Characteristics of Changes in Land Use Intensity in Xinjiang Under Different Future Climate Change Scenarios

Lijie Huang, Hongqi Wu (), Mingjie Shi (), Jingjing Tian, Kai Zheng, Tong Dong, Shanshan Wang, Yunhao Li and Yuwei Li
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Lijie Huang: Xinjiang Engineering Technology Research Center of Soil Big Data, Xinjiang Agricultural University, Urumqi 830052, China
Hongqi Wu: Xinjiang Engineering Technology Research Center of Soil Big Data, Xinjiang Agricultural University, Urumqi 830052, China
Mingjie Shi: Xinjiang Engineering Technology Research Center of Soil Big Data, Xinjiang Agricultural University, Urumqi 830052, China
Jingjing Tian: Institute of Natural Resources Planning of the Autonomous Region, Urumqi 830052, China
Kai Zheng: Xinjiang Engineering Technology Research Center of Soil Big Data, Xinjiang Agricultural University, Urumqi 830052, China
Tong Dong: Key Laboratory of Coastal Science and Integrated Management, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
Shanshan Wang: Xinjiang Engineering Technology Research Center of Soil Big Data, Xinjiang Agricultural University, Urumqi 830052, China
Yunhao Li: Xinjiang Engineering Technology Research Center of Soil Big Data, Xinjiang Agricultural University, Urumqi 830052, China
Yuwei Li: Xinjiang Engineering Technology Research Center of Soil Big Data, Xinjiang Agricultural University, Urumqi 830052, China

Sustainability, 2025, vol. 17, issue 10, 1-28

Abstract: Climate change drives land use intensity changes in Xinjiang, a typical inland arid region. There are relatively few studies on the changes in land use intensity under future climate change. For this purpose, this study adopts the Patch-level Land Use Simulation (PLUS) model and the Markov chain model, combined with shared socioeconomic pathways (SSPs). This study uses the PLUS model to make projections of land use/land cover (LULC) in Xinjiang under different climate scenarios for 2025–2060, constructs a land use intensity atlas to visualize regional spatial patterns, and analyzes the driving factors. The results show that under the SSP126 scenario, the cropland area decreases sharply while the forest, grassland, and water area expand rapidly. However, under the SSP245 and SSP585 scenarios, this trend is obviously reversed; the cropland area expands quickly, and the area of grassland and water decreases. In addition, under the SSP126 scenario, the management and control of LULC are strict, and it may be significantly affected by the conversion of cropland to forest, and the change of forest is relatively active. Under the SSP585 scenario, productivity increases, which may exacerbate the use of constructed land, and the change of constructed land is relatively active. Land use intensity may not significantly promote changes in land type proportions in the region. Population density and GDP are key drivers of land use intensity, showing relatively significant spatial heterogeneity. This study conducts research on the trend of LULC changes under different future climate scenarios, providing data support for the sustainable development of LULC and helping the government formulate different policies to cope with future LULC changes.

Keywords: future climate; land use; transfer matrix; intensity map; driving mechanisms; Xinjiang (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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