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The identification and efficiency evaluation of industrial parcels by integrating multi-source spatial data in Shenzhen, South China

Authors :
Danyang Wang
Xianjin Huang
Lifeng Shi
Hong Yang
Weidong Sun
Source :
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
Publication Year :
2024
Publisher :
Taylor & Francis Group, 2024.

Abstract

ABSTRACTIndustrial land status, encompassing quantity, distribution and efficiency, is pivotal in urban planning and sustainable development. However, obtaining detailed and up-to-date industrial land maps poses a significant challenge in many developing countries due to rapid urban expansion. Furthermore, the identification and efficiency assessment of industrial land at the parcel scale are rarely undertaken. To address these challenges, our study proposes an innovative approach to map industrial land, categorize its types and assess its efficiency at the parcel scale. We select Shenzhen, one of China’s largest industrial cities, as a case study to demonstrate the effectiveness of our method. Our results unveil several key findings: (1) Shenzhen’s urban area was meticulously segmented into 15,591 multi-size socio-economic parcels, of which 5,738 were identified as industrial parcels (IPs); (2) IPs were further categorized into three distinct types: office industrial parcels at 69.47%, manufacturing industrial parcels at (6.08%) and comprehensive industrial parcels at 24.45%; (3) Their efficiency was classified into four levels: low (20.30%), middle (35.73%), fine (35.97%) and high (8.00%). Efficient IPs were predominately concentrated in the southwest, whereas other IPs clustered in the northwest. Our findings can provide valuable insights into industrial land identification, classification and efficiency evaluation at parcel scale.

Details

Language :
English
ISSN :
15481603 and 19437226
Volume :
61
Issue :
1
Database :
Directory of Open Access Journals
Journal :
GIScience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.7300e1283db945f8843d124f53dec6db
Document Type :
article
Full Text :
https://doi.org/10.1080/15481603.2024.2344405