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Study on Tianjin Land-Cover Dynamic Changes, Driving Factor Analysis, and Forecasting

Author

Listed:
  • Zhaoxu Zhang

    (School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
    The Eighth Geological Brigade, Hebei Bureau of Geology and Mineral Resources Exploration, Qinhuangdao 066000, China)

  • Yuzhao Wei

    (School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China)

  • Xutong Li

    (School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China)

  • Dan Wan

    (Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
    Tianjin Bohai Rim Coastal Earth Critical Zone National Observation and Research Station, Tianjin University, Tianjin 300072, China)

  • Zhenwei Shi

    (Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China)

Abstract

Land-use and land-cover changes constitute pivotal components in global environmental change research. Through an examination of spatiotemporal variations in land cover, we can deepen our understanding of land-cover change dynamics, shape appropriate policy frameworks, and implement targeted environmental conservation strategies. The judicious management of land is a critical determinant in fostering the sustainable growth of urban economies and enhancing quality of life for residents. This study harnessed remote sensing data to analyze land-cover patterns in Tianjin over five distinct time points: 2000, 2005, 2010, 2015, and 2020. It focused on evaluating the evolving dynamics, transition velocities, and transformation processes across various land categories within the region. Utilizing dynamic analysis and a transition matrix, the study traced shifts among different land-use classes. The center-of-gravity migration model was employed to elucidate land-cover pattern evolution. This research also integrated pertinent land-cover statistics to offer a holistic perspective on Tianjin’s land-cover transformations. Employing the CA–Markov model, we projected the prospective spatial layout of land cover for the area. Our findings revealed the following. (1) From 2000 to 2020, Tianjin experienced a significant reduction in cropland, forest, grassland, and water areas, alongside a substantial increase in impervious. (2) The impervious surface’s center of gravity, initially in Beichen District, shifted 4.20 km northwestward at an average rate of 0.84 km per year. (3) Principal component analysis indicated that the growth in the output value of the secondary and forestry industries is a key driver in expanding Tianjin’s impervious-surface area. (4) Predictions for 2025 suggest an increase in Tianjin’s impervious-surface area to 4659.78 km 2 , with a concurrent reduction in cropland to 5656.18 km 2 . The insights gleaned from this study provide a solid theoretical foundation and empirical evidence, aiding in the formulation of informed land-use strategies, the preservation of urban land resources, and guiding principles for sustainable urban development.

Suggested Citation

  • Zhaoxu Zhang & Yuzhao Wei & Xutong Li & Dan Wan & Zhenwei Shi, 2024. "Study on Tianjin Land-Cover Dynamic Changes, Driving Factor Analysis, and Forecasting," Land, MDPI, vol. 13(6), pages 1-20, May.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:6:p:726-:d:1399727
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    References listed on IDEAS

    as
    1. Dang, Anh Nguyet & Kawasaki, Akiyuki, 2017. "Integrating biophysical and socio-economic factors for land-use and land-cover change projection in agricultural economic regions," Ecological Modelling, Elsevier, vol. 344(C), pages 29-37.
    2. Maomao Zhang & Cheng Zhang & Abdulla-Al Kafy & Shukui Tan, 2021. "Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China," Land, MDPI, vol. 11(1), pages 1-17, December.
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