Visual and semi-automated
interpretation methods for urban flood detection using SAR Sentinel-1A image: study
case in North Aceh Regency, Indonesia
Ayyasy Muhammad Fadhil and Akhyar
Disaster Advances; Vol. 16(2); 30-40;
doi: https://doi.org/10.25303/1602da030040; (2023)
Abstract
Flood is a natural disaster when causes damage and loss, especially in urban areas
that are inhabited by many people and have many properties. The goal of this study
is to map rapidly the flooded areas in North Aceh district on January, 5 2022 using
multi-temporal SAR Sentinel-1A images through visual interpretation and semi-automated
interpretation methods including thresholding and support vector machine (SVM).
Visual interpretation relied on multi-polarization image of VH-VV with median filters
of 3x3 and 5x5.
This study produced the flooded area maps from three methods used with an area of
each method: visual interpretation (422.86 ha), thresholding (791.22 ha) and SVM
(1084.76 ha). According to the comparison with the result generated from visual
interpretation using Planetscope-3A, SVM method has the similar result in the flooded
areas with an area of 1001.52 ha. This study also analysed impact of flood event
against land cover referring to Sentinel-2 10-Meter Land Use/Land Cover of ESRI
and showed that class of cultivated crops is most affected. Results show that this
study can be very helpful in damage and loss assessment of flood event and can be
reference for urban planning management in order to face the climate change.
