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Remote Sensing for Land & Resources    2020, Vol. 32 Issue (1) : 176-183     DOI: 10.6046/gtzyyg.2020.01.24
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Dynamic simulation of multi-scenario land use change based on CLUMondo model: A case study of coastal cities in Guangxi
Ruiqi GUO, Bo LU, Kailin CHEN
School of Public Administration, Guangxi University, Nanning 530004, China
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Abstract  

In this study, the authors used the CLUMondo model which can deeply describe the intensity of land and the land use data of 2010 and 2015 to simulate the spatial distribution pattern of land use in the three different scenarios of “natural growth”, “economic development” and “land use optimization” in coastal cities of Guangxi in 2025. Some conclusions have been reached: The CLUMondo model can effectively simulate the development status and trajectory of land system in large-scale coastal areas; under the“natural growth” scenario, the intensive and effective use of land resources in coastal cities has been slower; under the “economic development” scenario, urban and rural construction land is growing rapidly and is closely related in space. There is a sharp contradiction between regional forest and cultivated land protection and industrial construction; under the “land use optimization” scenario, the pace of regional economic construction has gradually slowed down, and the construction of regional cities has formed a trend of concentration of resources to cities and towns and concentration of farmlands. The simulation results provide a certain reference for the future land use planning and related system formulation of coastal cities in Guangxi and even the whole country.
Keywords land use change simulation      coastal city      CLUMondo model     
:  TP79  
Issue Date: 14 March 2020
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Ruiqi GUO
Bo LU
Kailin CHEN
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Ruiqi GUO,Bo LU,Kailin CHEN. Dynamic simulation of multi-scenario land use change based on CLUMondo model: A case study of coastal cities in Guangxi[J]. Remote Sensing for Land & Resources, 2020, 32(1): 176-183.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.01.24     OR     https://www.gtzyyg.com/EN/Y2020/V32/I1/176
Fig.1  Driving factors of land use spatial pattern in the study area
Fig.2  CLUMondo model of land use change allocation
Fig.3  Restriction map for spatial planning of coastal cities in Guangxi
土地利用类型 AUC 土地利用类型 AUC
高产量农田 0.70 城市建设用地 0.98
低产量农田 0.68 农村建设用地 0.74
林地 0.84 水域 0.85
草地 0.65 其他用地 0.73
Tab.1  Logistic regression coefficient table for different land use types
土地利用类型 高产量农田 低产量农田 林地 草地 城市建设用地 农村建设用地 水域 其他用地
高产量农田 1 1 1 1 1 1 1 1
低产量农田 1 1 1 1 1 1 1 1
林地 1 1 1 1 1 1 1 1
草地 1 1 1 1 1 1 1 1
城市建设用地 0 0 0 0 1 1 0 0
农村建设用地 0 0 0 0 1 1 0 0
水域 1 1 1 1 1 1 1 0
其他用地 1 1 1 1 1 1 1 1
Tab.2  Transfer matrix between different land use types
土地利用类型 转换弹性系数 土地利用类型 转换弹性系数
高产量农田 0.8 城市建设用地 0.9
低产量农田 0.7 农村建设用地 0.9
林地 0.7 水域 0.7
草地 0.6 其他用地 0.8
Tab.3  Transfer resistance parameters for different land use types
年份 高产量农
田农作物
产量/万t		 低产量农
田农作物
产量/万t		 森林碳
储存/
万t		 城市建设
用地面
积/km2		 农村建设
用地面
积/km2
2010年 95.64 70.52 1 509.02 210.59 901.04
2011年 95.49 70.59 1 507.28 219.82 910.42
2012年 95.34 70.67 1 505.53 229.05 919.79
2013年 95.18 70.75 1 503.79 238.28 929.17
2014年 95.03 70.82 1 502.05 247.51 938.54
2015年 94.88 70.89 1 500.31 256.74 947.92
Tab.4  Land use demand of research areas from 2010 to 2015
Fig.4  Contrast map of land use simulation results in the study area in 2015
土地利用类型 Kappa 土地利用类型 Kappa
高产量农田 0.84 城市建设用地 0.82
低产量农田 0.82 农村建设用地 0.90
林地 0.87 水域 0.98
草地 0.93 其他用地 0.88
所有地类 0.88
Tab.5  Kappa algorithm test results
情景 土地利用类型 高产量农田 低产量农田 林地 草地 城市建设用地 农村建设用地 水域 其他用地
经济发展 高产量农田 1 1 1 1 1 1 1 1
低产量农田 1 1 1 1 1 1 1 1
林地 1 1 1 1 1 1 1 1
草地 1 1 1 1 1 1 1 1
城市建设用地 0 0 0 0 1 1 0 0
农村建设用地 0 0 0 0 1 1 0 0
水域 1 1 1 1 1 1 1 1
其他用地 1 1 1 1 1 1 0 1
弹性系数 0.7 0.6 0.6 0.5 1 1 0.6 0.7
土地利用优化 高产量农田 1 1 1 0 1 1 1 1
低产量农田 1 1 1 0 1 1 1 1
林地 1 1 1 1 1 1 1 0
草地 1 1 1 1 1 1 1 1
城市建设用地 0 0 0 0 1 1 0 0
农村建设用地 0 0 0 0 1 1 0 0
水域 1 1 1 1 1 1 1 0
其他用地 1 1 1 1 1 1 1 1
弹性系数 0.9 0.9 0.8 0.6 0.9 0.9 0.7 0.8
Tab.6  Transfer matrix between different land use types
土地利用
服务需求		 高产量农田
农作物产量		 低产量农田
农作物产量		 森林碳
储量		 城市建设
用地面积		 农村建设
用地面积
自然增长 -0.2 0.11 -0.11 4 1
经济发展 -0.3 0.4 -0.4 6.5 1.5
土地利用优化 -0.1 0.5 2 3.5 1
Tab.7  Change rate of land use service demand under different situations(%)
Fig.5  Land use type change in three scenarios from 2015 to 2025
Fig.6  Land use change simulation maps of three scenarios in the study area in 2025
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