Characteristics of Spatial and Temporal Land Use Changes, Driving Factors and Development Trend Prediction
-- Taking the Three Northeastern Provinces as an Example
DOI:
https://doi.org/10.54097/1hd6kw45Keywords:
PLUS Model, Three Northeastern Provinces, Markov Chain, Land Use, Future Prediction, Driving MechanismAbstract
Urbanization and economic development have reshaped the production and living needs of the population, making land-use planning and forecasting increasingly critical for national development. Currently, the issues related to land use in the three northeastern provinces of China remain inadequately defined. This study focuses on these provinces, investigating the spatial and temporal patterns of land-use change, the driving factors influencing land-use types, and future development trends. By analyzing data from the National Bureau of Statistics, the Chinese Academy of Sciences, and the Institute of Geography, among others, and applying the PLUS model, Markov chains, and ArcGIS spatial analysis techniques, the study yields the following conclusions: (i) The influence of different driving factors on the expansion of various types of land in the three northeastern provinces has obvious differences, among which the influence of GDP on construction land is particularly significant. (ii) Under the double influence of national strategy and the background of the times, the land use of the three northeastern provinces has been transformed, with arable land and residential land, construction land expanding in the central plains; and forests converting into the peripheral mountainous areas, especially in the northern forested areas with a particularly significant trend. (iii) The likelihood of conversion of different land-use types varies, with cropland and forest land in general not changing much. In contrast, the probability of conversion of grassland and other construction land is as high as 50%, and unutilized land is also subjected to a considerable degree of development. Only about 20% of urban and rural residential land is likely to change, but there is a clear trend of conversion between the two. (iv) Generally speaking, there will be little change in land use in the study area in the next 10 years. Under the influence of “returning farmland to the forest”, arable land will shrink in the Sanjiang Plain and Songnen Plain, and the area of ecological land will grow significantly; further population growth will trigger urbanization and residential migration in the suburbs, and the sustainable development of food, environment, and population will be realized step by step.
Downloads
References
[1] Zhang, S. Q., Zhang, S. L., Jiang, Z. & Wbm Org, C. in 1st Conference on Web Based Business Management. 931-+ (2010).
[2] Liu, F. et al. Urban expansion in China and its spatial-temporal differences over the past four decades. Journal of Geographical Sciences 26, 1477-1496, doi:10.1007/s11442-016-1339-3 (2016).
[3] Guo, C. X. & Hu, Y. China's Sustainable Industrialization and Its Significance. Chinese Journal of Urban and Environmental Studies 7, doi:10.1142/s2345748119400037 (2019).
[4] Luo, B. & Dou, X. Climate change, agricultural transformation and climate smart agriculture development in China. Heliyon 10, e40008, doi:https://doi.org/10.1016/j.heliyon.2024.e40008 (2024).
[5] Sun, X., Xiang, P. & Cong, K. Research on early warning and control measures for arable land resource security. Land Use Policy 128, 106601, doi:https://doi.org/10.1016/j.landusepol.2023.106601 (2023).
[6] Cavanagh, C. & Nel, A. Introduction to the special issue – Frontiers of property: promises, pitfalls, and ambivalences of ‘resurgent collectivisation’ in global land and resource governance. Political Geography 115, 103218, doi:https://doi.org/10.1016/j.polgeo.2024.103218 (2024).
[7] Pojani, D., Corcoran, J., Mateo-Babiano, I., Sipe, N. & Stead, D. Special issue on global transitions of urban mobility and land use. Land Use Policy 91, 104425, doi: https:// doi.org/10. 1016/j. landusepol. 2019. 104425 (2020).
[8] Xie, H. L., Zhang, Y. W., Zeng, X. J. & He, Y. F. Sustainable land use and management research: a scientometric review. Landscape Ecology 35, 2381-2411, doi:10.1007/s10980-020-01002-y (2020).
[9] Zakharov, V. V. Principle of Dynamic Balance of Demographic Process and the Limits of World Population Growth. Doklady Mathematics 108, 419-424, doi:10.1134/s1064562423701302 (2023).
[10] Jin, B. & Lv, Y. in I3rd International Conference on Management of Technology. 88-92 (2006).
[11] Yi, C. Z. in 10th International Conference on Public Administration. 457-468 (2014).
[12] Dale, V. H. The relationship between land-use change and climate change. Ecological Applications 7, 753-769, doi:10.1890/1051-0761(1997)007[0753:trbluc]2.0.co;2 (1997).
[13] Yu, H. Q. et al. Re-introduction of light grazing reduces soil erosion and soil respiration in a converted grassland on the Loess Plateau, China. Agriculture Ecosystems & Environment 280, 43-52, doi:10.1016/j.agee.2019.04.020 (2019).
[14] Tang, H. et al. Household Groups' Land Use Decisions Investigation Based on Perspective of Livelihood Heterogeneity in Sichuan Province, China. International Journal of Environmental Research and Public Health 19, doi:10.3390/ijerph19159485 (2022).
[15] Foley, J. A. et al. Global consequences of land use. 309, 570-574 (2005).
