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Application of Ecology-Geomorphology Cognition Approach in Land Type Classification: A Case Study in the Altay Region

Author

Listed:
  • Baixue Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Weiming Cheng

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    Collaborative Innovation Center of South China Sea Studies, Nanjing 210093, China)

  • Keyu Song

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Suiji Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China)

  • Yichi Zhang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China)

  • Hao Li

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jiayin Deng

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Ruibo Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Land types play an important guiding role in human survival and production. Clarifying the division of land types is the basis for ensuring the sustainable and coordinated development of social-economic-natural complex ecosystems. To date, the land type classification system has not formed a unified standard, and the existing classification fails to highlight the natural background elements of land. Therefore, it is important to construct a classification system that can reflect natural background elements. Additionally, land type classification is often based on land resource surveys. Updating the land type is generally difficult and slow, mainly due to a lack of appropriate information. Hence, it is necessary to develop an automatic land type renewal method using multisource information. This study proposes the ecology-geomorphology cognition (Eco-geoC) approach for land type classification. The approach is realized by the segmentation of land units using remote sensing images, geographic information, vegetation, soil, DEM, and geoscience knowledge. This approach is an extension of the object-based image analysis method. The spatial objects segmented from different attribute data are integrated, and finally, a comprehensive land mapping unit representing a certain degree of geographical homogeneity and land use potential is generated. The results show that the Eco-geoC approach is an integrated approach with objectification cognition on remote sensing images and multisource information using geo-knowledge. The Eco-geoC approach is tested in the Altay region. From coarse to fine scales, the study area is divided into two kinds of natural belts, 27 land systems and 78 land units, and a 1:500,000 land-type map, which shows a good coupling relationship between the physiognomy, vegetation, and soil in the Altay region, is compiled. The results of this study show that the use of the Eco-geoC approach for land type classification is significant and has potential for land assessment and planning. This approach can provide a scientific basis for the restoration of the regional ecology and the comprehensive management and adjustment of land resources and the environment.

Suggested Citation

  • Baixue Wang & Weiming Cheng & Keyu Song & Suiji Wang & Yichi Zhang & Hao Li & Jiayin Deng & Ruibo Wang, 2022. "Application of Ecology-Geomorphology Cognition Approach in Land Type Classification: A Case Study in the Altay Region," Sustainability, MDPI, vol. 14(7), pages 1-22, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:4023-:d:782029
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    References listed on IDEAS

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    1. Alejandro Vallina-Rodríguez & Ángel I. Aguilar-Cuesta & Laura García-Juan & Miguel B. Bernabé-Crespo & Miguel A. Bringas-Gutiérrez & Concepción Camarero-Bullón, 2022. "Discovering the Legacy of Hispanic/Spanish and South American Landscapes through Geohistorical Sources: The Geographical and Topographical Relations of Philip II," Sustainability, MDPI, vol. 14(3), pages 1-14, January.
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    4. Solomon Kebebew & Bobe Bedadi & Teklu Erkossa & Fantaw Yimer & Lemma Wogi, 2022. "Effect of Different Land-Use Types on Soil Properties in Cheha District, South-Central Ethiopia," Sustainability, MDPI, vol. 14(3), pages 1-14, January.
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    Cited by:

    1. Jianfei Shi & Wenting Qian & Zhibin Zhou & Zhengzhong Jin & Xinwen Xu, 2023. "Influence of Acid Mine Drainage Leakage from Tailings Ponds on the Soil Quality of Desert Steppe in the Northwest Arid Region of China," Land, MDPI, vol. 12(2), pages 1-17, February.
    2. Yang Yan & Junhui Cheng & Yongkang Li & Jie Fan & Hongqi Wu, 2023. "Characteristics of NDVI Changes in the Altay Region from 1981 to 2018 and Their Relationship to Climatic Factors," Land, MDPI, vol. 12(3), pages 1-18, February.

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