Citation

Zhang Z, Li J, Yu S, Zhao J, Zhang Z, Li J, Yu S, Zhao J. Int. J. Wildland Fire 2021; 30(10): 763-775.

Copyright

(Copyright © 2021, International Association of Wildland Fire, Fire Research Institute, Publisher CSIRO Publishing)

DOI

10.1071/WF20125

PMID

unavailable

Abstract

Fires can have an enormous impact on grassland systems, affecting their ecology as well as their economic productivity. As most grassland fires are caused by human activities, understanding the relationship between anthropogenic activities that cause fires and where fire ignitions occur is essential in determining where grassland fires pose the greatest risk. Any potential model to predict the spatial distribution and intensity of anthropogenic activities that cause grassland fire ignition needs to take into account the size of residential areas, roads and area of land that is cultivated. The spatial accessibility of human activities that cause grassland fire ignitions was predicted by the model to represent the ability of human driving factors that influence the occurrence of grassland fire ignitions. An index of spatial accessibility of anthropogenic fire ignition sources was overlapped with artificially generated neural networks. Within the index, five categories were created to adequately assess the level of ignition risk to grassland fires: extremely low, low, medium, high and extremely high. The percentages of actual fires in each ignition risk zone from low to high were 2.94%, 18.82%, 20.01%, 22.35% and 35.88%. This methodology provides new insight into how human factors affect the occurrence of wildland fire.

Language: en