Daily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands

doi:10.3832/ifor3623-014

Daily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands

Aleida Yadira Vilchis-Francés^(1-2), Carlos Díaz-Delgado^(1-2) , Rocío Becerril Piña^(1-2), Carlos Alberto Mastachi Loza⁽¹⁾, Miguel Ángel Gómez-Albores⁽¹⁾, Khalidou M Bâ⁽¹⁾

iForest - Biogeosciences and Forestry, Volume 14, Issue 5, Pages 437-446 (2021)
doi: https://doi.org/10.3832/ifor3623-014
Published: Sep 28, 2021 - Copyright © 2021 SISEF

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We analyzed the behavior of forest fires for daily prediction purposes in one of the regions with the highest fire incidence in Mexico. The main objective was to build logistic regression models (LRMs) for daily prediction of forest fire ignition based on meteorological drought indices. We built 252 LRMs for seven types of vegetation cover of greater representativeness and interest for the study area. Three dynamic variables were considered to estimate daily dryness in combustible fuels based on the effective drought index and the standardized precipitation-evapotranspiration index. Additionally, two weather data sources were included in drought indices: conventional weather stations (CWS) and automatic weather stations (AWS). Prediction efficiency assessment for LRMs was done through the relative operating characteristic (ROC) and model precision efficiency (MPE). The results show that LRMs using data from CWS performed relatively better than those based on data from AWS, as the former data sources have higher spatial density and thus generate predictions with higher accuracy (ROC ≥ 0.700, MPE ≥ 0.934). For both data sources, the use of standardized precipitation-evapotranspiration index as a fuel dryness estimator is recommended, as it reflects an atmospheric moisture balance between precipitation and reference evapotranspiration (ROC ≥ 0.734, MPE = 1). Such predictive models can be used as inputs in early warning systems for forest fire prevention or mitigation.

Keywords

Logistic Regression, Effective Drought Index, Standardized Precipitation-Evapotranspiration Index, Conventional Weather Stations, Automatic Weather Stations

Authors’ address

(1)

0000-0001-8637-2945

0000-0001-9516-1170
0000-0002-6313-9187
0000-0003-1710-5653
Instituto Interamericano de Tecnología y Ciencias del Agua, Universidad Autónoma del Estado de México - IITCA/UAEMex (México)

(2)

0000-0001-8637-2945

Red Interinstitucional e Interdisciplinaria de Investigación, Consulta y Coordinación Científica para la Recuperación de la Cuenca, Lerma-Chapala-Santiago-IITCA-UAEMex, Red Lerma (México)

Corresponding author

Carlos Díaz-Delgado
cdiazd@uaemex.mx

Citation

Vilchis-Francés AY, Díaz-Delgado C, Becerril Piña R, Mastachi Loza CA, Gómez-Albores MÁ, Bâ KM (2021). Daily prediction modeling of forest fire ignition using meteorological drought indices in the Mexican highlands. iForest 14: 437-446. - doi: 10.3832/ifor3623-014

Academic Editor

Davide Ascoli

Paper history

Received: Aug 11, 2020
Accepted: Jul 28, 2021

First online: Sep 28, 2021
Publication Date: Oct 31, 2021
Publication Time: 2.07 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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