[16] Oyinna, B. et al. Assessing small hydropower sites in Nigeria for sustainable development using ArcGIS. Energy Reports 10, 2889-2898, doi:https://doi.org/10.1016/j.egyr.2023.09.102 (2023).
[17] Qiu, J. H. & Chen, H. B. Recent progresses in atmospheric remote sensing research in China - Chinese national report on atmospheric remote sensing research in China during 1999-2003. Advances in Atmospheric Sciences 21, 475-484 (2004).
[18] Li, L., Fu, M., Zhu, Y., Kang, H. & Wen, H. The current situation and trend of land ecological security evaluation from the perspective of global change. Ecological Indicators 167, 112608, doi:https:// doi.org/ 10. 1016/j.ecolind.2024.112608 (2024).
[19] Xu, X. et al. Integrating global socio-economic influences into a regional land use change model for China. Frontiers of Earth Science 8, 81-92, doi:10.1007/s11707-013-0421-8 (2014).
[20] Luo, R. & He, D. The dynamic impact of land use change on ecosystem services as the fast GDP growth in Guiyang city. Ecological Indicators 157, 111275, doi: https://doi.org/10.1016/j.ecolind.2023.111275 (2023).
[21] Liu, Y. C. et al. in 5th International Conference on Computer and Computing Technologies in Agriculture (CCTA). 340-350 (2012).
[22] Kabanda, T. Land use/cover changes and prediction of Dodoma, Tanzania. African Journal of Science Technology Innovation & Development 11, 55-60, doi:10.1080/20421338.2018.1550925 (2019).
[23] Bi, S. W., Lin, X. L., Yang, S. & Wu, Z. Q. in Conference on Quantum Sensing and Nano Electronics and Photonics XIII. (2016).
[24] Man, J. Y., Zhu, J. R., Cao, L. C. & Ieee. in 38th Chinese Control Conference (CCC). 7950-7955 (2019).
[25] Verburg, P. H. & Overmars, K. P. in Modelling Land-Use Change: Progress and Applications Vol. 90 Geojournal Library (eds E. Koomen, J. Stillwell, A. Bakema, & H. J. Scholten) 321-335 (2007).
[26] Liu, J. H., Gong, J. & Chen, J. H. in International Conference on Sustainable Energy and Environmental Engineering (ICSEEE 2012). 2523-+ (2013).
[27] Kiziridis, D. A. et al. Improving the predictive performance of CLUE-S by extending demand to land transitions: The trans-CLUE-S model. Ecological Modelling 478, doi:10.1016/j.ecolmodel.2023.110307 (2023).
[28] Zhang, Y. F., Yu, M. K. & Ye, Y. S. Spatial Land Use Optimization Using the CLUE-S Model: a Case Study in the Keerqinzuoyihou Banner, China. Polish Journal of Environmental Studies 31, 5963-5974, doi:10.15244/pjoes/151909 (2022).
[29] He, C. Y. et al. Developing land use scenario dynamics model by the integration of system dynamics model and cellular automata model. Science in China Series D-Earth Sciences 48, 1979-1989, doi:10. 1360/04yd0248 (2005).
[30] Haney, N. & Cohen, S. Predicting 21st century global agricultural land use with a spatially and temporally explicit regression-based model. Applied Geography 62, 366-376, doi:10.1016/j.apgeog.2015.05.010 (2015).
[31] Li, X., Liu, Z. S., Li, S. J. & Li, Y. X. Multi-Scenario Simulation Analysis of Land Use Impacts on Habitat Quality in Tianjin Based on the PLUS Model Coupled with the InVEST Model. Sustainability 14, doi:10. 3390/su14116923 (2022).
[32] Xu, L. F. et al. Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model. Land 11, doi:10.3390/land11050652 (2022).
[33] Yang, X. L. et al. Impacts of emission reduction and meteorological conditions on air quality improvement from 2016 to 2020 in the Northeast Plain, China. Journal of Environmental Sciences 151, 484-496, doi:10.1016/j.jes.2024.04.017 (2025).
[34] Li, D., Yang, Y., Du, G. & Huang, S. Understanding the contradiction between rural poverty and rich cultivated land resources: A case study of Heilongjiang Province in Northeast China. Land Use Policy 108, 105673, doi:https://doi.org/10.1016/j.landusepol.2021.105673 (2021).
[35] Chung, J. H., Lai, H. Y. & Joo, J. H. Assessing the "Revive the Northeast" Programme: Origins, Policies and Implementation. China Quarterly, 108-125, doi:10.1017/s030574100900006x (2009).
[36] Du, Y., Li, S. L. & Wang, H. W. Comparative analysis of resources and environment of regional economic development from the perspective of the man-earth relationship in the three provinces in northeast China. Agro Food Industry Hi-Tech 28, 642-648 (2017).
[37] Zhang, Y., Zhang, Y., Zhang, Y., Gong, C. & Kong, Y. Analysis of the carbon emission driving factors and prediction of a carbon peak scenario--A case study of Xi'an city. Heliyon 8, e11753, doi:https:// doi. org/ 10. 1016/j.heliyon.2022.e11753 (2022).
