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Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level

Wildland fires are some of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this paper, our overall objective was to study the structural damages due to the 2016 Horse River Fire (HRF) that happened in Fort McMurra...

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Autores principales: Ahmed, M. Razu, Rahaman, Khan Rubayet, Hassan, Quazi K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5981306/
https://www.ncbi.nlm.nih.gov/pubmed/29762504
http://dx.doi.org/10.3390/s18051570
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author Ahmed, M. Razu
Rahaman, Khan Rubayet
Hassan, Quazi K.
author_facet Ahmed, M. Razu
Rahaman, Khan Rubayet
Hassan, Quazi K.
author_sort Ahmed, M. Razu
collection PubMed
description Wildland fires are some of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this paper, our overall objective was to study the structural damages due to the 2016 Horse River Fire (HRF) that happened in Fort McMurray (Alberta, Canada) by employing primarily very high spatial resolution optical satellite data, i.e., WorldView-2. Thus, our activities included the: (i) estimation of the structural damages; and (ii) delineation of the wildland-urban interface (WUI) and its associated buffers at certain intervals, and their utilization in assessing potential risks. Our proposed method of remote sensing-based estimates of the number of structural damages was compared with the ground-based information available from the Planning and Development Recovery Committee Task Force of Regional Municipality of Wood Buffalo (RMWB); and found a strong linear relationship (i.e., r(2) value of 0.97 with a slope of 0.97). Upon delineating the WUI and its associated buffer zones at 10 m, 30 m, 50 m, 70 m and 100 m distances; we found existence of vegetation within the 30 m buffers from the WUI for all of the damaged structures. In addition, we noticed that the relevant authorities had removed vegetation in some areas between 30 m and 70 m buffers from the WUI, which was proven to be effective in order to protect the structures in the adjacent communities. Furthermore, we mapped the wildland fire-induced vulnerable areas upon considering the WUI and its associated buffers. Our analysis revealed that approximately 30% of the areas within the buffer zones of 10 m and 30 m were vulnerable due to the presence of vegetation; in which, approximately 7% were burned during the 2016 HRF event that led the structural damages. Consequently, we suggest to remove the existing vegetation within these critical zones and also monitor the region at a regular interval in order to reduce the wildland fire-induced risk.
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spelling pubmed-59813062018-06-05 Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level Ahmed, M. Razu Rahaman, Khan Rubayet Hassan, Quazi K. Sensors (Basel) Article Wildland fires are some of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this paper, our overall objective was to study the structural damages due to the 2016 Horse River Fire (HRF) that happened in Fort McMurray (Alberta, Canada) by employing primarily very high spatial resolution optical satellite data, i.e., WorldView-2. Thus, our activities included the: (i) estimation of the structural damages; and (ii) delineation of the wildland-urban interface (WUI) and its associated buffers at certain intervals, and their utilization in assessing potential risks. Our proposed method of remote sensing-based estimates of the number of structural damages was compared with the ground-based information available from the Planning and Development Recovery Committee Task Force of Regional Municipality of Wood Buffalo (RMWB); and found a strong linear relationship (i.e., r(2) value of 0.97 with a slope of 0.97). Upon delineating the WUI and its associated buffer zones at 10 m, 30 m, 50 m, 70 m and 100 m distances; we found existence of vegetation within the 30 m buffers from the WUI for all of the damaged structures. In addition, we noticed that the relevant authorities had removed vegetation in some areas between 30 m and 70 m buffers from the WUI, which was proven to be effective in order to protect the structures in the adjacent communities. Furthermore, we mapped the wildland fire-induced vulnerable areas upon considering the WUI and its associated buffers. Our analysis revealed that approximately 30% of the areas within the buffer zones of 10 m and 30 m were vulnerable due to the presence of vegetation; in which, approximately 7% were burned during the 2016 HRF event that led the structural damages. Consequently, we suggest to remove the existing vegetation within these critical zones and also monitor the region at a regular interval in order to reduce the wildland fire-induced risk. MDPI 2018-05-15 /pmc/articles/PMC5981306/ /pubmed/29762504 http://dx.doi.org/10.3390/s18051570 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
Ahmed, M. Razu
Rahaman, Khan Rubayet
Hassan, Quazi K.
Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level
title Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level
title_full Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level
title_fullStr Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level
title_full_unstemmed Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level
title_short Remote Sensing of Wildland Fire-Induced Risk Assessment at the Community Level
title_sort remote sensing of wildland fire-induced risk assessment at the community level
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5981306/
https://www.ncbi.nlm.nih.gov/pubmed/29762504
http://dx.doi.org/10.3390/s18051570
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