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Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia
Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia
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Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia
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Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia
Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia

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Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia
Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia
Journal Article

Post-flood land use damage estimation using improved Normalized Difference Flood Index (NDFI3) on Landsat 8 datasets: December 2014 floods, Kelantan, Malaysia

2018
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Overview
Floods in Malaysia have been increasing in frequency and magnitude as reflected in the Kelantan Flood event in 2014 that resulted in a huge loss of lives and properties. Whereas remote sensing (RS) and geographical information system (GIS) tools have been extensively applied in flood disaster management, there are few reports and studies on the impact of floods on the land use/land cover environment in a post-disaster assessment. In this study, an integrated modelling approach was developed that used Landsat 8 OLI TIRS (Operational Land Imager (OLI) and Thermal Infrared Sensor) data, flood indexing and classification processes to estimate the impact of flood on the environment. The Normalized Difference Flood Index-3 (NDFI3) is an improvement on NDFI2 that takes into account the effects of cloud shadow in the images when extracting flood index areas. The flood model developed showed good agreement when compared with flooded areas shown in SAR (synthetic-aperture radar) image. The results of the flood extent as a proxy for damage estimation showed that the total flooded area was 502.34 km2 for the Kelantan Flood event in 2014, with plantation and built-up area accounting for 43 and 34.6% respectively. The least affected land uses/land covers were deforested area and forest, which accounted for 12.2 and 10.2% respectively. The RS and GIS technique developed in this post-disaster damage assessment is effective, relatively inexpensive and simple to implement by local authorities in support of post-flood disaster planning and decision-making.