Research Progress of Land Use Land Change Spatial Simulation Prediction

Authors

  • Yinping Wang
  • Zhaoxin Zhang

DOI:

https://doi.org/10.54691/jamf7138

Keywords:

Land Use; Spatial Simulation; Driving Mechanism; Research Progress.

Abstract

Land use Land change is mainly driven by human activities, is an important part of the changing environment, and is also a direct reflection of the impact of human activities on the changing environment. By analyzing the research progress in three aspects of land use change characteristics, driving mechanism and simulation prediction, this paper obtains the key research direction of subsequent land use related research, and provides scientific support for the development of land engineering industry.

Downloads

Download data is not yet available.

References

[1] Luo J, Xin LJ, Liu FG, et al. Study of the intensity and driving factors of land use/cover change in the Yarlung Zangbo River, Nyang Qu River, and Lhasa River region, Qinghai-Tibet Plateau of China[J]. Journal of Arid Land, 2022, 14(4): 411-425.

[2] He QQ, Meng Q, Flatley W, et al. Examining the effects of agricultural aid on forests in sub-Saharan Africa: A causal analysis based on remotely sensed data of Sierra Leone[J]. Land, 2022, 11(5): 668.

[3] Zhai H, Lv CQ, Liu WZ, et al. Understanding spatio-temporal patterns of land use/land cover change under urbanization in Wuhan, China, 2000-2019[J]. Remote Sensing, 2021, 13(16): 3331.

[4] Liu SL, Dong YH, Wang FF, et al. Priority area identification of ecological restoration based on land use trajectory approach—Case study in a typical karst watershed[J]. Frontiers in Environmental Science, 2022, 10: 1011755.

[5] Li J, Jiang Z, Miao H, et al. Identification of cultivated land change trajectory and analysis of its process characteristics using time-series Landsat images: A study in the overlapping areas of crop and mineral production in Yanzhou City, China[J]. Science of the Total Environment, 2022, 806: 150318.

[6] Wang JF, Li XH, Christakos G, et al. Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region, China[J]. International Journal of Geographical Information Science, 2010, 24(1): 107-127.

[7] Liu XP, Liang X, Li X, et al. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects[J]. Landscape and Urban Planning, 2017, 168: 94-116.

[8] Yu Y, Guo B, Wang CL, et al. Carbon storage simulation and analysis in Beijing-Tianjin-Hebei region based on CA-plus model under dual-carbon background[J] Geomatics Natural Hazards & Risk, 2023, 14(1): 2173661.

[9] Li Z, Jiang WG, Peng KF, et al. Comparative analysis of land use change prediction models for land and fine wetland types: Taking the wetland cities Changshu and Haikou as examples[J]. Landscape and Urban Planning, 2024, 243: 104975.

[10] Lin ZQ, and Peng SY. Comparison of multimodel simulations of land use and land cover change considering integrated constraints- A case study of the Fuxian Lake basin[J]. Ecological Indicators, 2022, 142: 109254.

Downloads

Published

2024-12-20

Issue

Section

Articles

How to Cite

Wang, Y., & Zhang, Z. (2024). Research Progress of Land Use Land Change Spatial Simulation Prediction. Scientific Journal of Technology, 6(12), 1-4. https://doi.org/10.54691/jamf7138