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

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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.

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