Applications of Sentinel -1 SAR Data for Flood Damage Assessment: a Case Study of Central Vietnam Flooding Event in October 2020

EasyChair Preprint 7136

Abstract

Floods are one of the major devastating natural hazards around the globe. Recent development in remote sensing technology provides support in faster and low-cost analysis of flood hazards. In this study, the Sentinel-1 SAR data was used for flood mapping and damage assessment. We selected the flood event that occurred in three provinces of Central Vietnam in October 2020. Random Forest algorithm was adopted to detect and classify the inundation areas from 344 sample points of training and testing. The results showed that the inundation situation remained high throughout October and the flooded area was up to 101,000 ha. The estimation of land cover damage showed that most of the affected areas were in the cultivated land and accounted for more than 90% of the total inundated area. The results help the decision-makers for better monitoring and flood damage assessment in Central Vietnam.

Keyphrases: Flood mapping, Random Forest, Sentinel-1, Vietnam

@booklet{EasyChair:7136,
  author    = {Hoang Duc Vinh and Liou Yuei-An},
  title     = {Applications of Sentinel -1 SAR Data for Flood Damage Assessment: a Case Study of Central Vietnam Flooding Event in October 2020},
  howpublished = {EasyChair Preprint 7136},
  year      = {EasyChair, 2021}}