Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu
Urbanization increases the scales of urban spaces and the sizes of their populations, causing the functions in cities and towns to be in short supply. This study carries out functional space identification on the Dujiangyan elite irrigation area based on remote sensing data and point of interest (PO...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/11/3/386 |
| _version_ | 1827628672925827072 |
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| author | Qidi Dong Jun Cai Linjia Wu Di Li Qibing Chen |
| author_facet | Qidi Dong Jun Cai Linjia Wu Di Li Qibing Chen |
| author_sort | Qidi Dong |
| collection | DOAJ |
| description | Urbanization increases the scales of urban spaces and the sizes of their populations, causing the functions in cities and towns to be in short supply. This study carries out functional space identification on the Dujiangyan elite irrigation area based on remote sensing data and point of interest (POI) data from Open Street Map (OSM), enabling the use of POI data to analyze rural functional spaces. Research and development and big data can greatly improve the accuracy of spatial function recognition, but research on rural spaces has limitations regarding the amount of available data. The Dujiangyan Irrigation District has low spatial aggregation levels for functions, scattered functions and linear distributions along roads. The mixing degrees of regional functions are low, the connections between functional elements are insufficient, and the comprehensive functional quality is low. The features of various functional elements in the region are significant, mostly in the discrete distribution mode, and functional compounding has become a trend. Therefore, it is necessary to integrate spatial resources and improve the centrality of cities and towns to realize the optimal allocation of resources and enable the development of surrounding cities and towns. |
| first_indexed | 2024-03-09T13:36:45Z |
| format | Article |
| id | doaj.art-1d9658c873a348a0a38d14e7adb768d8 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T13:36:45Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-1d9658c873a348a0a38d14e7adb768d82023-11-30T21:11:10ZengMDPI AGLand2073-445X2022-03-0111338610.3390/land11030386Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in ChengduQidi Dong0Jun Cai1Linjia Wu2Di Li3Qibing Chen4College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, ChinaCollege of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, ChinaCollege of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, ChinaCollege of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, ChinaCollege of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, ChinaUrbanization increases the scales of urban spaces and the sizes of their populations, causing the functions in cities and towns to be in short supply. This study carries out functional space identification on the Dujiangyan elite irrigation area based on remote sensing data and point of interest (POI) data from Open Street Map (OSM), enabling the use of POI data to analyze rural functional spaces. Research and development and big data can greatly improve the accuracy of spatial function recognition, but research on rural spaces has limitations regarding the amount of available data. The Dujiangyan Irrigation District has low spatial aggregation levels for functions, scattered functions and linear distributions along roads. The mixing degrees of regional functions are low, the connections between functional elements are insufficient, and the comprehensive functional quality is low. The features of various functional elements in the region are significant, mostly in the discrete distribution mode, and functional compounding has become a trend. Therefore, it is necessary to integrate spatial resources and improve the centrality of cities and towns to realize the optimal allocation of resources and enable the development of surrounding cities and towns.https://www.mdpi.com/2073-445X/11/3/386big datafunction recognitionspatial planningDujiangyanIrrigation district |
| spellingShingle | Qidi Dong Jun Cai Linjia Wu Di Li Qibing Chen Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu Land big data function recognition spatial planning Dujiangyan Irrigation district |
| title | Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu |
| title_full | Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu |
| title_fullStr | Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu |
| title_full_unstemmed | Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu |
| title_short | Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu |
| title_sort | quantitative identification of rural functions based on big data a case study of dujiangyan irrigation district in chengdu |
| topic | big data function recognition spatial planning Dujiangyan Irrigation district |
| url | https://www.mdpi.com/2073-445X/11/3/386 |
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