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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (2) : 122-131     DOI: 10.6046/zrzyyg.2022117
GF-1 images-based information extraction of natural roads in arid and semi-arid regions of the Mongolian Plateau: A case study of Gurvantes Soum, Mongolia
LIANG Xiya1,2(), WANG Juanle1,3(), LI Pengfei2, DAVAADORJ Davaasuren4
1. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China
2. College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, China
3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China
4. School of the Art & Sciences, National University of Mongolia, Ulaanbaatar 14201, Mongolia
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Many unplanned natural roads, which are also known as temporary roads or unpaved roads, exist in the vast arid and semi-arid regions of the Mongolian Plateau. These natural roads, which were formed due to the arbitrary running of vehicles, will influence the surface ecology and its stability and aggravate land degradation in arid and semi-arid regions. They have a large quantity, are distributed irregularly, and tend to change with regional development. Therefore, there is an urgent need for the efficient and accurate information acquisition of natural roads in large-scale grassland regions, which is a challenge. Based on domestic high-resolution satellite (GF-1) images, this study extracted information on the natural roads in Mongolia using the object-oriented method. First, the data of GF-1 images covering the study area were preprocessed, and the image objects were segmented using the multiresolution segmentation method. Then, the characteristics of the natural roads were analyzed for information extraction. By calculating the parameters of spectral and geometric features and randomly selecting road samples to statistically analyze the characteristic values of samples, the parameters that could characterize the natural roads were selected to construct a set of rules for information extraction of roads. Finally, information on roads was extracted and optimized by combining multiple methods for classification, among which the nearest neighbor classification method was used for preliminary extraction while other classification algorithms such as threshold classification were used for optimization. Consequently, natural roads with a length of 3 708.745 km were extracted in the study area, with a density of 0.129 km/km2. This result shows that the natural roads in the study area are densely distributed in the southeast and sparsely distributed in the north and west overall. These distribution characteristics are consistent with the actual production of coal mine enterprises and the living of local residents in the study area. Therefore, the method proposed in this study can extract almost complete information about natural roads in the study area and thus can be used as a reference for the information extraction of natural roads in vast arid and semi-arid regions of the Mongolian Plateau.

Keywords GF-1 image      Mongolian Plateau      natural road      unpaved road      road information extraction      object-oriented     
ZTFLH:  TP79  
Issue Date: 07 July 2023
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Juanle WANG
Pengfei LI
Davaasuren DAVAADORJ
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Xiya LIANG,Juanle WANG,Pengfei LI, et al. GF-1 images-based information extraction of natural roads in arid and semi-arid regions of the Mongolian Plateau: A case study of Gurvantes Soum, Mongolia[J]. Remote Sensing for Natural Resources, 2023, 35(2): 122-131.
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卫星名称 轨道高度/km 传感器 重访周期/d 波段数 波谱或频率范围/μm 空间分辨率/m 幅宽/km 工作模式
GF-1 645 PMS全色 4 5 0.45~0.90 2 60 推扫成像
PMS多光谱 4 5 0.45~0.52 8
WFV多光谱 2 4 0.45~0.52 16 800
Tab.1  Main parameters of GF-1 satellites
Fig.1  Part of the image datas of the study area
Fig.2  The flow chart of road extraction
Fig.3  Image segmentation experiment
Fig.4  The result of optimal segmentation parameters combination
Fig.5  Calculation results of spectral characteristic parameters of image
Fig.6  Calculation results of image geometric feature parameters
序号 参数特征 特征值范围、阈值
1 长宽比 [5,19.3]
2 形状指数 [2.4,6]
3 密度 [0.38,0.75]
4 亮度 [1 460,1 871]
5 均值 [1 414,1 949]
6 标准差 [143,254]
Tab.2  Natural Road extraction rule set
Fig.7  Optimization of natural road wrong division
Fig.8  Road extraction distribution map of Gurvantes Soum in 2015
Fig.9  Overlay map of road distribution and elevation
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