Quantitative Identification of Rural Functions Based on Big Data: A Case Study of Dujiangyan Irrigation District in Chengdu

Qidi Dong, Jun Cai, Linjia Wu, Di Li and Qibing Chen
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Qidi Dong: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Jun Cai: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Linjia Wu: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Di Li: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Qibing Chen: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China

Land, 2022, vol. 11, issue 3, 1-17

Abstract: 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.

Keywords: big data; function recognition; spatial planning; Dujiangyan; Irrigation district (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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