Abstract
The paper aims to present the results obtained in the development of a system allowing for the detection and monitoring of forest fires and the continuous comparison of their intensity when several events occur simultaneously—a common occurrence in European Mediterranean countries during the summer season. The system, called SFIDE (Satellite FIre DEtection), exploits a geostationary satellite sensor (SEVIRI, Spinning Enhanced Visible and InfraRed Imager, on board of MSG, Meteosat Second Generation, satellite series). The algorithm was developed several years ago in the framework of a project (SIGRI) funded by the Italian Space Agency (ASI). This algorithm has been completely reviewed in order to enhance its efficiency by reducing false alarms rate preserving a high sensitivity. Due to the very low spatial resolution of SEVIRI images (4 × 4 km2 at Mediterranean latitude) the sensitivity of the algorithm should be very high to detect even small fires. The improvement of the algorithm has been obtained by: introducing the sun elevation angle in the computation of the preliminary thresholds to identify potential thermal anomalies (hot spots), introducing a contextual analysis in the detection of clouds and in the detection of night-time fires. The results of the algorithm have been validated in the Sardinia region by using ground true data provided by the regional Corpo Forestale e di Vigilanza Ambientale (CFVA). A significant reduction of the commission error (less than 10%) has been obtained with respect to the previous version of the algorithm and also with respect to fire-detection algorithms based on low earth orbit satellites.
Highlights
Every year, annual reports highlight the extent of the forest fires phenomenon in the European Union, where more than half a million ha of forests burn in about 65,000 fires (Figure 1) [1,2]
Calle proposes an algorithm capable of detecting fire with a minimum dimension of 0.7 ha on the Iberian land; Laneve shows a process for real-time coverage in Mediterranean area; Roberts and Wooster propose an algorithm in which false detection is less than 4% of observed fires; lastly, Amraoui proposes an algorithm for live coverage and combusted area rates on Africa
The main purpose of this paper is to show the utility of geostationary systems (MSG/SEVIRI) for fire-detection, focusing on fire occurrences on the Sardinian island, characterized by a non-homogeneous coverage (that is, the coexistence of urban settlements, infrastructure networks and vegetated areas in a complex, dense and intricate patchwork) and high anthropization, issues neglected by current literature
Summary
Annual reports highlight the extent of the forest fires phenomenon in the European Union, where more than half a million ha of forests burn in about 65,000 fires (Figure 1) [1,2]. In Italy, the amount of wildland and forest areas that burns each year is, on average, 50,000 ha, and this phenomenon is relevant in regions such as Sardinia, where, from 1995 to 2009, an area of 16,600 ha per year burnt, and over 90% of these fires were human-induced [3] For this reason, the adoption of a system capable of detecting as early as possible the trigger of new fires would considerably reduce environmental, material and social damage [4]. The main purpose of this paper is to show the utility of geostationary systems (MSG/SEVIRI) for fire-detection, focusing on fire occurrences on the Sardinian island, characterized by a non-homogeneous coverage (that is, the coexistence of urban settlements, infrastructure networks and vegetated areas (forest, agricultural and uncultivated areas) in a complex, dense and intricate patchwork) and high anthropization, issues neglected by current literature. The paper is organized as follows: Section 2.1 describes exploited data and method for real time coverage, Section 2.2 describes SFIDE algorithm; Section 3 shows the results achieved by comparing hot spots detected by SFIDE, ground data provided by forest rangers CFVA (Corpo Forestale e di Vigilanza Ambientale) and hot spots detected by low orbit based fire-detection system
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