Version 1
: Received: 29 May 2024 / Approved: 30 May 2024 / Online: 30 May 2024 (08:49:29 CEST)
Version 2
: Received: 23 July 2024 / Approved: 23 July 2024 / Online: 23 July 2024 (15:57:04 CEST)
How to cite:
Xu, Z.; Tang, S.; Wang, X.; Chen, Y.; Luo, H. Greenness evaluation of rural residential buildings based on the composite perspective of Environment-Building-Resources. Preprints2024, 2024052021. https://doi.org/10.20944/preprints202405.2021.v2
Xu, Z.; Tang, S.; Wang, X.; Chen, Y.; Luo, H. Greenness evaluation of rural residential buildings based on the composite perspective of Environment-Building-Resources. Preprints 2024, 2024052021. https://doi.org/10.20944/preprints202405.2021.v2
Xu, Z.; Tang, S.; Wang, X.; Chen, Y.; Luo, H. Greenness evaluation of rural residential buildings based on the composite perspective of Environment-Building-Resources. Preprints2024, 2024052021. https://doi.org/10.20944/preprints202405.2021.v2
APA Style
Xu, Z., Tang, S., Wang, X., Chen, Y., & Luo, H. (2024). Greenness evaluation of rural residential buildings based on the composite perspective of Environment-Building-Resources. Preprints. https://doi.org/10.20944/preprints202405.2021.v2
Chicago/Turabian Style
Xu, Z., Yuhao Chen and Hangyu Luo. 2024 "Greenness evaluation of rural residential buildings based on the composite perspective of Environment-Building-Resources" Preprints. https://doi.org/10.20944/preprints202405.2021.v2
Abstract
Based on the composite perspective of environment-building-resource(EBR), influencing factors of the greenness of rural buildings were sorted out by brainstorming and expert consultation, an innovative comprehensive evaluation system was constructed and the weight ofthe impact factors were calculated by fuzzy analytic network process(FANP). The EBR greenness comprehensive scoring standards of each influence factor were established by means of questionnaire, field measurement and numerical simulation. As a typical representative of human populated areas in southwest China, 13 villages in the second circle of Chengdu were selected as case study areas by means of the regional average distribution theory and minimum sampling criteria. Innovative combination of obstacle degree model and spatial interpolation analysis, the key factors affecting the greening of rural buildings were diagnosed. The results showed that, indoor thermal environment(E21), indoor light environment(E22), popularity of biogas facilities (R12), green building material usage(R13) have a significant impact on the EBR greenness score. The EBR score of study area shows a spatial distribution pattern of high in the west and low in the east, with extremely uneven scores in various dimensions. According to the key factors obtained from the systematic evaluation, the refined exploration of promotion strategies and measures was carried out, the greenness improvement suggestion was put forward.
Keywords
Rural residential building; Building greenness score; Fuzzy analytic network process (FANP); Obstacle degree analysis
Subject
Engineering, Architecture, Building and Construction
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
