New Advances in Spatial Analysis of Wildfire Planning

A special issue of Fire (ISSN 2571-6255).

Deadline for manuscript submissions: 31 May 2024 | Viewed by 2211

Special Issue Editors


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Guest Editor
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
Interests: bird migration; movement ecology; animal tracking; wildlife conservation; earth observation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Institute for Environmental Studies of Japan, Tsukuba, Japan
Interests: spatial analysis; environmental monitoring; satellite image analysis; air pollution monitoring; geospatial science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wildfire is a significant global challenge, affecting not only the natural environment but also human life and infrastructure. As a result, there is a critical need for new advances in spatial analysis techniques to better understand the patterns and processes of wildfires and improve our ability to manage and respond to them. This Special Issue seeks to bring together the latest research and developments in the spatial analysis of wildfires. We welcome original research articles, reviews, and perspectives that address advances in spatial analysis techniques, such as grassland and forestland management, remote sensing, fuel management, big data analytics, high-resolution imagery, crowdsourcing, and spatial statistics.

Papers cover a wide range of topics of interest include but are not limited to:

  • Fire-safe landscaping;
  • Planned fires;
  • Fuel management;
  • Fire and resource management planning;
  • Postfire soil burn severity mapping;
  • Machine learning and big data analytics in wildfire analysis;
  • GIS-based analysis of wildfire patterns and processes;
  • High-resolution imagery and LiDAR for wildfire mapping and modeling;
  • Crowdsourcing and citizen science in wildfire data collection and analysis;
  • Spatial statistics in wildfire research and management;
  • Identification of underlying factors that contribute to wildfire occurrences;
  • Mapping fire extent and severity;
  • Tracking fire behavior and movement;
  • Early warning systems for wildfires;
  • Wildfire risk assessment and management;
  • Decision support systems for firefighting and evacuation strategies;
  • Spatial‒temporal analysis of wildfire patterns and processes;
  • Impacts of wildfires on ecosystems and biodiversity.

Manuscripts will be peer-reviewed and should follow the journal's formatting guidelines. We also encourage submissions of papers that demonstrate interdisciplinary collaboration and present solutions that integrate social, ecological, and economic factors.

Please indicate your interest in contributing to this special issue by emailing the guest editors [insert names and email addresses] with a tentative title and a brief abstract of your proposed paper.

We look forward to your contribution to this Special Issue and to advancing the field of wildfire research and management through new advances in spatial analysis techniques.

You may choose our Joint Special Issue in Land.

Dr. Kunpeng Yi
Dr. Shuai Yin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fire is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

20 pages, 2875 KiB  
Article
YOLO-Based Models for Smoke and Wildfire Detection in Ground and Aerial Images
by Leon Augusto Okida Gonçalves, Rafik Ghali and Moulay A. Akhloufi
Fire 2024, 7(4), 140; https://doi.org/10.3390/fire7040140 - 14 Apr 2024
Viewed by 516
Abstract
Wildland fires negatively impact forest biodiversity and human lives. They also spread very rapidly. Early detection of smoke and fires plays a crucial role in improving the efficiency of firefighting operations. Deep learning techniques are used to detect fires and smoke. However, the [...] Read more.
Wildland fires negatively impact forest biodiversity and human lives. They also spread very rapidly. Early detection of smoke and fires plays a crucial role in improving the efficiency of firefighting operations. Deep learning techniques are used to detect fires and smoke. However, the different shapes, sizes, and colors of smoke and fires make their detection a challenging task. In this paper, recent YOLO-based algorithms are adopted and implemented for detecting and localizing smoke and wildfires within ground and aerial images. Notably, the YOLOv7x model achieved the best performance with an mAP (mean Average Precision) score of 80.40% and fast detection speed, outperforming the baseline models in detecting both smoke and wildfires. YOLOv8s obtained a high mAP of 98.10% in identifying and localizing only wildfire smoke. These models demonstrated their significant potential in handling challenging scenarios, including detecting small fire and smoke areas; varying fire and smoke features such as shape, size, and colors; the complexity of background, which can include diverse terrain, weather conditions, and vegetation; and addressing visual similarities among smoke, fog, and clouds and the the visual resemblances among fire, lighting, and sun glare. Full article
(This article belongs to the Special Issue New Advances in Spatial Analysis of Wildfire Planning)
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20 pages, 3092 KiB  
Article
A Multicriteria Geographic Information System Analysis of Wildfire Susceptibility in the Andean Region: A Case Study in Ibarra, Ecuador
by Paúl Arias-Muñoz, Santiago Cabrera-García and Gabriel Jácome-Aguirre
Fire 2024, 7(3), 81; https://doi.org/10.3390/fire7030081 - 06 Mar 2024
Viewed by 1346
Abstract
The uncontrolled spread of fire can have huge effects on ecosystems. In Ecuador, in 2022, wildfires caused a loss of 6566.66 hectares of vegetation cover. Ibarra is an Andean canton that has also been exposed to wildfires and their effects. The aim of [...] Read more.
The uncontrolled spread of fire can have huge effects on ecosystems. In Ecuador, in 2022, wildfires caused a loss of 6566.66 hectares of vegetation cover. Ibarra is an Andean canton that has also been exposed to wildfires and their effects. The aim of this study was to map wildfire susceptibility in the Ibarra canton. Seven factors that directly affect these fires were examined: precipitation, temperature, water deficit, potential evapotranspiration, slope, proximity to roads, and land cover and land use. The variables were reclassified using Geographic Information Systems and a multicriteria analysis. The results showed that Ibarra has four susceptibility categories: very low, moderate, high, and very high. The more susceptible areas are those considered to have high and very high exposure, occupying 82% of the surface. Consequently, the most susceptible land covers are crops, pastures, shrub vegetation, and forests. Full article
(This article belongs to the Special Issue New Advances in Spatial Analysis of Wildfire Planning)
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