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Characteristics and Forecasting of Rocky Desertification Dynamics in the Pearl River Source Region from 1990 to 2030

Author

Listed:
  • Haojun Sun

    (College of Soil and Water Conservation, Southwest Forestry University, Kunming 650224, China
    Key Laboratory of Ecological Environment Evolution and Pollution Control in Mountainous & Rural Areas of Yunnan Province, Kunming 650224, China
    Zhanyi Karst Ecosystem Observation and Research Station, Qujing 655500, China)

  • Shaoyun Zhang

    (College of Soil and Water Conservation, Southwest Forestry University, Kunming 650224, China
    Key Laboratory of Ecological Environment Evolution and Pollution Control in Mountainous & Rural Areas of Yunnan Province, Kunming 650224, China
    Zhanyi Karst Ecosystem Observation and Research Station, Qujing 655500, China)

  • Songyang He

    (College of Soil and Water Conservation, Southwest Forestry University, Kunming 650224, China
    Key Laboratory of Ecological Environment Evolution and Pollution Control in Mountainous & Rural Areas of Yunnan Province, Kunming 650224, China
    Zhanyi Karst Ecosystem Observation and Research Station, Qujing 655500, China)

  • Zecheng Liu

    (College of Geographical Sciences, Shanxi Normal University, Taiyuan 030031, China)

Abstract

Rocky desertification is a significant ecological issue in the karst regions of Southwest China, severely affecting both the environment and local livelihoods. Accurate extraction and prediction of rocky desertification are critical for its prevention and control, playing a crucial role in advancing ecological civilization and sustainable land management. This study focuses on the Pearl River source area in Yunnan, analyzing dynamic changes in rocky desertification over eight periods from 1990 to 2023, using long-term remote sensing data and multi-source reference data. It also predicts the intensity and trends of rocky desertification for the next decade. The results indicate that: (1) Rocky desertification is widespread and severe in the study area; however, its further intensification has been effectively mitigated through long-term governance efforts. By 2023, an area of 14,896.19 km 2 of rocky desertification has been mitigated to varying extents, accounting for 55.77% of the total watershed area. Trend analysis suggests that, under current management conditions, rocky desertification will continue to decline and improve over time. (2) The overall development of rocky desertification in the basin is showing a positive trend, with deep-level rocky desertification gradually transitioning to shallow-level rocky desertification. In future scenarios, the extent of rocky desertification will continue to decrease. (3) The approach of integrating the Google Earth Engine with traditional remote sensing platforms for extracting rocky desertification information has proven to be both fast and efficient. This method retains high extraction accuracy while alleviating the data burden typically associated with exclusive use of local platforms, thereby enhancing processing efficiency.

Suggested Citation

  • Haojun Sun & Shaoyun Zhang & Songyang He & Zecheng Liu, 2025. "Characteristics and Forecasting of Rocky Desertification Dynamics in the Pearl River Source Region from 1990 to 2030," Land, MDPI, vol. 14(5), pages 1-18, May.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:5:p:984-:d:1648440
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    References listed on IDEAS

    as
    1. Shiwen Zhang & Yan Wang & Xuehua Wang & Yang Wu & Chengrong Li & Chao Zhang & Yuhang Yin, 2022. "Ecological Quality Evolution and Its Driving Factors in Yunnan Karst Rocky Desertification Areas," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
    2. Zhenming Zhang & Yunchao Zhou & Shijie Wang & Xianfei Huang, 2018. "Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds," IJERPH, MDPI, vol. 15(4), pages 1-13, April.
    3. Jiaju Cao & Xingping Wen & Meimei Zhang & Dayou Luo & Yinlong Tan, 2022. "Information Extraction and Prediction of Rocky Desertification Based on Remote Sensing Data," Sustainability, MDPI, vol. 14(20), pages 1-15, October.
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