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Article << Previous     |     Next >>   Contents Vol 23(4)

A quantitative study of the proximity of satellite detected active fires to roads and rivers in the Brazilian tropical moist forest biome

Sanath S. Kumar A D , David P. Roy A , Mark A. Cochrane A , Carlos M. Souza Jr B , Chirstopher P. Barber A and L. Boschetti C

A Geographic Information Science Center of Excellence, South Dakota State University, Brookings, SD 57007, USA.
B Instituto do Homem e Meio Ambiente da Amazônia–Imazon, Caixa Postal 5101, Ananindeua, Pará 67, 113-000, Brazil.
C Department of forest, rangeland and fire sciences, College of Natural Resources, University of Idaho, Moscow, ID 83844, USA.
D Corresponding author. Email: sanath.kumar@sdstate.edu

International Journal of Wildland Fire 23(4) 532-543 http://dx.doi.org/10.1071/WF13106
Submitted: 1 July 2013  Accepted: 4 February 2014   Published: 15 May 2014


 
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Abstract

The Brazilian tropical moist forest biome (BTMFB) is experiencing high rates of deforestation and fire. Previous studies indicate that the majority of fires occur close to roads, however they did not consider the network of unofficial roads and navigable rivers, nor inter-state and inter-annual variability. We examine 8 years of Moderate Resolution Imaging Spectroradiometer (MODIS) active fire detections and the cumulative frequency distribution of the distance of each detection to the closest official road, unofficial road, and navigable river bank. Approximately 50 and 95% of all MODIS active fire detections occurred within 1 and 10 km respectively of a road or navigable river. Inter-state and inter-annual variations are discussed and linkages to expansion of the road network are suggested. Comparison of the distance distribution of the MODIS active fire detections and the distance distribution of a 0.5-km spaced geographic grid to the combined roads and navigable river network revealed significant differences for each state and for the BTMFB and indicate that the great majority of fires are anthropogenic. The results provide insights that may be useful for modelling the incidence of fire under future expansion of the Amazonian road network and increased river navigability.



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