Understanding, Monitoring, and Responses to Wildfires with New Sensors

A special issue of Fire (ISSN 2571-6255). This special issue belongs to the section "Fire Science Models, Remote Sensing, and Data".

Deadline for manuscript submissions: 25 September 2024 | Viewed by 2932

Special Issue Editors


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Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia CNT, Via di Vigna Muarata 605, 00143 Rome, Italy
Interests: wildfires from space; remote sensing; calibration; validation; detection techniques; hyperspectral; thermal; active fire; post fire; air quality; machine learning

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Guest Editor
School of Aerospace Engineering, Sapienza University of Rome, 00138 Rome, Italy
Interests: artificial intelligence; deep learning; active fire temperature retrieval; hot spot detection; on board computing
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Guest Editor
Lab of Forest Management and Remote Sensing, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: forest fires; land-use/land-cover mapping; pre-fire planning and post-fire assessment; remote sensing; GIS; forest management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wildfires are complex phenomena that play an important role in Earth's biogeochemical cycles. Fires are considered, more and more every year, a major hazard, with them affecting the densely populated areas of the world.

Climate change, which we are experiencing with a decrease in rainfall, a change in the number of lightning strikes, and an increase in temperature, directly affects both the number and intensity of wildfires.

Accurate, timely, and regular information on active fires is vital for understanding and early response to the phenomena. Satellite remote sensing has been used for almost sixty years in the detection of active fires.

To date, active fires, fire radiative power, and air quality can be detected, monitored, and estimated on an hourly or daily basis from both geostationary (GOES and MSG–SEVIRI) and polar orbiting (VIIRS–MODIS, Sentinel 3, OMI, and Sentinel 5p) satellites.

Although the spatial resolution of the produced products varies between 1–7 km, the information produced is extremely valuable for monitoring active fires not only globally but also regionally and even nationally.

With new satellites and new-generation multispectral, hyperspectral, thermal, and laser sensors (PRISMA, EnMap, HSUI, SBG, TRISNA, PRISMA2G, CHIME, MAIA, and GEDI), there are numerous new possibilities such as improved spatial resolution (<100 m) and high frequency of observation. The spatial resolution and number of observations are expected to increase even more with the development of CubeSat constellations.

This Special Issue, in addition to original research articles, welcomes case study reports, technical notes, letters, and reviews focusing on, but not limited to, the following:

  • New methods including deep learning and artificial intelligence as well as improved algorithms related to the detection and monitoring of active fires applied to spaceborne data;
  • The synergistic use of data collected by different sensors to improve the detection of active fires and the understanding of fire behavior and rate of spread, thus helping the response time and therefore mitigating the impact of fires;
  • Exploitation of data from high-spatial-resolution sensors to better understand the uncertainties in the detection of active fires.

Dr. Stefania Amici
Dr. Dario Spiller
Dr. Ioannis Gitas
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.

Keywords

  • active fires
  • temperature
  • FRP
  • fire behavior
  • smoke emission
  • fire intensity
  • remote sensing, Earth observation, wildfire impact, deep learning, and AI

Published Papers (1 paper)

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Research

19 pages, 3072 KiB  
Article
Canadian Fire Management Agency Readiness for WildFireSat: Assessment and Strategies for Enhanced Preparedness
by Colin B. McFayden, Emily S. Hope, Den Boychuk, Lynn M. Johnston, Ashlin Richardson, Matthew Coyle, Meghan Sloane, Alan S. Cantin, Joshua M. Johnston and Timothy J. Lynham
Fire 2023, 6(2), 73; https://doi.org/10.3390/fire6020073 - 16 Feb 2023
Cited by 3 | Viewed by 2376
Abstract
Wildfires are worsening in Canada and globally, partly due to climate change. The government of Canada is designing and building WildFireSat, the world’s first purpose-built operational satellite system for wildfire monitoring. It will provide new fire intelligence to support decision-making. It takes time [...] Read more.
Wildfires are worsening in Canada and globally, partly due to climate change. The government of Canada is designing and building WildFireSat, the world’s first purpose-built operational satellite system for wildfire monitoring. It will provide new fire intelligence to support decision-making. It takes time for fire management agencies to use new information: to understand it and its implications, change processes, develop training, and modify computer systems. Preparing for the system’s prelaunch will allow agencies to benefit more rapidly from the new information. We present (1) an assessment of the readiness of 12 Canadian fire management agencies to integrate WildFireSat information and (2) guidance for reducing readiness gaps. We used survey and other data to score readiness indicators for three readiness components: understanding, organization, and information technology. We weighted the influence of each indicator score on each component. We modelled scoring and weighting uncertainties and used Monte Carlo simulation to generate distributions of aggregated agency readiness. The results indicated that most agencies have a moderate level of readiness while others have a higher level of readiness. Cluster analysis was used to group agencies by similarity in multiple dimensions. Strategies for increasing readiness are highlighted. This identifies opportunities for agencies and the WildFireSat team to collaborate on enhancing readiness for the forthcoming WildFireSat data products. Full article
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