Modeling and forecasting MODIS-based Fire Potential Index on a pixel basis using time series models

Huesca Martínez, Margarita, Litago Lavilla, Jesús Javier ORCID: https://orcid.org/0000-0003-2088-7991, Merino de Miguel, Silvia ORCID: https://orcid.org/0000-0002-4764-5311, Cicuéndez López-Ocaña, Víctor Manuel ORCID: https://orcid.org/0000-0002-9934-0472 and Palacios Orueta, Alicia ORCID: https://orcid.org/0000-0002-1248-8336 (2014). Modeling and forecasting MODIS-based Fire Potential Index on a pixel basis using time series models. "International Journal of Applied Earth Observation and Geoinformation", v. 26 (n. 1); pp. 363-376. ISSN 03032434. https://doi.org/10.1016/j.jag.2013.09.003.

Descripción

Título: Modeling and forecasting MODIS-based Fire Potential Index on a pixel basis using time series models
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: International Journal of Applied Earth Observation and Geoinformation
Fecha: 1 Febrero 2014
ISSN: 03032434
Volumen: 26
Número: 1
Materias:
Palabras Clave Informales: Areas; Autoregressive Models; Climate; Ecosystems; Greenness; MODIS; Productivity; Rainfall; Satellite; Seasonality; Time Series Analysis; Trends; Variables
Escuela: E.T.S.I. Montes, Forestal y del Medio Natural (UPM)
Departamento: Ingeniería Agroforestal
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The aim of this research was to model and forecast MODIS-based Fire Potential Index (FPI), implemented with Normalized Difference Water Index (NDWI), as a proxy of forest fire risk, in Navarre (Spain) on a pixel basis using time series models with a forecasting horizon of one year.
We forecast FPINDWI for 2009 based on time series from 2001 to 2008. In the modeling process, the Box and Jenkins methodology was applied in two consecutive stages. First, several generic models based on average FPINDWI time series from different fuel type-ecoregion combinations were developed. In a second stage, the generic models were implemented at the pixel level for the entire study region. The usefulness of the proposed autoregressive (AR) model, using the original data and introducing significant seasonal AR parameters, was demonstrated.
Results show that 93.18% of the estimated models (EMs) are highly accurate and present good forecasting ability, precisely reproducing the original FPINDWI, dynamics. Best results were found in the Mediterranean areas dominated by grasslands; slightly lower accuracies were found in the temperate and alpine regions, and especially in the transition areas between them and the Mediterranean region. (C) 2013 Elsevier B.V. All rights reserved.

Proyectos asociados

Tipo
Código
Acrónimo
Responsable
Título
Gobierno de España
AGL-2010-17505
Sin especificar
Sin especificar
Sin especificar

Más información

ID de Registro: 87634
Identificador DC: https://oa.upm.es/87634/
Identificador OAI: oai:oa.upm.es:87634
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/5489655
Identificador DOI: 10.1016/j.jag.2013.09.003
URL Oficial: https://www.sciencedirect.com/science/article/pii/...
Depositado por: iMarina Portal Científico
Depositado el: 01 Feb 2025 19:39
Ultima Modificación: 01 Feb 2025 19:39