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Article

Assessment of Interventions in Fuel Management Zones Using Remote Sensing

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Departamento de Informática da Faculdade de Ciências e Tecnologia and NOVA LINCS, Universidade Nova de Lisboa, Largo da Torre, 2825-149 Caparica, Portugal
2
ALGORITMI Research Centre, University of Minho, Campus de Azurém, 4800-058 Guimarães, Portugal
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(9), 533; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090533
Received: 8 July 2020 / Revised: 14 August 2020 / Accepted: 29 August 2020 / Published: 7 September 2020
Every year, wildfires strike the Portuguese territory and are a concern for public entities and the population. To prevent a wildfire progression and minimize its impact, Fuel Management Zones (FMZs) have been stipulated, by law, around buildings, settlements, along national roads, and other infrastructures. FMZs require monitoring of the vegetation condition to promptly proceed with the maintenance and cleaning of these zones. To improve FMZ monitoring, this paper proposes the use of satellite images, such as the Sentinel-1 and Sentinel-2, along with vegetation indices and extracted temporal characteristics (max, min, mean and standard deviation) associated with the vegetation within and outside the FMZs and to determine if they were treated. These characteristics feed machine-learning algorithms, such as XGBoost, Support Vector Machines, K-nearest neighbors and Random Forest. The results show that it is possible to detect an intervention in an FMZ with high accuracy, namely with an F1-score ranging from 90% up to 94% and a Kappa ranging from 0.80 up to 0.89. View Full-Text
Keywords: remote sensing; time series; Sentinel-2; Sentinel-1; Fuel Management Zones; machine learning remote sensing; time series; Sentinel-2; Sentinel-1; Fuel Management Zones; machine learning
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MDPI and ACS Style

Afonso, R.; Neves, A.; Viegas Damásio, C.; Moura Pires, J.; Birra, F.; Santos, M.Y. Assessment of Interventions in Fuel Management Zones Using Remote Sensing. ISPRS Int. J. Geo-Inf. 2020, 9, 533. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090533

AMA Style

Afonso R, Neves A, Viegas Damásio C, Moura Pires J, Birra F, Santos MY. Assessment of Interventions in Fuel Management Zones Using Remote Sensing. ISPRS International Journal of Geo-Information. 2020; 9(9):533. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090533

Chicago/Turabian Style

Afonso, Ricardo, André Neves, Carlos Viegas Damásio, João Moura Pires, Fernando Birra, and Maribel Y. Santos 2020. "Assessment of Interventions in Fuel Management Zones Using Remote Sensing" ISPRS International Journal of Geo-Information 9, no. 9: 533. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9090533

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