Modelling spatial patterns of forest fire occurrence in the Northwestern region of Vietnam

Trang Pham Thanh; Thuan Chu; Bao Tran Quang

doi:10.15625/2615-9783/20366

Author affiliations

Authors

Trang Thanh Pham Faculty of Forest Resources Environmental Management, Vietnam National University of Forestry, Xuan Mai, Chuong My, Hanoi, 100000 Vietnam
Thuan Chu Department of Geography and Planning, University of Saskatchewan, Saskatoon, SK S7N5C8, Canada
Bao Quang Tran Department of Forestry, Ministry of Agriculture and Rural Development, Hanoi, 100000 Vietnam

DOI:

https://doi.org/10.15625/2615-9783/20366

Keywords:

Forest fire, machine learning, MaxEnt, remote sensing, Southeast Asia, tropical forest

Abstract

Forest fires present a significant threat to the tropical forest ecosystem in the northwestern region of Vietnam. Our study aimed to assess the impacts of environmental factors on forest fire occurrence and to map forest fire probability for the whole region. The forest fire occurrence data over the period 2003–2016, environmental factors (climate, fuel condition, topography, and human activity), and the MaxEnt approach were used for this study. The MaxEnt model performed better than the random model (AUC>0.88). Climatic factors (especially climatic seasonality: annual temperature range (bio_07), isothermality (bio_03), and precipitation of warmest quarter (bio_18)) had the highest contribution to the model, followed by population density and elevation. In contrast, fuel condition (Land cover type) had a small contribution to the model. While medium, high, and very high probabilities of forest fire occurred at medium to high elevations (e.g., Dien Bien, Son La, and Lai Chau provinces) throughout southern to northern and western areas, very low and low probability concentrated southeastern areas at lower elevations (mainly in Hoa Bình province). Our results may be helpful references for fire managers and policymakers to establish more effective fire management strategies for the region's forest.

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