Spatial and Temporal Variation, Simulation and Prediction of Land Use in Ecological Conservation Area of Western Beijing
2022
Jia Wang | Junping Zhang | Nina Xiong | Boyi Liang | Zong Wang | Elizabeth Cressey
Exploring land use change is crucial to planning land space scientifically in a region. Taking the ecological conservation area (ECA) in western Beijing as the study area, we employ ArcGIS 10.2, landscape pattern index and multiple mathematical statistics to explore the temporal and spatial variation of land use from 2000 to 2020. Patch-generating Land Use Simulation (PLUS), Future Land Use Simulation (FLUS) and Markov models were used to simulate and predict the current land use in 2020. The models were evaluated for accuracy, and the more accurate PLUS model was selected and used to simulate and predict the potential land use in the study area in 2030 under two management scenarios. The main findings of this research are: (1) From 2000 to 2020, the construction land increased constantly, and the area of cultivated land and grassland decreased significantly. (2) For predicting the spatial distribution of land use in the study area, the PLUS model was more accurate than the FLUS model. (3) The land-use prediction of the study area in 2030 shows that the area of grassland, forest and water is approximately equal to their corresponding value in 2020, but the construction land increased constantly by occupying the surrounding cultivated land. According to this research, the continuous decrease of cultivated land in favor of increasing construction land will cause losses to the ecological service function of the ECA, which is not beneficial to the sustainable development of the region. Relevant departments should take corresponding measures to reduce this practice and promote sustainable development, particularly in the southern and western areas of the ECA where there is less construction land.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Multidisciplinary Digital Publishing Institute
Découvrez la collection de ce fournisseur de données dans AGRIS