Advances in Spectral Imagery and Methods for Fire and Smoke Detection

Dear Colleagues,

The increasing frequency and intensity of wildfires globally have underscored the critical need for advanced detection and monitoring systems. According to the latest WMO State of the Climate Update, 2024 is on track to be the warmest on record, with global mean surface air temperatures of 1.54 °C above pre-industrial levels. The report highlights that the past decade has also been the warmest on record, with extreme weather events, including wildfires, causing massive economic and human losses. These fires have led to significant CO₂ emissions, severe air quality issues, and widespread evacuations. This Special Issue aims to highlight the latest scientific advancements in the field of early fire and smoke detection, emphasizing the importance of innovative methodologies and technologies in mitigating the devastating impacts of wildfires and the climate change-accelerating impacts of aerosols.

This Special Issue seeks to bring together the current state of knowledge on spectral imagery (e.g., multi- and hyperspectral imagery) and its applications in fire and smoke detection. By aligning with the journal's scope of promoting interdisciplinary research in remote sensing and environmental monitoring, this issue will provide a platform for showcasing rigorous novel approaches that provide solutions to current challenges. The Remote Sensing journal focuses on the science and application of remote sensing technologies, covering a wide range of topics, including environmental monitoring, disaster management, urban planning, and more. It emphasizes interdisciplinary research and the integration of various remote sensing technologies, such as satellite, UAV, and ground-based sensors. The goal of this issue is to foster collaboration among researchers, practitioners, policymakers, and, ultimately, end-users to enhance our collective understanding and capabilities in wildfire and aerosol management.

We invite submissions on a wide range of topics, including but not limited to the following:

• The development and application of multispectral and hyperspectral imaging for fire detection;
• The integration of thermal imaging with other spectral data for enhanced smoke detection;
• Machine learning and AI models for analyzing spectral imagery in fire and smoke detection;
• Multi-sensor fusion for comprehensive fire detection systems;
• Super-resolution techniques for improving the accuracy and early detection of fire and smoke;
• Integrating ground monitoring and IoT sensors with satellite observations;
• The comparison of thermal versus shortwave detection methods;
• The efficacy of complex (e.g., hyperspectral) data-heavy, deep learning (ML), and heavy computational detection methods versus lightweight (e.g., RGB) methods;
• The development of smoke training datasets for AI models;
• Case studies demonstrating the effectiveness of spectral imagery in real-world fire events;
• Reviews and meta-analyses on current trends and future directions in spectral fire and smoke detection;
• Translating research into actionable remote sensing technologies for fire and/or smoke detection.

Dr. Eriita Jones
Guest Editor

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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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.

• fire detection
• smoke detection
• spectral imagery
• remote sensing
• environmental monitoring and management
• multispectral and hyperspectral imaging
• thermal imaging
• machine learning
• AI models
• super-resolution
• IOT
• wildfires and aerosols