role to detect the flooded area while it was useful to separate the water-vegetation mixed flooded classes from the purely water surface.
Keywords
flood mapping; MODIS; thresholding; SWIR band; spectral mixture;
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