Abstract
Satellite remote sensing provides significant information for the monitoring of natural disasters. Recently, on a global scale, floods have been increasing both in frequency and in magnitude. In order to map the inundation area, flooding events are investigated using unique RGB composite imagery based on the MODIS surface reflectance (MOD09GA) data obtained from the Terra satellite, which is used to visualize and analyze these events. This study proposes using an RGB combination of MODIS band 6 (1.64 μm), band 5 (1.24 μm), and band 2 (0.86 μm) data from the visible and the near-infrared spectral ranges to map flood events. The flooding events that were investigated in this study occurred on 25 October 2015 along the Pampanga River in the Philippines, and on 28 July 2016 along the Poyang and Dongting Lakes in China. In the case of the Pampanga River, the inundated areas were estimated with surface reflectance (R) thresholds of 0.0 ≤ R6 ≤ 0.102, 0.0 ≤ R5 ≤ 0.138, and 0.03 ≤ R2 ≤ 0.148 for MODIS bands 6, 5, and 2, respectively, which were determined using Otsu’s method. The total inundated area was estimated to be 487.75 km2. This estimate was indirectly compared with the results obtained from SENTINEL-1A Synthetic Aperture Radar (SAR) data. The total inundated area on 26 October 2015 for the case of the Pampanga River was estimated to be 486.37 km2 using histogram analysis based on Otsu’s method. For the flooding case in China, the total estimated inundated area using MODIS RGB imagery on 28 July 2016 and SAR on 3 August 2016 was 1148.25 km2 and 1110.096 km2, respectively. In addition, RGB imagery results using MODIS 6-5-2 bands were supported by the refractive index retrieval along the inundation area. A threshold of 1.6 for the real part of the complex refractive index allows for the discrimination between the flooded and non-flooded areas using the Hong and ASH approximations. This study shows that the RGB composite techniques using advanced sensors with more bands and higher spatio-temporal resolutions, and supported by the refractive index retrieval method, are useful for estimating flood events.
Highlights
The recent increase in the number of natural disasters has become a global issue, because of the damages to the hydrological and ecological environment and human-made infrastructure, and the threats to human lives
This study shows that the RGB composite techniques using advanced sensors with more bands and higher spatio-temporal resolutions, and supported by the refractive index retrieval method, are useful for estimating flood events
Bimodal distributions of the surface reflectance histograms were more suitable for the separation of the flooded areas from the non-flooded areas for MODIS band 2 (0.86 μm), band 5 (1.24 μm), and band 6 (1.64 μm) data
Summary
The recent increase in the number of natural disasters has become a global issue, because of the damages to the hydrological and ecological environment and human-made infrastructure, and the threats to human lives. Satellite remote sensing techniques provide valuable support for monitoring these disasters and for post-event crisis management. Many studies have demonstrated the effectiveness of SAR data in mapping wetlands [7,8], because it has the advantage of observations during the night and day, and under cloud cover [9,10]. These methods have a disadvantage: SAR data largely depends on the accuracy of the determined thresholds that are usually static in space and time, despite the significant variability of the backscatter. This may lead to the misidentification of pixels [11]
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