Publication detail
Research on Classification Method of Building Function Oriented to Urban Building Stock Management
Xiao, Bing Jia, Xuexiu Yang, Dong Sun, Lingwen Shi, Feng Wang, Qitong Jia, Yongfei
English title
Research on Classification Method of Building Function Oriented to Urban Building Stock Management
Type
journal article in Web of Science
Language
en
Original abstract
With the development of human society, the urban population and the urban building stock have been continuously increasing. Environmental issues such as greenhouse gases emissions, air pollution, and construction waste have gradually emerged. Due to the lack of an urban functional area database, it is very time-consuming to manually identify building functional areas. As a result, most of the current research on urban building functions are estimated at a large regional scale or only detailed calculations of individual buildings. The building functions classification method needs to be further improved. Based on the traditional methods, this paper proposes a building function classification method with higher recognition accuracy and is less time-consuming. The method is then applied to a certain area of Chaoyang District, Beijing, for validation and verification. The results show that the urban building function classification method in this paper has a recognition rate of 96.18%, an overall classification accuracy of 94.37%, and a kappa coefficient of 0.9089. The classification results are in good agreement with the virtual interpretation. In addition, automatic classification of building functions is implemented using ArcPy in ArcGIS, which significantly improves the classification efficiency.
English abstract
With the development of human society, the urban population and the urban building stock have been continuously increasing. Environmental issues such as greenhouse gases emissions, air pollution, and construction waste have gradually emerged. Due to the lack of an urban functional area database, it is very time-consuming to manually identify building functional areas. As a result, most of the current research on urban building functions are estimated at a large regional scale or only detailed calculations of individual buildings. The building functions classification method needs to be further improved. Based on the traditional methods, this paper proposes a building function classification method with higher recognition accuracy and is less time-consuming. The method is then applied to a certain area of Chaoyang District, Beijing, for validation and verification. The results show that the urban building function classification method in this paper has a recognition rate of 96.18%, an overall classification accuracy of 94.37%, and a kappa coefficient of 0.9089. The classification results are in good agreement with the virtual interpretation. In addition, automatic classification of building functions is implemented using ArcPy in ArcGIS, which significantly improves the classification efficiency.
Keywords in English
urban building stock; building function classification; POI data
Released
12.05.2022
Publisher
MDPI
Location
Basel
ISSN
2071-1050
Book
Sustainability
Volume
14
Number
10
Edition number
14
Pages count
10
BIBTEX
@article{BUT182559,
author="Xuexiu {JIA},
title="Research on Classification Method of Building Function Oriented to Urban Building Stock Management",
booktitle="Sustainability
",
year="2022",
volume="14",
number="10",
month="May",
publisher="MDPI",
address="Basel
",
issn="2071-1050"
}