Black Marble Nighttime Light Data for Disaster Damage Assessment
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Published:2023-08-30
Issue:17
Volume:15
Page:4257
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Zhang Danrong1ORCID, Huang Huili1ORCID, Roy Nimisha2ORCID, Roozbahani M. Mahdi2ORCID, Frost J. David3ORCID
Affiliation:
1. School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA 2. School of Computing Instruction, Georgia Institute of Technology, Atlanta, GA 30332, USA 3. School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
Abstract
This research explores the utilization of the Black Marble nighttime light (NTL) product to detect and assess damage caused by hurricanes, tornadoes, and earthquakes. The study first examines average regional NTL trends before and after each disaster, demonstrating that NTL patterns for hurricanes closely align with the features of a resilience curve, unlike those for earthquakes and tornadoes. The relative NTL change ratio is computed using monthly and daily NTL data, effectively reducing variance due to daily fluctuations. Results indicate the robustness of the NTL change ratio in detecting hurricane damage, whereas its performance in earthquake and tornado assessment was inconsistent and inadequate. Furthermore, NTL demonstrates a high performance in identifying hurricane damage in well-lit areas and the potential to detect damage along tornado paths. However, a low correlation between the NTL change ratio and the degree of damage highlights the method’s limitation in quantifying damage. Overall, the study offers a promising, prompt approach for detecting damaged/undamaged areas, with specific relevance to hurricane reconnaissance, and points to avenues for further refinement and investigation.
Funder
US National Science Foundation
Subject
General Earth and Planetary Sciences
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