Thirteenth International Conference on Climate Change: Impacts & Responses

Abstract

The objective of this research was to develop a new damaged area assessment (DAA) method to measure the area in tropical cyclone-affected coastal regions of Bangladesh. In this research, the Kalapara sub-district of Bangladesh was considered in the development of a DAA method using Landsat 8 OLI and TIRS datasets. The weighted-overlay method was incorporated with a pix-code sum (plus+) operation on the NDVI-CTC (CD-5), SAVI-CTC (CD-6) and SMI-CTC (CD-8) datasets to determine the expected damage type classes (DTCs). The plus+ operation was developed with a conditional pseudo-code algorithm to determine the affected agricultural land areas. We found that the undamaged area in square km was 7.71 (2.5%), slightly damaged area was 32.96 (10.66%), moderately damaged area was 79 (25.56%); very damaged area was 131.56 (42.56%), and extremely damaged area was 57.85 (18.72%). We separately assessed point DAA through a total of 420 reference point observations on agricultural lands in the study area. We randomly observed that totals of 4 points (0.95%), 13 points (3.10%), 52 points (12.38%), 205 points (48.81%) and 146 points (34.76%) were calculated to represent the undamaged, slightly damaged, moderately damaged, very damaged and extremely damaged ground point areas, respectively. These ground reference points were accurately matched in the area using DAA to validate the damaged areas. The DAA method with DTCs could be helpful for researchers creating new disaster risk reduction policies to help local farming communities prepare an effective cyclone mitigation plan at the regional level of the country to reduce losses and risks.