Skip to Main Content
U.S. Forest Service
Caring for the land and serving people

United States Department of Agriculture

Home > Search > Publication Information

  1. Share via EmailShare on FacebookShare on LinkedInShare on Twitter
    Dislike this pubLike this pub
    Author(s): Daniel Jose Vega-Nieva; Maria Guadalupe Nava-Miranda; Eric Calleros-Flores; Pablito Marcelo López-Serrano; Jaime Briseño-Reyes; Carlos López-Sánchez; Jose Javier Corral-Rivas; Eusebio Montiel-Antuna; Maria Isabel Cruz-Lopez; Rainer Ressl; Martin Cuahtle; Ernesto Alvarado-Celestino; Armando González-Cabán; Citlali Cortes-Montaño; Diego Pérez-Salicrup; Enrique Jardel-Pelaez; Enrique Jiménez; Stefano Arellano-Pérez; Juan Gabriel Álvarez-González; Ana Daria. Ruiz-González
    Date: 2019
    Source: Fire Ecology. 15: 28
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Southwest Research Station
    PDF: Download Publication  (4.0 MB)



    Understanding the temporal patterns of fire occurrence and their relationships with fuel dryness is key to sound fire management, especially under increasing global warming. At present, no system for prediction of fire occurrence risk based on fuel dryness conditions is available in Mexico. As part of an ongoing national-scale project, we developed an operational fire risk mapping tool based on satellite and weather information.


    We demonstrated how differing monthly temporal trends in a fuel greenness index, dead ratio (DR), and fire density (FDI) can be clearly differentiated by vegetation type and region for the whole country, using MODIS satellite observations for the period 2003 to 2014. We tested linear and non-linear models, including temporal autocorrelation terms, for prediction of FDI from DR for a total of 28 combinations of vegetation types and regions. In addition, we developed seasonal autoregressive integrated moving average (ARIMA) models for forecasting DR values based on the last observed values. Most ARIMA models showed values of the adjusted coefficient of determination (R2 adj) above 0.7 to 0.8, suggesting potential to forecast fuel dryness and fire occurrence risk conditions. The best fitted models explained more than 70% of the observed FDI variation in the relation between monthly DR and fire density.


    These results suggest that there is potential for the DR index to be incorporated in future fire risk operational tools. However, some vegetation types and regions show lower correlations between DR and observed fire density, suggesting that other variables, such as distance and timing of agricultural burn, deserve attention in future studies.

    Publication Notes

    • You may send email to to request a hard copy of this publication.
    • (Please specify exactly which publication you are requesting and your mailing address.)
    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.


    Vega-Nieva, Daniel Jose; Nava-Miranda, Maria Guadalupe; Calleros-Flores, Eric; López-Serrano, Pablito Marcelo; Briseño-Reyes, Jaime; López-Sánchez, Carlos; Corral-Rivas, Jose Javier; Montiel-Antuna, Eusebio; Cruz-Lopez, Maria Isabel; Ressl, Rainer; Cuahtle, Martin; Alvarado-Celestino, Ernesto; González-Cabán, Armando; Cortes-Montaño, Citlali; Pérez-Salicrup, Diego; Jardel-Pelaez, Enrique; Jiménez, Enrique; Arellano-Pérez, Stefano; Álvarez-González, Juan Gabriel; Ruiz-González, Ana Daria. 2019. Temporal patterns of active fire density and its relationship with a satellite fuel greenness index by vegetation type and region in Mexico during 2003–2014. Fire Ecology. 15: 28.


    Google Scholar


    active fire density, ARIMA, fire occurrence risk, fuel greenness

    Related Search

    XML: View XML
Show More
Show Fewer
Jump to Top of Page