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Open AccessArticle

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

by Wu Rihan 1,2, Jianjun Zhao 1,2,*, Hongyan Zhang 1,2, Xiaoyi Guo 1,2, Hong Ying 1,2, Guorong Deng 1,2 and Hui Li 1,2
1
Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
2
Urban Remote Sensing Application Innovation Center, School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(20), 2361; https://doi.org/10.3390/rs11202361
Received: 11 July 2019 / Revised: 23 August 2019 / Accepted: 11 October 2019 / Published: 11 October 2019
(This article belongs to the Special Issue Remote Sensing and Image Processing for Fire Science and Management)
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.
Keywords: driving factors; wildfire; Random Forest; Mongolian Plateau driving factors; wildfire; Random Forest; Mongolian Plateau
MDPI and ACS Style

Rihan, W.; Zhao, J.; Zhang, H.; Guo, X.; Ying, H.; Deng, G.; Li, H. Wildfires on the Mongolian Plateau: Identifying Drivers and Spatial Distributions to Predict Wildfire Probability. Remote Sens. 2019, 11, 2361.

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