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Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)

Wildfire is a major threat to the environment, and this threat is aggravated by different climatic and socioeconomic factors. The availability of detailed, reliable mapping and periodic and immediate updates makes wildfire prevention and extinction work more effective. An analyst protocol has been g...

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Autores principales: Sánchez Sánchez, Yolanda, Martínez-Graña, Antonio, Santos Francés, Fernando, Mateos Picado, Marina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876519/
https://www.ncbi.nlm.nih.gov/pubmed/29522460
http://dx.doi.org/10.3390/s18030826
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author Sánchez Sánchez, Yolanda
Martínez-Graña, Antonio
Santos Francés, Fernando
Mateos Picado, Marina
author_facet Sánchez Sánchez, Yolanda
Martínez-Graña, Antonio
Santos Francés, Fernando
Mateos Picado, Marina
author_sort Sánchez Sánchez, Yolanda
collection PubMed
description Wildfire is a major threat to the environment, and this threat is aggravated by different climatic and socioeconomic factors. The availability of detailed, reliable mapping and periodic and immediate updates makes wildfire prevention and extinction work more effective. An analyst protocol has been generated that allows the precise updating of high-resolution thematic maps. For this protocol, images obtained through the Sentinel 2A satellite, with a return time of five days, have been merged with Light Detection and Ranging (LiDAR) data with a density of 0.5 points/m(2) in order to obtain vegetation mapping with an accuracy of 88% (kappa = 0.86), which is then extrapolated to fuel model mapping through a decision tree. This process, which is fast and reliable, serves as a cartographic base for the later calculation of ignition-probability mapping. The generated cartography is a fundamental tool to be used in the decision making involved in the planning of preventive silvicultural treatments, extinguishing media distribution, infrastructure construction, etc.
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spelling pubmed-58765192018-04-09 Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain) Sánchez Sánchez, Yolanda Martínez-Graña, Antonio Santos Francés, Fernando Mateos Picado, Marina Sensors (Basel) Article Wildfire is a major threat to the environment, and this threat is aggravated by different climatic and socioeconomic factors. The availability of detailed, reliable mapping and periodic and immediate updates makes wildfire prevention and extinction work more effective. An analyst protocol has been generated that allows the precise updating of high-resolution thematic maps. For this protocol, images obtained through the Sentinel 2A satellite, with a return time of five days, have been merged with Light Detection and Ranging (LiDAR) data with a density of 0.5 points/m(2) in order to obtain vegetation mapping with an accuracy of 88% (kappa = 0.86), which is then extrapolated to fuel model mapping through a decision tree. This process, which is fast and reliable, serves as a cartographic base for the later calculation of ignition-probability mapping. The generated cartography is a fundamental tool to be used in the decision making involved in the planning of preventive silvicultural treatments, extinguishing media distribution, infrastructure construction, etc. MDPI 2018-03-09 /pmc/articles/PMC5876519/ /pubmed/29522460 http://dx.doi.org/10.3390/s18030826 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sánchez Sánchez, Yolanda
Martínez-Graña, Antonio
Santos Francés, Fernando
Mateos Picado, Marina
Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)
title Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)
title_full Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)
title_fullStr Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)
title_full_unstemmed Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)
title_short Mapping Wildfire Ignition Probability Using Sentinel 2 and LiDAR (Jerte Valley, Cáceres, Spain)
title_sort mapping wildfire ignition probability using sentinel 2 and lidar (jerte valley, cáceres, spain)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876519/
https://www.ncbi.nlm.nih.gov/pubmed/29522460
http://dx.doi.org/10.3390/s18030826
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