Revealing the spatial patterns of differentiation and the driving mechanism of agricultural multifunctional patterns is an important aspect of coordinating the functional optimisation and coordinated development of different agricultural regions. On the basis of understanding the connotation of agricultural multiple functions, this paper constructed an evaluation index system of agricultural multiple functions. Taking Jiangsu Province as a typical case, the spatial patterns of agricultural multifunctions in Jiangsu since 1978 were analysed by using the entropy weight TOPSIS (technique for order preference by similarity to ideal solution) method and ESDA (exploratory spatial data analysis) model, and the influencing mechanism of agricultural multifunction spatial differentiation was revealed by a geographic detector model. The results showed that (1) the cities with higher agricultural grain production functions were mainly concentrated in Yancheng and Huai'an; cities with higher agricultural economic development functions were mainly distributed in the coastal areas of Jiangsu; cities with higher agricultural social security functions were mainly concentrated in the Suzhou-Wuxi-Changzhou metropolitan area; and cities with higher agricultural ecotourism functions evolved from Nanjing-Zhenjiang to Suzhou-Wuxi-Changzhou. (2) The H-H (high-high) cluster pattern of the agricultural grain production function shifted from southern Jiangsu to northern Jiangsu. The H-H clusters of the agricultural economic development function and social security function were mainly distributed in Suzhou-Wuxi-Changzhou, while the L-L (low-low) cluster was mainly distributed in northern Jiangsu. The H-H cluster of agricultural ecotourism functions was mainly distributed in the areas with rich mountain and hill resources or dense water networks in Jiangsu. (3) The agricultural multifunction pattern differentiation was affected by the natural environment and economic and social comprehensive factors; the level of economic development and population employment structure were the leading factors of agricultural multifunction spatial differentiation; industry structure and people's living conditions were the important driving forces of agricultural multifunction spatial differentiation; and the natural environment and population density were the basic factors underlying agricultural multifunction spatial differentiation.
机构:
Beijing Normal Univ, Sch Govt, Beijing, Peoples R ChinaBeijing Normal Univ, Sch Govt, Beijing, Peoples R China
Zhou, Xiaoping
Xiao, Longkai
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Beijing Normal Univ, Sch Govt, Beijing, Peoples R ChinaBeijing Normal Univ, Sch Govt, Beijing, Peoples R China
Xiao, Longkai
Lu, Xiao
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Qufu Normal Univ, Coll Geog & Tourism, Rizhao 276826, Shandong, Peoples R China
Northeastern Univ, Coll Humanities & Law, Shenyang, Peoples R ChinaBeijing Normal Univ, Sch Govt, Beijing, Peoples R China
Lu, Xiao
Sun, Dongqi
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Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R ChinaBeijing Normal Univ, Sch Govt, Beijing, Peoples R China
机构:
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Univ Chinese Acad Sci, Beijing 100049, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Pei, Jie
Niu, Zheng
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Univ Chinese Acad Sci, Beijing 100049, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Niu, Zheng
Wang, Li
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Hebei Univ Econ & Business, Coll Management Sci & Engn, Shijiazhuang 050061, Hebei, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Wang, Li
Song, Xiao-Peng
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Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USAChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Song, Xiao-Peng
Huang, Ni
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Huang, Ni
Geng, Jing
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Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Geng, Jing
Wu, Yan-Bin
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Hebei Univ Econ & Business, Coll Management Sci & Engn, Shijiazhuang 050061, Hebei, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
Wu, Yan-Bin
Jiang, Hong-Hui
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Key Area Planning Construct & Management Bur Long, Shenzhen 518116, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China