Abstract

Frequent and intense anthropogenic fires present meaningful challenges to forest management in the boreal forest of China. Understanding the underlying drivers of human-caused fire occurrence is crucial for making effective and scientifically-based forest fire management plans. In this study, we applied logistic regression (LR) and Random Forests (RF) to identify important biophysical and anthropogenic factors that help to explain the likelihood of anthropogenic fires in the Chinese boreal forest. Results showed that the anthropogenic fires were more likely to occur at areas close to railways and were significantly influenced by forest types. In addition, distance to settlement and distance to road were identified as important predictors for anthropogenic fire occurrence. The model comparison indicated that RF had greater ability than LR to predict forest fires caused by human activity in the Chinese boreal forest. High fire risk zones in the study area were identified based on RF, where we recommend increasing allocation of fire management resources.

Keywords

human-caused fire; driving factors; forest fire; Daxing'an Mountains; ROC curve

Published in

Forests
2016, Volume: 7, number: 11, article number: 250
Publisher: MDPI AG

SLU Authors

• Tigabu, Mulualem

  • Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences
    

Associated SLU-program

Forest


Sustainable Development Goals

SDG15 Life on land
SDG13 Climate action
SDG11 Sustainable cities and communities


UKÄ Subject classification

Forest Science


Publication Identifiers

DOI: https://doi.org/10.3390/f7110250

Permanent link to this page (URI)

https://res.slu.se/id/publ/81148