E3S Web Conf.
Volume 308, 20212021 6th International Conference on Materials Science, Energy Technology and Environmental Engineering (MSETEE 2021)
|Number of page(s)||7|
|Section||Environmental Ecology and Biochemical Testing|
|Published online||27 September 2021|
Evaluation of environmental recovery and vulnerability in the Mohe area by using mathematical modeling and remote sensing techniques
1 College of letter and science, University of California Santa Barbara, Goleta, California, 93117, The United States
2 School of Ecosystem and Forest Sciences, University of Melbourne, Melbourne, Victoria, 3010, Australia
3 Environmental Engineering, Rensselaer Polytechnic Institute, Troy, New York, 12180, The United States
In the Greater Khingan Range, wildfires in forests were frequent and severe. The wildfire in the Greater Khingan Range in 1987 was one of the severest wildfires in human history, and the study is primarily based on this natural disaster. Mohe is a representative region in the Greater Khingan Range field related to wildfire cases. Many indicators affect the relationship between wildfire and forests, such as topography, climate change, and human behaviors. This paper used remote sensing techniques, the AHP model, and the entropy model to study the environmental fragility of forests in the region of Mohe. Present paper used NDVI images from 1987, 1992, 1997, 2002 to detect the vegetation coverage change in this area and found out its potential problems that need to be paid attention to. NDVI images in the paper showed that the vegetation coverage in the region of Mohe was generally low. Therefore, the results indicated that it is necessary to make prevention and conservation in the region of Mohe. By collecting dem images and data from fire yearbooks within these years, the paper summarized seven indicators: vegetation coverage, number of fires, area of damaged forest, number of injured people, slope, altitude, and temperature. Then the paper used the AHP model to calculate the ratio of each indicator affecting wildfire and scored on indicators to observe the quality of the environment under different indicators. AHP tables in the paper showed that the influence of slope and altitude were weak on a wildfire in this region because their scores were constant. Forest quality in 1987 was relatively low, and the trend dramatically increased after this year; however, it decreased again from 1997 to 2002. Besides the AHP model, the paper also provided an entropy model by using the same parameters. Compared to the AHP model, the entropy model was more objective. Although its scores were all higher than the AHP model, the trends of the two models were similar.
© The Authors, published by EDP Sciences, 2021
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