Spatial modeling of forest fires in Mexico: an integration of two data sources

Abstract

© 2017, Universidad Austral de Chile. All rights reserved. Forest fires are a cause of global concern, which requires generating knowledge on their spatial behavior. By hypothesizing that the spatial pattern of forest fires across Mexico is randomly distributed, this study aimed at making an analysis of the distribution of forest fires (2005-2015) using remote sensing information and field data collected by CONAFOR (National Forest Commission) and MODIS (Moderate-Resolution Imaging Spectroradiometer). The study compared both sources of information through the G-statistic test that identified clustering patterns. The “hot spots” analysis identified clustered areas with significant values in both data sources. These zones were extended through Sierra Madre Occidental, Península de Yucatán, northern Sierra Madre Oriental and Península de Baja California. The highly coincidental clusters were found in the central-western region along the Eje Neovolcánico, as well as in a small part of Sierra Madre del Sur. The analysis of spatial correlation determined that both sources of information complement each other, enhancing their scope. It is concluded that forest fires in Mexico follow a spatial clustering trend.