Abstract
Malaysia is affected by floods almost every year. In this situation, high-frequency flood monitoring is crucial so that timely measures can be taken. However, the low revisit time of the satellites, as well as occlusion cast by clouds in optical images, limits the frequency of flood observation of the focused area. Therefore, this study proposes utilising multisatellite data from optical satellites such as Landsat 7, Landsat 8, and Moderate Resolution Imaging Spectroradiometer (MODIS), as well as Synthetic Aperture Radar (SAR) images from Advanced Land Observation Satellite (ALOS-2) and Sentinel-1, to increase observation of flood. The main objective was to utilize Otsu image segmentation over both optical and SAR satellite images to distinguish water and nonwater areas in each image separately. For this, modified normalized difference water index (MNDWI) for the optical satellite and total dual-polarization backscatter for SAR satellite images were estimated. The focused area has been divided into Universal Transverse Mercator (UTM) square-size grids of 30 pixels, and each satellite image was reprojected and resampled with a pixel size of 0.001° to standardize the flood map resolution. The second objective was to assess the potential of image fusion for increasing the consistency of water area extraction. Two pairs of satellite images with the same observation period covering a flood event in September 2017 in Perlis, Malaysia, were processed using 2D wavelet transform. Lastly, the temporal changes of the integrated surface water extent were evaluated by comparing the output from both multisatellite and fused images with the observed water level data from the Department of Drainage and Irrigation. The results showed that the proposed model can be used to estimate flood duration as well as to estimate the flood-related losses, especially in ungauged or data-poor regions.
Highlights
Floods are recurrent natural disasters in Malaysia as a result of heavy rainfall especially during the monsoon season
Study Area. e study area is located in the state of Perlis, Malaysia, which was affected by floods in 2017. e study area extents ranges between 6°43′19′′ N latitude and 100°07′59′′ E longitude, covering a land area of about 795 km2. ere are two distinct seasons: a wet season with heavy rainfall and a hot season with prolonged drought. e wet season, which is associated with the southwestern monsoon, usually starts between April and May and lasts until September or October
Sentinel-1 images of the Arau and Kangar areas on 24 September 2017 were used as flood stage images. e methods described in Section 2.7 were used to extract the surface water area, and an automated thresholding method was developed to differentiate water and nonwater areas
Summary
Floods are recurrent natural disasters in Malaysia as a result of heavy rainfall especially during the monsoon season. Massive efforts have been performed to mitigate flood disasters in the country [1]. In 2017, Perlis experienced two flood events, in May and September. E flood consequences caused damage to paddies, resulting in a 65% reduction in crop weight and causing farmers an average loss of about Malaysian Ringgit (RM) 1800/h, with almost 194 farmers affected [2]. Multitemporal coverage of large areas using Earth observation satellites is widely used to observe differences in land cover before, during, and after flood events [3,4,5,6]. Large-scale information of flood situations can be retrieved from optical and radar satellite images
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