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Geographically and Ontologically Oriented Scoping of a Dry Valley and Its Spatial Characteristics Analysis: The Case of the Three Parallel Rivers Region

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  • Linhao Zhang

    (School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Haiping Tang

    (School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Peijun Shi

    (State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810008, China)

  • Wei Jia

    (School of Geographical Science, Qinghai Normal University, Xining 810008, China)

  • Luwei Dai

    (School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

Abstract

A dry valley is a special landscape type that is formed by the combined effect of climate and topography. Accurately defining the scope of a dry valley and knowledge of its spatial distribution characteristics can provide data support for relevant studies in the region. Starting from natural ontological characteristics and formation mechanisms, we constructed a geographical ontological model of dry valleys through an analysis of concepts related to the dry valley and combined GIS technology and methods to accurately define the scope and analyze the spatial characteristics of the dry valleys in the Three Parallel Rivers Region (DVT). Our results show that: (1) The geographically and ontologically oriented method developed to define the scope of the dry valley has a high accuracy, with an overall accuracy of 92.3% and a kappa coefficient of 0.84, therefore it can provide a better mechanism for defining the scope of a dry valley on a large scale. (2) The total area and total length of the DVT are 6147.1 km 2 and 2125.3 km, respectively. The dry valleys in this region are mainly located in the Tibet Autonomous Region and in the Sichuan and Yunnan provinces in China. (3) The terrain in the DVT is precipitous, and areas with slopes greater than 25° account for 70% of the total area of the dry valleys. The DVT area of sunny aspects (north, northeast, and northwest aspects) is larger than that of shady aspects (south, southeast, and southwest aspects), and the land cover is mainly grassland with a desert substrate. The result of our study can provide data support for further in-depth research in related fields of dry valleys.

Suggested Citation

  • Linhao Zhang & Haiping Tang & Peijun Shi & Wei Jia & Luwei Dai, 2023. "Geographically and Ontologically Oriented Scoping of a Dry Valley and Its Spatial Characteristics Analysis: The Case of the Three Parallel Rivers Region," Land, MDPI, vol. 12(6), pages 1-17, June.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:6:p:1235-:d:1172289
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    References listed on IDEAS

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    1. Chao Yang & Jianrong Fan & Jiali Liu & Fubao Xu & Xiyu Zhang, 2021. "Evaluating the Dominant Controls of Water Erosion in Three Dry Valley Types Using the RUSLE and Geodetector Method," Land, MDPI, vol. 10(12), pages 1-16, November.
    2. Weidong Ma & Wei Jia & Peng Su & Xingyun Feng & Fenggui Liu & Jing’ai Wang, 2021. "Mapping Highland Barley on the Qinghai–Tibet Combing Landsat OLI Data and Object-Oriented Classification Method," Land, MDPI, vol. 10(10), pages 1-15, September.
    3. Zhilian Gong & Yong Li & Luqing Liu & Shuang Deng, 2022. "Great Facilitation of Thirty Years of Reforestation with Mixed Species to Ecosystem Nitrogen Accumulation in Dry-Hot Valley in the Jinsha River," IJERPH, MDPI, vol. 19(19), pages 1-12, October.
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    Cited by:

    1. Jiansong Luo & Min Xie & Qiang Wu & Jun Luo & Qi Gao & Xuezhi Shao & Yongping Zhang, 2024. "Early Crop Identification Study Based on Sentinel-1/2 Images with Feature Optimization Strategy," Agriculture, MDPI, vol. 14(7), pages 1-28, June.

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