Identifying the drivers of land expansion and evaluating multi-scenario simulation of land use: A case study of Mashan County, China

被引:22
作者
Chen, Shuai [1 ]
Yao, Shunbo [1 ]
机构
[1] Northwest A&F Univ, Coll Econ & Management, Yangling 712100, Peoples R China
基金
中国国家自然科学基金;
关键词
Land use change; Ecological protection; Land expansion; Scenario simulation; RANDOM FOREST; CELLULAR-AUTOMATA; PREDICTION; REGRESSION; RIVER; SUPPORT; INFORMATION; CLIMATE; MODELS; COVER;
D O I
10.1016/j.ecoinf.2023.102201
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
To reduce land conflicts and improve the coordination of human activities and land use, it is crucial to conduct thorough research on sustainable land management and optimization. In this study, we introduce a new framework for identifying the drivers of land expansion and evaluating multi-scenario simulation of land use. Using Mashan County in China for a case study, the results indicate that the areas of cultivated land and grassland are gradually decreasing, while the building area is gradually increasing, the development probability of cultivated land and forest land is relatively high. Ecological land is primarily influenced by elevation, population density and temperature. In contrast, the expansion of building land is most significantly influenced by gross domestic product (GDP). The prediction result indicates that building land will continue to expand in the future, occupying more ecological space under economic development scenarios. Forest land is expected to increase under the ecological protection scenario, with the smallest expansion of building land, and cultivated land is likely to become a central area for all stakeholders. Our results suggest that adopting the ecological protection scenario is an appropriate strategy for Mashan County's sustainable development. This study provides a better understanding of the complex conflict between ecology and the economy, and offers policy insights for promoting sustainable land use.
引用
收藏
页数:12
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共 67 条
[1]   Amenity Landownership, Land Use Change, and the Re-Creation of "Working Landscapes" [J].
Abrams, Jesse ;
Bliss, John C. .
SOCIETY & NATURAL RESOURCES, 2013, 26 (07) :845-859
[2]   Prediction of spatial land use changes based on LCM in a GIS environment for Desert Wetlands - A case study: Meighan Wetland, Iran [J].
Ansari, Amir ;
Golabi, Mohammad H. .
INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH, 2019, 7 (01) :64-70
[3]   Machine learning prediction of mechanical properties of concrete: Critical review [J].
Ben Chaabene, Wassim ;
Flah, Majdi ;
Nehdi, Moncef L. .
CONSTRUCTION AND BUILDING MATERIALS, 2020, 260
[4]   Transfer payment in national key ecological functional areas and economic development: evidence from a quasi-natural experiment in China [J].
Chen, Shuai ;
Hou, Mengyang ;
Wang, Xiuying ;
Yao, Shunbo .
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024, 26 (02) :4075-4095
[5]   Change in land-use structure due to urbanisation in China [J].
Chen, Wanxu ;
Zeng, Jie ;
Li, Na .
JOURNAL OF CLEANER PRODUCTION, 2021, 321
[6]   Spatial and temporal changes in ecosystem service values in karst areas in southwestern China based on land use changes [J].
Chen, Wei ;
Zhang, Xuepeng ;
Huang, Yingshuang .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (33) :45724-45738
[7]   Urbanization, Economic Development, and Ecological Environment: Evidence from Provincial Panel Data in China [J].
Chen, Xiaofu ;
Liu, Chang ;
Yu, Xiaohua .
SUSTAINABILITY, 2022, 14 (03)
[8]   Integrating Remote Sensing and a Markov-FLUS Model to Simulate Future Land Use Changes in Hokkaido, Japan [J].
Chen, Zhanzhuo ;
Huang, Min ;
Zhu, Daoye ;
Altan, Orhan .
REMOTE SENSING, 2021, 13 (13)
[9]   Land Use Change Detection and Prediction in Upper Siem Reap River, Cambodia [J].
Chim, Kosal ;
Tunnicliffe, Jon ;
Shamseldin, Asaad ;
Ota, Tetsuji .
HYDROLOGY, 2019, 6 (03)
[10]   Climate change versus land-use change-What affects the ecosystem services more in the forest-steppe ecotone? [J].
Cui, Fengqi ;
Wang, Bojie ;
Zhang, Qin ;
Tang, Haiping ;
De Maeyer, Philippe ;
Hamdi, Rafiq ;
Dai, Luwei .
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 759