[38] Kejin, R. et al. Risk assessment of haze disaster in the Liaoning region based on ArcGIS and principal component analysis. Ecological Indicators 168, 112757, doi: https://doi.org/ 10.1016/j. ecolind. 2024. 112 757 (2024).
[39] Wu, L., Li, L. Y., Liu, H. Y., Cheng, X. F. & Zhu, T. X. Application of ArcGIS in Geography Teaching of Secondary School: A Case Study in the Practice of Map Teaching. Wireless Personal Communications 102, 2543-2553, doi:10.1007/s11277-018-5276-6 (2018).
[40] Zhou, Y. N., Zeng, C. H. & Xian, F. in 3rd International Conference on Materials Engineering, Manufacturing Technology and Control (ICMEMTC). 1013-1016 (2016).
[41] Wang, Q. et al. Multi-Scenario Simulation of Land-Use/Land-Cover Changes and Carbon Storage Prediction Coupled with the SD-PLUS-InVEST Model: A Case Study of the Tuojiang River Basin, China %J Land. 13, 1518-1518 (2024).
[42] Jian, L., Xia, X., Liu, X., Zhang, Y. & Wang, Y. Spatiotemporal variations and multi-scenario simulation of urban thermal environments based on complex networks and the PLUS model: A case study in Chengdu central districts %J Sustainable Cities and Society. 115, 105833-105833 (2024).
[43] Liang, X., Liu, X., Li, D., Zhao, H. & Chen, G. J. I. J. o. G. I. S. Urban growth simulation by incorporating planning policies into a CA-based future land-use simulation model. 32, 2294-2316 (2018).
[44] Zhao, B., Li, S. & Liu, Z. Multi-Scenario Simulation and Prediction of Regional Habitat Quality Based on a System Dynamic and Patch-Generating Land-Use Simulation Coupling Model—A Case Study of Jilin Province. Sustainability 14 (2022).
[45] Luo, H. et al. Carbon emission prediction model of prefecture-level administrative region: A land-use-based case study of Xi'an city, China. Applied Energy 348, 121488, doi: https://doi. org/10.1016/j. apenergy. 2023.121488 (2023).
[46] Liang, X. et al. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China. Computers, Environment and Urban Systems 85, 101569, doi:https://doi.org/10.1016/j.compenvurbsys.2020.101569 (2021).
[47] Park, C. Implementation of Markov chain: Review and new applications. Korean Journal of Applied Statistics 34, 537-556, doi:10.5351/kjas.2021.34.4.537 (2021).
[48] Kumar, S., Radhakrishnan, N., Mathew, S. J. G., Natural Hazards & Risk. Land use change modelling using a Markov model and remote sensing. 5, 145-156 (2014).
[49] Akgül, I., Bildirici, M. & Özdemir, S. Evaluating the Nonlinear Linkage between Gold Prices and Stock Market Index Using Markov-Switching Bayesian VAR Models. Procedia - Social and Behavioral Sciences 210, 408-415, doi:https://doi.org/10.1016/j.sbspro.2015.11.388 (2015).
[50] Zakarczemny, M. & Zajecka, M. Note on DNA Analysis and Redesigning Using Markov Chain. Genes 13, doi:10.3390/genes13030554 (2022).
[51] Martynenko, I. A., Maksimovich, A. V., Meshalkina, J. L., Stoorvogel, J. J. & Yaroslavtsev, A. M. in Megacities 2050: Environmental Consequences of Urbanization: Proceedings of the VI International Conference on Landscape Architecture to Support City Sustainable Development 6. 41-50 (Springer).
[52] Westlund, H. A brief history of time, space, and growth: Waldo Tobler's first law of geography revisited. Annals of Regional Science 51, 917-924, doi:10.1007/s00168-013-0571-3 (2013).
[53] Liu, Y. & He, Z. Synergistic industrial agglomeration, new quality productive forces and high-quality development of the manufacturing industry. International Review of Economics & Finance 94, 103373, doi:https://doi.org/10.1016/j.iref.2024.103373 (2024).
[54] Cao, S. Y. & Zhang, W. in International Conference on the Modern Development of Humanities and Social Science (MDHSS). 46-48 (2013).
[55] Yu, D. et al. Forest management in Northeast China: history, problems, and challenges. 48, 1122-1135 (2011).
[56] Yuan, X. F. et al. Study on the potential of cultivated land quality improvement based on a geological detector. Geological Journal 53, 387-397, doi:10.1002/gj.3160 (2018).
[57] Ma, J. C. et al. The Variation of the Soil Bacterial and Fungal Community Is Linked to Land Use Types in Northeast China. Sustainability 11, doi:10.3390/su11123286 (2019).
[58] Zhou, G. L., Zhang, J., Li, C. G. & Liu, Y. J. Spatial Pattern of Functional Urban Land Conversion and Expansion under Rapid Urbanization: A Case Study of Changchun, China. Land 11, doi:10. 3390/ land 11010119 (2022).
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.