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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (4) : 282-291     DOI: 10.6046/zrzyyg.2022341
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Changes and spatial conflict measurement of land use in Urumqi City
TIAN Liulan1(), LYU Siyu1, WU Zhaopeng1,2(), WANG Juanjuan1, SHI Xinpeng1
1. School of Geographic Science and Tourism, Xinjiang Normal University, Urumqi 830054, China
2. Laboratory of Lake Environment and Resources in Arid Region of Xinjiang, Urumqi 830054, China
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Abstract  

Identifying land use conflicts holds critical significance for sustainable socio-economic development and ecological civilization construction. Since Urumqi City is situated in the core region of the Silk Road Economic Belt, investigating the causes and manifestations of its land use conflicts arising from urban development, oasis agriculture, and ecological environment becomes an urgent and necessary task. With Urumqi as the study area, this study analyzed its land use characteristics in 2000, 2010, and 2020, as well as those in 2030 simulated from the FLUS model. Based on this analysis and the pressure-state-response (PSR) model, a land use conflict intensity measurement model was constructed to evaluate the land use conflicts over the four periods. Finally, a geographic detector was employed to quantitatively analyze the factors driving land use conflicts in the study area. The findings indicate that: ① The land use between 2000 and 2030 exhibited significant spatial differentiation, showing increased construction land, forest land, and water areas, but decreased grassland, arable land, and unused land; ② The comprehensive indices of land use indicate low to medium utilization degrees but an overall rising trend, suggesting land use in a development stage; ③ Significant spatial changes occurred in land use conflicts between 2000 and 2030. The conflict-free and mild conflict zones occupied the largest proportions, the moderate conflict zones showed normal distributions, and severe and high-level conflict zones increased annually, with the highest increase observed in high-level conflict zones; ④ From 2000 to 2010, the hotspots of land use conflicts were distributed primarily in the north and southwest of the central urban area. From 2010 to 2020, they spread to the periphery of forest land in the southern and northern mountainous areas, and the areas near the alluvial fans on both sides of the salt lake in the Dabancheng District. From 2020 to 2030, the hotspots are still mainly located around the land for construction and near the forest land in mountainous areas but significantly decreased in the mountainous areas; ⑤ As demonstrated by one-way influence analysis of spatial differentiation drivers on land use conflicts, the influences of factors are in the order of patch density > population density > GDP > slope > elevation > distance from districts and counties > distance from rivers > distance from roads. Additionally, the interaction detection analysis indicates (patch density ∩ elevation) > (patch density ∩ average land population)>(patch density ∩ distance from roads). This study serves as a reference for effectively managing the conflicting demands between economic development and ecological conservation in Urumqi and enhancing the future land use composition.
Keywords FLUS model      land use change      land use conflict      geographical detector      Urumqi     
ZTFLH:  TP79  
Issue Date: 21 December 2023
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Liulan TIAN
Siyu LYU
Zhaopeng WU
Juanjuan WANG
Xinpeng SHI
Cite this article:   
Liulan TIAN,Siyu LYU,Zhaopeng WU, et al. Changes and spatial conflict measurement of land use in Urumqi City[J]. Remote Sensing for Natural Resources, 2023, 35(4): 282-291.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022341     OR     https://www.gtzyyg.com/EN/Y2023/V35/I4/282
Fig.1  Sketch map of study area
目标层 准则层 指标层 权重 与土地利用
冲突的关系
土地利用冲突综合指数 压力(P) 干扰度指数 1/3 +
状态(S) 脆弱度指数 1/3 +
响应(R) 稳定性指数 1/3 -
Tab.1  The landuse conflict composite index to measure indicators
判断依据 交互作用
q(X1∩X2)<min(q(X1),q(X2)) 非线性减弱
min(q(X1),q(X2)) <q(X1∩X2) <max(q(X1),q(X2)) 单因子非线性减弱
q(X1∩X2)>max(q(X1),q(X2)) 双因子增强
q(X1∩X2)= q(X1)+q(X2) 独立
q(X1∩X2)>q(X1)+q(X2) 非线性增强
Tab.2  Types of interaction
Fig.2  Distribution of land use pattern
Fig.3  Changes in land use pattern
Fig.4  Distribution of land use conflict pattern from 2020 to 2030
Fig.5  Change of land use conflict area at different levels
Fig.6  Temporal and spatial evolution of cold and hot spots of land use conflict
Fig.7  Pattern distribution of natural environment driving factors
Fig.8  Distribution pattern of socio-economic driving factors
因子指标 斑块密度 地均人口 GDP 坡度 高程 距区县距离 距河流距离 距道路距离
q统计量 0.763 3 0.092 6 0.077 7 0.069 7 0.057 8 0.046 7 0.035 8 0.034 8
p值 0.000 0 0.000 0 0.000 0 0.000 0 0.000 0 0.000 0 0.000 0 0.000 0
Tab.3  Factor detection results of land use conflict
因子 斑块密度 高程 距河流距离 坡度 距区县距离 距道路距离 GDP 地均人口
斑块密度 0.763 3
高程 0.806 3* 0.057 8
距河流距离 0.767 7* 0.098 7# 0.035 8
坡度 0.781 3* 0.104 8* 0.096 9* 0.069 7
距区县距离 0.785 4* 0.091 9* 0.080 8* 0.115 3* 0.046 7
距道路距离 0.787 6* 0.092 2* 0.096 4# 0.104 1* 0.065 9* 0.034 8
GDP 0.785 6* 0.131 6* 0.112 7* 0.131 7* 0.114 9* 0.108 1* 0.077 7
地均人口 0.795 6* 0.161 6* 0.128 3* 0.161 7* 0.134 9* 0.126 7* 0.164 9* 0.092 6
Tab.4  Interactive detection results of land use conflict
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