Spatial Distribution and Driving Forces of the Vegetable Industry in China
Based on the ArcGIS geostatistical analysis method, this study offers a visualization of the spatial distribution pattern and spatial trend of vegetable production in China. The research also examines the degree of spatial agglomeration patterns of vegetable production by using the standard deviatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Land |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-445X/11/7/981 |
| _version_ | 1797445869884145664 |
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| author | Hongru Wang Jun He Noshaba Aziz Yue Wang |
| author_facet | Hongru Wang Jun He Noshaba Aziz Yue Wang |
| author_sort | Hongru Wang |
| collection | DOAJ |
| description | Based on the ArcGIS geostatistical analysis method, this study offers a visualization of the spatial distribution pattern and spatial trend of vegetable production in China. The research also examines the degree of spatial agglomeration patterns of vegetable production by using the standard deviation ellipse technique and exploratory spatial data analysis method. In addition, we employ the spatial regression model partial differential method to explore the driving factors leading to the changing layout of vegetable production. The findings unveil that vegetable production in China exhibit strong spatial non-equilibrium characteristics, with “high-high” and “low-low” types as the main agglomeration patterns. Furthermore, the location distribution shows a northeast–southwest orientation with the center of gravity of distribution gradually directed toward the southwest. Regarding driving factors, the results show that the effective irrigated area of natural factors had a facilitating effect on the layout of vegetable production, while the affected area had an inhibiting effect on it. Climate indicators such as temperature, precipitation and light show different degrees of influence on the layout of vegetable production. The level of urbanization and transportation conditions have a negative impact on the layout of production in the region. Market demand has a positive spillover effect on the layout of local vegetable production, while it has a negative spillover effect on other regions. Technological progress shows positive spillover effects on the layout of vegetable production in the region and other regions. Financial support policy also shows positive effects from an overall perspective. |
| first_indexed | 2024-03-09T13:32:01Z |
| format | Article |
| id | doaj.art-4835c9e2cf5946e599cfed2122ebfb08 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T13:32:01Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-4835c9e2cf5946e599cfed2122ebfb082023-11-30T21:16:10ZengMDPI AGLand2073-445X2022-06-0111798110.3390/land11070981Spatial Distribution and Driving Forces of the Vegetable Industry in ChinaHongru Wang0Jun He1Noshaba Aziz2Yue Wang3College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, ChinaCollege of Economics and Management, Nanjing Agricultural University, Nanjing 210095, ChinaCollege of Economics and Management, Nanjing Agricultural University, Nanjing 210095, ChinaInstitute of Agricultural Economics and Development, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, ChinaBased on the ArcGIS geostatistical analysis method, this study offers a visualization of the spatial distribution pattern and spatial trend of vegetable production in China. The research also examines the degree of spatial agglomeration patterns of vegetable production by using the standard deviation ellipse technique and exploratory spatial data analysis method. In addition, we employ the spatial regression model partial differential method to explore the driving factors leading to the changing layout of vegetable production. The findings unveil that vegetable production in China exhibit strong spatial non-equilibrium characteristics, with “high-high” and “low-low” types as the main agglomeration patterns. Furthermore, the location distribution shows a northeast–southwest orientation with the center of gravity of distribution gradually directed toward the southwest. Regarding driving factors, the results show that the effective irrigated area of natural factors had a facilitating effect on the layout of vegetable production, while the affected area had an inhibiting effect on it. Climate indicators such as temperature, precipitation and light show different degrees of influence on the layout of vegetable production. The level of urbanization and transportation conditions have a negative impact on the layout of production in the region. Market demand has a positive spillover effect on the layout of local vegetable production, while it has a negative spillover effect on other regions. Technological progress shows positive spillover effects on the layout of vegetable production in the region and other regions. Financial support policy also shows positive effects from an overall perspective.https://www.mdpi.com/2073-445X/11/7/981spatial distributionspatial agglomerationstandard deviation ellipsespatial regression model partial differential method |
| spellingShingle | Hongru Wang Jun He Noshaba Aziz Yue Wang Spatial Distribution and Driving Forces of the Vegetable Industry in China Land spatial distribution spatial agglomeration standard deviation ellipse spatial regression model partial differential method |
| title | Spatial Distribution and Driving Forces of the Vegetable Industry in China |
| title_full | Spatial Distribution and Driving Forces of the Vegetable Industry in China |
| title_fullStr | Spatial Distribution and Driving Forces of the Vegetable Industry in China |
| title_full_unstemmed | Spatial Distribution and Driving Forces of the Vegetable Industry in China |
| title_short | Spatial Distribution and Driving Forces of the Vegetable Industry in China |
| title_sort | spatial distribution and driving forces of the vegetable industry in china |
| topic | spatial distribution spatial agglomeration standard deviation ellipse spatial regression model partial differential method |
| url | https://www.mdpi.com/2073-445X/11/7/981 |
| work_keys_str_mv | AT hongruwang spatialdistributionanddrivingforcesofthevegetableindustryinchina AT junhe spatialdistributionanddrivingforcesofthevegetableindustryinchina AT noshabaaziz spatialdistributionanddrivingforcesofthevegetableindustryinchina AT yuewang spatialdistributionanddrivingforcesofthevegetableindustryinchina |