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Effective disaster response is critical for affected communities. Responders and decision-makers would benefit from reliable, timely measures of the issues impacting their communities during a disaster, and social media offers a potentially…

Social and Information Networks · Computer Science 2024-01-11 Zihui Ma , Lingyao Li , Libby Hemphill , Gregory B. Baecher , Yubai Yuan

Social media platforms provide a real-time lens into public sentiment during natural disasters; however, models built solely on textual data often reinforce urban-centric biases and overlook underrepresented communities. This paper…

Social and Information Networks · Computer Science 2026-02-20 Zihui Ma , Yiheng Chen , Runlong Yu , Afra Izzati Kamili , Fangqi Chen , Zhaoxi Zhang , Juan Li , Yuki Miura

With increased frequency and intensity due to climate change, wildfires have become a growing global concern. This creates severe challenges for fire and emergency services as well as communities in the wildland-urban interface (WUI). To…

Computers and Society · Computer Science 2021-09-17 Xilei Zhao , Yiming Xu , Ruggiero Lovreglio , Erica Kuligowski , Daniel Nilsson , Thomas Cova , Alex Wu , Xiang Yan

Wildland-Urban Interface (WUI) fires represent a compound disaster resulting from the interactions between natural ecosystems and human settlements, characterized by significantly dynamic evolving risks. However, most current risk…

Risk Management · Quantitative Finance 2025-11-24 Yusheng Hu , Huaiyi Pan , Shaobo Zhong , Liying Zhang

Climate-driven wildfires are intensifying, particularly in urban regions such as Southern California. Yet, traditional fire risk communication tools often fail to gain public trust due to inaccessible design, non-transparent outputs, and…

Computers and Society · Computer Science 2026-04-21 Sanaz Sadat Hosseini , Mona Azarbayjani , Mohammad Pourhomayoun , Hamed Tabkhi

Wildfire is one of the biggest disasters that frequently occurs on the west coast of the United States. Many efforts have been made to understand the causes of the increases in wildfire intensity and frequency in recent years. In this work,…

Machine Learning · Computer Science 2021-09-07 Tanqiu Jiang , Sidhant K. Bendre , Hanjia Lyu , Jiebo Luo

Wildfires pose a significant global threat to ecosystems worldwide, with California experiencing recurring fires due to various factors, including climate, topographical features, vegetation patterns, and human activities. This study aims…

This study presents a comprehensive analysis of four significant California wildfires: Palisades, Eaton, Kenneth, and Hurst, examining their impacts through multiple dimensions, including land cover change, jurisdictional management,…

Signal Processing · Electrical Eng. & Systems 2025-01-31 Seyd Teymoor Seydi

Each year, wildfires destroy larger areas of Spain, threatening numerous ecosystems. Humans cause 90% of them (negligence or provoked) and the behaviour of individuals is unpredictable. However, atmospheric and environmental variables…

Computer Vision and Pattern Recognition · Computer Science 2023-06-09 Helena Liz-López , Javier Huertas-Tato , Jorge Pérez-Aracil , Carlos Casanova-Mateo , Julia Sanz-Justo , David Camacho

Wildfires are increasingly impacting the environment, human health and safety. Among the top 20 California wildfires, those in 2020-2021 burned more acres than the last century combined. California's 2018 wildfire season caused damages of…

Machine Learning · Computer Science 2022-08-22 Rohan Tan Bhowmik

Disparity in suicide rates between urban and suburban/rural areas is growing, with rural areas typically witnessing higher suicide rates in the U.S. However, previous studies often ignored the effect of socio-environmental factors on the…

Applications · Statistics 2022-01-19 Sayanti Mukherjee , Zhiyuan Wei

Due to climate change and the disruption of ecosystems worldwide, wildfires are increasingly impacting environment, infrastructure, and human lives globally. Additionally, an exacerbating climate crisis means that these losses would…

Machine Learning · Computer Science 2025-09-16 Rohan Tan Bhowmik , Youn Soo Jung , Juan Aguilera , Mary Prunicki , Kari Nadeau

The growing frequency and intensity of wildfires pose serious threats to communities in wildland-urban interface regions. Understanding evacuation behavior is critical for effective emergency planning. This study analyzes evacuation during…

Applications · Statistics 2026-01-06 Shangkun Jiang , Ruggiero Lovreglio , Thomas J. Cova , Sangung Park , Susu Xu , Xilei Zhao

Wildfires have significantly increased in the United States (U.S.), making certain areas harder to live in. This motivates us to jointly analyze active fires and population changes in the U.S. from July 2020 to June 2021. The available data…

Methodology · Statistics 2024-11-19 Shijie Zhou , Jonathan R. Bradley

As wildfires are expected to become more frequent and severe, improved prediction models are vital to mitigating risk and allocating resources. With remote sensing data, valuable spatiotemporal statistical models can be created and used for…

Machine Learning · Computer Science 2021-11-30 Alissa Chavalithumrong , Hyung-Jin Yoon , Petros Voulgaris

The Burning Index (BI) produced daily by the United States government's National Fire Danger Rating System is commonly used in forecasting the hazard of wildfire activity in the United States. However, recent evaluations have shown the BI…

Applications · Statistics 2011-08-04 Haiyong Xu , Frederic Paik Schoenberg

Recent wildfires in the United States have resulted in loss of life and billions of dollars, destroying countless structures and forests. Fighting wildfires is extremely complex. It is difficult to observe the true state of fires due to…

Artificial Intelligence · Computer Science 2020-10-16 Tina Diao , Samriddhi Singla , Ayan Mukhopadhyay , Ahmed Eldawy , Ross Shachter , Mykel Kochenderfer

Natural hazard risk management is a demanding interdisciplinary task. It requires domain knowledge, integration of robust computational methods, and effective use of complex datasets. However, existing solutions tend to focus on specific…

Optimization and Control · Mathematics 2024-07-11 Cristobal Pais , Minho Kim , John Radke , Marta C. Gonzalez

Given the increasing prevalence of wildland fires in the Western US, there is a critical need to develop tools to understand and accurately predict burn severity. We develop a machine learning model to predict post-fire burn severity using…

Community resilience in the face of natural hazards relies on a community's potential to bounce back. A failure to integrate equity into resilience considerations results in unequal recovery and disproportionate impacts on vulnerable…

Machine Learning · Statistics 2022-02-08 Ali Nejat , Laura Solitare , Edward Pettitt , Hamed Mohsenian-Rad
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