FLUS Based Modeling of the Urban LULC in Arid and Semi-Arid Region of Northwest China: A Case Study of Urumqi City

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Abstract
Modeling land use and land cover (LULC) change is important for understanding its spatiotemporal trends and plays a crucial role in land use planning and natural resources management. To this end, this study assessed the spatiotemporal characteristics of the LULC changes in Urumqi city between 1980 and 2020. In addition, future LULC was successfully projected for 2030 and 2050 under different scenarios based on the FLUS model. This model was validated using actual and simulated land use data for 2020. The kappa coefficient and figure of merit of the simulation results for 2020 were 0.87 and 0.114, respectively, indicating that the simulation accuracy was satisfactory. The results demonstrated that grassland was the major land use type, with the area accounting for more than 50% of the study area. From 1980 to 2020, urban land greatly expanded, while grassland decreased significantly. Urban land increased from 353.51 km2 to 884.27 km2, while grassland decreased from 7903.4 km2 to 7414.92 km2 from 1980 to 2020. In addition, significant transitions mainly occurred between grasslands, cultivated lands and urban lands. Grassland and cultivated land were converted into urban land, resulting in rapid urban expansion over the last 40 years. From 1990 to 2000, grassland was converted into urban land with an area of 341.08 km2. Finally, the simulation results of the LULC showed that urban land is expected to increase under all three scenarios, and cultivated land, grassland and forest land are effectively protected under the Cultivated Land Protection Scenario (CPS) and Ecological Protection Scenario (EPS) compared to the Baseline Scenario (BLS). This study assessed the spatiotemporal characteristics and transitions of LULC between 1980 and 2020, and successfully projected LULC for 2035 and 2050 in Urumqi City in the arid and semi-arid regions of northwest China based on the FLUS model, which has not been investigated in previous studies.
Funding Information
  • National Natural Science Foundation of China (41661036, U1603241)
  • National Natural Science Foundation of China (41661036, U1603241)

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