A Method to Construct an Environmental Vulnerability Model Based on Multi-Source Data to Evaluate the Hazard of Short-Term Precipitation-Induced Flooding

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-03, Vol.15 (6), p.1609
• Main Authors: Zhu, Hong, Yao, Jiaqi, Meng, Jian, Cui, Chengling, Wang, Mengyao, Yang, Runlu
• Format: Article
• Language: English
• Subjects: AHP; Analysis; Analytic hierarchy process; Artificial satellites in remote sensing; China; Classification; Climate change; Disaster risk; Disasters; Economic impact; Emergency preparedness; Entropy; Environmental risk; Environmental Vulnerability Analysis Model (EVAM); Evaluation; Feature extraction; flood; Flood control; Flood hazards; Flood management; Flooding; Floods; Land use; Land use classification; Methods; multi-source data; Post-disaster reconstruction; Precipitation; Precipitation (Meteorology); Rain; Remote sensing; Risk assessment; Risk management; Satellite imagery; Sensitivity; U-NET
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15061609

Flood hazards resulting from short-term severe precipitation have caused serious social and economic losses and have posed extraordinary threats to the safety of lives and property. Vulnerability, which reflects the degree of the adverse impact of flooding on a city, the sensitivity of the environment, and the extent to which rescues are possible during flooding, is one of the significant factors of the disaster risk assessment. Because of this, this paper proposes an Environmental Vulnerability Analysis Model (EVAM), based on comprehensively evaluating multi-source remote sensing data. The EVAM includes a two-stage, short-term flood vulnerability assessment. In the first stage, the flood’s areal extension and land-use classification are extracted, based on the U-NET++ network, using multi-source satellite remote sensing images. The results from the first stage are used in the second stage of vulnerability assessment. In the second stage, combining multi-source data with associated feature extraction results establishes the Exposure–Sensitivity–Adaptive capacity framework. The short-term flood vulnerability index is leveraged through the analytic hierarchy process (AHP) and the entropy method is calculated for an environmental vulnerability evaluation. This novel proposed framework for short-term flood vulnerability evaluation is demonstrated for the Henan Province. The experimental results show that the proportion of vulnerable cities in the Henan Province ranging from high to low is 22.22%, 22.22%, 38.89%, and 16.67%, respectively. The relevant conclusions can provide a scientific basis for regional flood control and risk management as well as corresponding data support for post-disaster reconstruction in disaster regions.