Abstract
The China–Mongolia railway is the core foundation for the construction of traffic connection in the China–Mongolia–Russia economic corridor. Long-term desertification has brought significant ecological risks to the railway area. Owing to the large variety of vegetation cover in this region, desertification information is easily confused with other weak vegetation cover information. This article proposes a refined desertification information extraction method based on multisource feature spaces and geographical zoning modeling. First, based on the geographical zoning, land cover, and vegetation coverage data for Mongolia, the railway area is divided into the Central provinces and their northern region, the Eastern Mongolian Plateau, and the Southern Gobi region. According to the vegetation coverage characteristics and the applicability of various feature space models to different geographical regions, Albedo–normalized difference vegetation index, Albedo–modified soil adjusted vegetation index, and Albedo–topsoil grain size index feature space models were constructed for three geographical regions. Faced with new challenges presented by global warming and the impact of monsoons on the classification and extraction of desertification information, we established a desertification classification system with six levels (severe desertification, high desertification, medium desertification, low desertification, withered grassland, and nondesertification) and complete desertification information extraction. The results show that the overall classification accuracy of the method selected in this article is 85.21%. We further analyzed the mechanism of this method, compared it with previous studies, and thereby proved that this method is feasible to extract the fine information of desertification in large areas and complex geographical environments.
Highlights
T HE China–Mongolia railway, which connects China and Mongolia, is the main cross-border transportation trunk line in the China–Mongolia–Russia region, and it is the core foundation of transportation connectivity for the construction of the China–Mongolia–Russia economic corridor in the Belt and Road Initiative
We found that the Albedo–normalized difference vegetation index (NDVI) model was applicable to areas with high vegetation coverage and a large forest ratio, the Albedo–modified soil adjusted vegetation index (MSAVI) model was applicable to areas with relatively low vegetation coverage, and the Albedo–topsoil grain size index (TGSI) model was
It can be observed that Albedo has significant negative correlation with NDVI and MSAVI, with fitting degrees of 0.6805 and 0.7015, respectively
Summary
T HE China–Mongolia railway, which connects China and Mongolia, is the main cross-border transportation trunk line in the China–Mongolia–Russia region, and it is the core foundation of transportation connectivity for the construction of the China–Mongolia–Russia economic corridor in the Belt and Road Initiative. The China–Mongolia–Russia economic corridor is characterized by complex geography, fragile ecology, and serious desertification. Mongolia is the hotspot of global desertification [1]. In 2017, data from the Ministry of Natural Environment and Tourism of Mongolia showed that 76.8% of the land in the country had been desertified to varying degrees, and this trend is still spreading at a faster rate [2]. The increasingly serious desertification problem along the China–Mongolia railway (Mongolian section), along with the environmental changes poses a risk to the construction of transportation infrastructure and the region’s sustainable development. It is necessary to establish a refined desertification information extraction method to accurately assess the desertification conditions along the China–Mongolia railway
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