Geomatics, Natural Hazards and Risk

Advancing our Understanding of Wildfires: Mapping, Modeling, and Impact Assessment

Wildfires pose escalating threats to human health, infrastructure, and natural systems. In fire-prone regions, even a single wildfire event can result in economic losses exceeding several billion dollars, including damages to property, infrastructure, ecosystems, and public health.

As wildfires become more frequent, more intense, and threaten larger and larger areas in many parts of the world, accurate mapping and modelling have never been more critical. Improved monitoring, understanding, and modeling of wildfires will support emergency response, land-use management, and the development of adaptive, data-driven systems to reduce wildfire risk and strengthen the resilience of both human and natural systems.

Leveraging remote sensing technologies—including satellite and UAV-based observations—researchers can monitor fuel dynamics, active fires, burn scars, and vegetation recovery. Ground-based observations, such as fuel moisture sensors, flux towers, and agency records, provide complementary data to remote sensing, enabling deeper insights into fire mechanisms and fire impacts. In parallel, machine learning methods are increasingly used to enhance fire behavior forecasting, risk assessment, and post-fire impact analysis. This topic focuses on using remote sensing, ground-based observations, and artificial intelligence to improve fire early warning, understanding of fire mechanisms, and quantification of fire impacts on natural and human systems.

This Article Collection brings together cutting-edge research on how we detect, model, and understand the dynamics and impacts of wildfires at different scales. It will focus on advances in wildfire science, highlighting innovations in mapping, modeling, and impact assessment of wildfires. Subtopics include remote sensing of fires, machine learning for fire modelling, and quantification of wildfire impacts on air and water quality, ecosystem dynamics, and human systems. Emphasis will be placed on interdisciplinary studies that combine AI, remote sensing, and ground data to improve fire sciences. We invite Research papers, Reviews, Technical Papers and Data notes that advance scientific understanding or offer innovative applications.

Article Collection Guest Advisors

Fa Li is a Postdoctoral Scholar in the Department of Earth System Science at Stanford University and an incoming Assistant Professor at the University of Texas at Austin. His research focuses on wildfires, ecosystem biophysics and biogeochemistry, and fire–ecosystem–human interactions. He integrates data-driven approaches (e.g., physically interpretable AI and causal inference), process-based terrestrial biosphere and Earth system models, and large-scale datasets (e.g., remote sensing and in-situ measurements) to advance understanding of the fundamental processes that shape the resistance and resilience of socio-ecological systems.

Huilin Huang is an Assistant Professor in the Department of Environmental Sciences at the University of Virginia. Her research advances wildfire science by examining fire-ecosystem-atmosphere interactions and developing improved models of fire behavior and impacts. She is particularly interested in enhancing fire representation in Earth system and ecological models by integrating insights from remote sensing and field observations. She also works on advancing fire spread modeling through high-performance computation and new theoretical frameworks.

Yang Chen is an Associate Researcher in the Department of Earth System Science at the University of California, Irvine. His work spans multiple components of the Earth and climate system, focusing on interactions across the atmosphere, ocean, and land. He specializes in the remote sensing of wildfires, the links between wildfires and climate, and the impacts of fires on air quality and terrestrial ecosystems.

Kunxiaojia Yuan is an Assistant Professor in the Department of Earth and Atmospheric Sciences at the University of Houston. Her research investigates how ecosystems interact with climate dynamics and disturbances (e.g., wildfire, and land cover change). She integrates innovative AI approaches with process-based modeling to advance wildfire prediction and uncover the ecological impacts of wildfire on ecosystems.

Submission Information

­­All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisor for this Collection will not be handling the manuscripts (unless they are an Editorial Board member).

Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is 31 July 2026.

Please contact T&F Commissioning Editor Alex Johnson at [email protected] for more information and/or discount codes relating to this Article Collection.

lease be sure to select the appropriate Article Collection from the drop-down menu in the submission system.

The Guest Advisors for this Article Collection have declared no conflict of interest in preparing this Article Collection.