Anticipando el riesgo de fuego

M. Huesca Martinez; Alicia Palacios-Orueta; Javier Litago; Silvia Merino-de-Miguel; Jose  Roman  Ortiz; Victor Cicuendez; Jesus Maqueda Bueno

Anticipando el riesgo de fuego

Translated title of the contribution: Pre-empting fire risk

M. Huesca Martinez, Alicia Palacios-Orueta, Javier Litago, Silvia Merino-de-Miguel, Jose Roman Ortiz, Victor Cicuendez, Jesus Maqueda Bueno

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Abstract

This study develops specific models for estimating and forecasting fire risk based on a combination of time series analysis and remote sensing data. The risk indices used in this procedure are the FPINDWI and the FPINDVI, which differ in terms of the vegetation index used in their calculation, NDVI or NDWI. The FPI (Fire Potential Index) pools meteorological data with information from remote sensing images. Time series analysis has unearthed dynamic patterns in fire behaviour during the study period 2000-2009. From the time series for the period 2000-2008, specific forecast models were developed for the two indices by «fuel type-bioclimatic region». The results show a good fit between the original FPINDWI data and the forecasts for 2009. The study also shows that the FPINDWI’s risk forecasting accuracy is better than the FPINDVI’s, especially for the ecosystems of the north of the study region.

Translated title of the contribution	Pre-empting fire risk
Original language	Spanish
Pages (from-to)	1-15
Number of pages	15
Journal	Seguridad y medio ambiente
Volume	125
Publication status	Published - 2012
Externally published	Yes

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ITC-CV

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title = "Anticipando el riesgo de fuego",

abstract = "This study develops specific models for estimating and forecasting fire risk based on a combination of time series analysis and remote sensing data. The risk indices used in this procedure are the FPINDWI and the FPINDVI, which differ in terms of the vegetation index used in their calculation, NDVI or NDWI. The FPI (Fire Potential Index) pools meteorological data with information from remote sensing images. Time series analysis has unearthed dynamic patterns in fire behaviour during the study period 2000-2009. From the time series for the period 2000-2008, specific forecast models were developed for the two indices by «fuel type-bioclimatic region». The results show a good fit between the original FPINDWI data and the forecasts for 2009. The study also shows that the FPINDWI{\textquoteright}s risk forecasting accuracy is better than the FPINDVI{\textquoteright}s, especially for the ecosystems of the north of the study region.",

keywords = "ITC-CV",

author = "{Huesca Martinez}, M. and Alicia Palacios-Orueta and Javier Litago and Silvia Merino-de-Miguel and {Roman Ortiz}, Jose and Victor Cicuendez and {Maqueda Bueno}, Jesus",

year = "2012",

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TY - JOUR

T1 - Anticipando el riesgo de fuego

AU - Huesca Martinez, M.

AU - Palacios-Orueta, Alicia

AU - Litago, Javier

AU - Merino-de-Miguel, Silvia

AU - Roman Ortiz, Jose

AU - Cicuendez, Victor

AU - Maqueda Bueno, Jesus

PY - 2012

Y1 - 2012

N2 - This study develops specific models for estimating and forecasting fire risk based on a combination of time series analysis and remote sensing data. The risk indices used in this procedure are the FPINDWI and the FPINDVI, which differ in terms of the vegetation index used in their calculation, NDVI or NDWI. The FPI (Fire Potential Index) pools meteorological data with information from remote sensing images. Time series analysis has unearthed dynamic patterns in fire behaviour during the study period 2000-2009. From the time series for the period 2000-2008, specific forecast models were developed for the two indices by «fuel type-bioclimatic region». The results show a good fit between the original FPINDWI data and the forecasts for 2009. The study also shows that the FPINDWI’s risk forecasting accuracy is better than the FPINDVI’s, especially for the ecosystems of the north of the study region.

AB - This study develops specific models for estimating and forecasting fire risk based on a combination of time series analysis and remote sensing data. The risk indices used in this procedure are the FPINDWI and the FPINDVI, which differ in terms of the vegetation index used in their calculation, NDVI or NDWI. The FPI (Fire Potential Index) pools meteorological data with information from remote sensing images. Time series analysis has unearthed dynamic patterns in fire behaviour during the study period 2000-2009. From the time series for the period 2000-2008, specific forecast models were developed for the two indices by «fuel type-bioclimatic region». The results show a good fit between the original FPINDWI data and the forecasts for 2009. The study also shows that the FPINDWI’s risk forecasting accuracy is better than the FPINDVI’s, especially for the ecosystems of the north of the study region.

KW - ITC-CV

M3 - Article

VL - 125

SP - 1

EP - 15

JO - Seguridad y medio ambiente

JF - Seguridad y medio ambiente

ER -

Anticipando el riesgo de fuego

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