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Volume 43 Issue 3
Aug.  2024
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Article Navigation >  CARSOLOGICA SINICA  > 2024  >  43(3): 595-605
HE Jiyong, TIAN Yichao, ZHANG Qiang, WANG Donghua, ZHANG Yali, ZHOU Huijuan. Geomorphic information extraction and morphological characteristics analysis of karst peak-cluster depressions based on DEM[J]. CARSOLOGICA SINICA, 2024, 43(3): 595-605. doi: 10.11932/karst20240306
Citation: HE Jiyong, TIAN Yichao, ZHANG Qiang, WANG Donghua, ZHANG Yali, ZHOU Huijuan. Geomorphic information extraction and morphological characteristics analysis of karst peak-cluster depressions based on DEM[J]. CARSOLOGICA SINICA, 2024, 43(3): 595-605. doi: 10.11932/karst20240306
shu

Geomorphic information extraction and morphological characteristics analysis of karst peak-cluster depressions based on DEM

doi: 10.11932/karst20240306
  • 1.

    Beibu Gulf Marine Development Research Center/College of Resources and Environment, Beibu Gulf University, Qinzhou, Guangxi 535000, China

  • 2.

    Guangxi Key Laboratory of Marine Environmental Change and Disaster Research/Key Laboratory of Development and Utilization of Marine Geographic Information Resources, Beibu Gulf University, Qinzhou, Guangxi 535000, China

  • 3.

    College of Environmental Science and Engineering, Guilin University of Technology, Guilin, Guangxi 541004, China

  • Received Date: 2023-06-13
    Available Online: 2024-08-15
    Abstract
  • The largest area of karst in the world is distributed in China. In the karst area, the peak-cluster depression is regarded as one of the typical landforms. The positive and negative landforms in peak-cluster depressions control the spatial distribution pattern of soil and water resources, and significantly affect regional landforms, soil erosion and quality of regional ecological environment.In the southwest of Guangxi Zhuang Autonomous Region (hereinafter referred to as southwest Guangxi), the distribution of karst landforms is relatively concentrated, and their unique and steep terrain greatly restricts the development of regional economy. Consequently, this remote and border region became a poverty-stricken area in which are located old revolutionary bases and is inhabited by minority nationalities. The landform of karst peak-cluster depression together with urban architecture formed a unique mosaic landscape in southwest Guangxi, which is vulnerable in ecological environment. Although the traditional method of artificial vectorization can accurately obtain the positive and negative topographic features of peak-cluster depressions, this method has its disadvantages such as high working intensity, low working efficiency and long working period, which may pose challenges to the information extraction of peak-cluster depressions on a large regional scale, and which may also limit the detailed study on the ecosystem of peak-cluster depression basins. Therefore, it is of great significance for us to explore the formation mechanism of peak-cluster depressions and the evolution of regional geographic environment so that we can provide a scientific basis for the protection and sustainable development of regional ecological environment.In this study, with the use of software such as ArcGIS and Google Earth, information of peak-cluster depressions was extracted based on Digital Elevation Model (DEM) and satellite remote sensing images by two methods: hydrology method and saddle method. By means of spatial analysis and fractal theory, the structural morphological characteristics and spatial distribution of peak-cluster depressions were quantitatively analyzed. The results show as follows. (1) In terms of extraction methods, the saddle method can extract the depression boundary based on the features of the saddle, while the hydrology method can effectively identify the depression by simulating the convergence process of water flow. Compared with the hydrologic method, the saddle method can improve the accuracy of extracting saddle points by 29.80%. (2) In the morphological analysis of peak-cluster depressions, 94% of the depressions in the study area are basin-shaped, and the rest are deep cone-shaped and dish-shaped. The main morphology of peak-cluster depressions in the study area is basin-shaped with a shallow depth and a small area. In addition, the analysis of the relationship between the circumference and the area of the depression patch finds that there is a high correlation between the two, and its fractal dimension is 1.15. The mosaic structure of the depression patch is relatively stable. (3) In terms of spatial distribution, 80% of the peak-cluster depressions in the study area are concentrated in the interbedding areas of limestone and dolomite and in the contiguous areas of limestone in the south and north of the study area, while the development of peak-cluster depressions in the central clastic rock strata is not obvious.

     

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