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Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series
Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MOD...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4379084/ https://www.ncbi.nlm.nih.gov/pubmed/25822505 http://dx.doi.org/10.1371/journal.pone.0119811 |
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author | Bajocco, Sofia Dragoz, Eleni Gitas, Ioannis Smiraglia, Daniela Salvati, Luca Ricotta, Carlo |
author_facet | Bajocco, Sofia Dragoz, Eleni Gitas, Ioannis Smiraglia, Daniela Salvati, Luca Ricotta, Carlo |
author_sort | Bajocco, Sofia |
collection | PubMed |
description | Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000–2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies. |
format | Online Article Text |
id | pubmed-4379084 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43790842015-04-09 Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series Bajocco, Sofia Dragoz, Eleni Gitas, Ioannis Smiraglia, Daniela Salvati, Luca Ricotta, Carlo PLoS One Research Article Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000–2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies. Public Library of Science 2015-03-30 /pmc/articles/PMC4379084/ /pubmed/25822505 http://dx.doi.org/10.1371/journal.pone.0119811 Text en © 2015 Bajocco et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Bajocco, Sofia Dragoz, Eleni Gitas, Ioannis Smiraglia, Daniela Salvati, Luca Ricotta, Carlo Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series |
title | Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series |
title_full | Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series |
title_fullStr | Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series |
title_full_unstemmed | Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series |
title_short | Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series |
title_sort | mapping forest fuels through vegetation phenology: the role of coarse-resolution satellite time-series |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4379084/ https://www.ncbi.nlm.nih.gov/pubmed/25822505 http://dx.doi.org/10.1371/journal.pone.0119811 |
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