Estimation of economic loss and recover process after earthquake base on nighttime light data and time series model

Jinpeng Zhao, Xiaojun Li and Su Chen

Reliability Engineering and System Safety, 2025, vol. 263, issue C

Abstract: This study develops a framework for predicting Nighttime Light (NTL) data trends without earthquakes and estimating economic losses and recovery processes after an earthquake. Utilizing Geographic Information System (GIS) technology, the framework unfolds through five stages: data acquisition and extraction, data transformation and calibration, model training and tuning for each 500 m x 500 m grid in the Jiuzhaigou earthquake area in Sichuan Province, China, and calculation of economic losses by comparing NTL predictions and actual observations. By integrating socio-economic characteristics and Damage Index data with NTL trends, and adjusting for model performance through hyperparameter tuning, this research quantifies economic impacts after an earthquake. Final estimates of economic losses and recovery are derived by allocating losses according to each grid’s calculated weight. This study not only predicts NTL data trends in scenarios without earthquake but also contributes novel methods for evaluating economic losses and recovery from earthquakes, presenting an effective framework for similar disaster impact studies.

Keywords: Earthquake economic loss; Disaster risk management; Grid economic loss; NTL data; Machine learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:263:y:2025:i:c:s0951832025004454

DOI: 10.1016/j.ress.2025.111244

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