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Dear Colleagues,

The increasing risk of wildfire resulting from climate change has demanded an increase in information to support mitigation, response, and recovery activities by fire management agencies. Climate change has increased the risk of fires in nature, necessitating more efforts in emergency management. Forest fires are among the most devastating natural disasters, affecting millions of people and ecosystems worldwide. They endanger human health, biodiversity, climate change, and socioeconomic progress.

Remote sensing is a powerful tool for preventing, managing, and mitigating the effects of forest fires, and it is extremely useful in forest fire management. Remote sensing can be used to detect fires, monitor interventions, and for post-fire monitoring. Remote sensing can also provide information on the occurrence, extent, intensity, and severity of fires, as well as post-fire consequences such as vegetation recovery, soil erosion, and carbon emissions. Identifying these elements can help local governments in better management. This Special Issue aims to collect manuscripts that highlight recent progress and advances of remote sensing-based approaches to improve understanding of fire and emergency management.

Prof. Dr. Ágoston Restás
Guest Editor

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Keywords

forest fire
remote sensing
emergency management
risk assessment
fire montioring

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Research

24 pages, 5702 KiB

Open AccessArticle

Progress and Limitations in the Satellite-Based Estimate of Burnt Areas

by Giovanni Laneve, Marco Di Fonzo, Valerio Pampanoni and Ramon Bueno Morles

Remote Sens. 2024, 16(1), 42; https://0-doi-org.brum.beds.ac.uk/10.3390/rs16010042 - 21 Dec 2023

Viewed by 682

Abstract

The detection of burnt areas from satellite imagery is one of the most straightforward and useful applications of satellite remote sensing. In general, the approach relies on a change detection analysis applied on pre- and post-event images. This change detection analysis usually is carried out by comparing the values of specific spectral indices such as: NBR (normalised burn ratio), BAI (burn area index), MIRBI (mid-infrared burn index). However, some potential sources of error arise, particularly when near-real-time automated approaches are adopted. An automated approach is mandatory when the burnt area monitoring should operate systematically on a given area of large size (country). Potential sources of errors include but are not limited to clouds on the pre- or post-event images, clouds or topographic shadows, agricultural practices, image pixel size, level of damage, etc. Some authors have already noted differences between global databases of burnt areas based on satellite images. Sources of errors could be related to the spatial resolution of the images used, the land-cover mask adopted to avoid false alarms, and the quality of the cloud and shadow masks. This paper aims to compare different burnt areas datasets (EFFIS, ESACCI, Copernicus, FIRMS, etc.) with the objective to analyse their differences. The comparison is restricted to the Italian territory. Furthermore, the paper aims to identify the degree of approximation of these satellite-based datasets by relying on ground survey data as ground truth. To do so, ground survey data provided by CUFA (Comando Unità Forestali, Ambientali e Agroalimentari Carabinieri) and CFVA (Corpo Forestale e Vigilanza Ambientale Sardegna) were used. The results confirm the existence of significant differences between the datasets. The subsequent comparison with the ground surveys, which was conducted while also taking into account their own approximations, allowed us to identify the accuracy of the satellite-based datasets. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Fire and Emergency Management)

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