Wildfires on the Mongolian Plateau: Identifying Drivers and Spatial Distributions to Predict Wildfire Probability

Abstract

With climate change, significant fluctuations in wildfires have been observed on the Mongolian Plateau. The ability to predict the distribution of wildfires in the context of climate change plays a critical role in wildfire management and ecosystem maintenance. In this paper, Ripley’s K function and a Random Forest (RF) model were applied to analyse the spatial patterns and main influencing factors affecting the occurrence of wildfire on the Mongolian Plateau. The results showed that the wildfires were mainly clustered in space due to the combination of influencing factors. The distance scale is less than 1/2 of the length of the Mongolian Plateau; that is, it does not experience boundary effects in the study area and it meets the requirements of Ripley’s K function. Among the driving factors, the fraction of vegetation coverage (FVC), land use degree (La), elevation, precipitation (pre), wet day frequency (wet), and maximum temperature (tmx) had the greatest influences, while the aspect had the lowest influence. The likelihood of fire was mainly concentrated in the northern, eastern, and southern parts of the Mongolian Plateau and in the border area between the Inner Mongolia Autonomous Region (Inner Mongolia) and Mongolian People’s Republic (Mongolia), and wildfires did not occur or occurred less frequently in the hinterland area. The fitting results of the RF model showed a prediction accuracy exceeding 90%, which indicates that the model has a high ability to predict wildfire occurrences on the Mongolian Plateau. This study can provide a reference for predictions and decision-making related to wildfires on the Mongolian Plateau.

NDVI Indicates Long-Term Dynamics of Vegetation and Its Driving Forces from Climatic and Anthropogenic Factors in Mongolian Plateau

“…The statistical results show that 37.67% of pixels showed significant growth, with only 7.15% of the pixels exhibiting a significant decrease. Vegetation changes on the Mongolian Plateau were impacted by the compounding effects of human activity and climatic factors, such as wildfire and grazing [44,45]. The BFAST method provides functionality to detect stable yet abnormal changes from historical trends in the monthly NDVI.…”

Analysis of the Grassland Fires Effect on Dust Weather in Mongolia Based on Satellite-Derived Data

“…Dust weather was mainly concentrated at the Choibalsan and Khalkhgol stations, potentially due to differences in land use patterns. Mineral resources near Choibalsan station are relatively abundant [45], while a large area of farmland is distributed near Khalkhgol station [43]. Large-scale mining activities and extensive crop cultivation have resulted in damage to surface vegetation and soil loosening, contributing to the occurrence of dust to some extent [46,47].…”

Assessing Land Cover and Ecological Quality Changes in the Forest-Steppe Ecotone of the Greater Khingan Mountains, Northeast China, from Landsat and MODIS Observations from 2000 to 2018

“…However, land cover transformation often has positive or negative impacts on the ecosystem and ecological environment directly or indirectly. When the contribution rate of the land cover changes and improves the ecological environment rather than degrade the ecological environment, the ecological quality improves; otherwise, it declines [54]. In this work, land cover maps were created, and spatiotemporal changes in the NPP and FVC in a 20-year period were analyzed to determine the ecological quality changes in the forest-steppe ecozone of the Greater Khingan Mountains, northeast China.…”