TY - JOUR
T1 - A Wildfire Monitoring Method Based on Daily Nighttime Light Data
T2 - A Case Study of the Los Angeles Wildfire
AU - Yuan, Yuan
AU - Wang, Congxiao
AU - Xu, Wei
AU - Zhang, Lefeng
AU - Zhu, Jianbin
AU - Tu, Yue
AU - Yu, Bailang
N1 - Publisher Copyright:
© 2026 IEEE. All rights reserved.
PY - 2026
Y1 - 2026
N2 - Wildfires are among the most destructive natural disasters, inflicting severe and irreversible damage to ecosystems and human societies. However, most existing research lacked sufficient spatial coverage and spatiotemporal continuity to provide near-real-time assessments of wildfire impacts, including their extent and severity. Leveraging globally accessible, temporally continuous nighttime light (NTL) data from National Aeronautics and Space Administration (NASA)’s Black Marble VNP46A1 product, this study developed a threshold-based method to delineate wildfire-affected areas and quantify impact severity from daily observations, providing a rapid and scalable solution for near-real-time wildfire assessment across diverse regions and events. The method was applied to the Los Angeles (LAs) wildfire of January 2025, which resulted in infrastructure losses exceeding U.S. $50 billion. The results showed that the proposed approach effectively captured wildfire-affected regions—particularly in the Palisades, Eaton, and Hurst areas—covering approximately 307.75 km2. The sharp increase in NTL intensity from ∼30 to 4750 nW/cm2/sr revealed the extreme burning severity of the event. Furthermore, approximately 30 252 buildings and 281 240 individuals were estimated to be directly affected, with impacts classified into five severity levels to characterize variations in damage intensity across the affected areas. Overall, the proposed method demonstrated strong potential for large-scale wildfire monitoring and rapid impact assessment, offering near–real-time applicability and globally accessible data support.
AB - Wildfires are among the most destructive natural disasters, inflicting severe and irreversible damage to ecosystems and human societies. However, most existing research lacked sufficient spatial coverage and spatiotemporal continuity to provide near-real-time assessments of wildfire impacts, including their extent and severity. Leveraging globally accessible, temporally continuous nighttime light (NTL) data from National Aeronautics and Space Administration (NASA)’s Black Marble VNP46A1 product, this study developed a threshold-based method to delineate wildfire-affected areas and quantify impact severity from daily observations, providing a rapid and scalable solution for near-real-time wildfire assessment across diverse regions and events. The method was applied to the Los Angeles (LAs) wildfire of January 2025, which resulted in infrastructure losses exceeding U.S. $50 billion. The results showed that the proposed approach effectively captured wildfire-affected regions—particularly in the Palisades, Eaton, and Hurst areas—covering approximately 307.75 km2. The sharp increase in NTL intensity from ∼30 to 4750 nW/cm2/sr revealed the extreme burning severity of the event. Furthermore, approximately 30 252 buildings and 281 240 individuals were estimated to be directly affected, with impacts classified into five severity levels to characterize variations in damage intensity across the affected areas. Overall, the proposed method demonstrated strong potential for large-scale wildfire monitoring and rapid impact assessment, offering near–real-time applicability and globally accessible data support.
KW - Disaster severity
KW - VNP46A1
KW - fire area mapping
KW - nighttime light (NTL) data
KW - wildfires
UR - https://www.scopus.com/pages/publications/105031580279
U2 - 10.1109/LGRS.2026.3669070
DO - 10.1109/LGRS.2026.3669070
M3 - 文章
AN - SCOPUS:105031580279
SN - 1545-598X
VL - 23
JO - IEEE Geoscience and Remote Sensing Letters
JF - IEEE Geoscience and Remote Sensing Letters
M1 - 8001405
ER -