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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...

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Autores principales: Bajocco, Sofia, Dragoz, Eleni, Gitas, Ioannis, Smiraglia, Daniela, Salvati, Luca, Ricotta, Carlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
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.
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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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