Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, China
High-quality urban green space (UGS) is an integral part of a livable city. The scientific evaluation of UGS has great value for improving the quality and efficiency of green spaces. In this study, we integrated the water and walking networks into the existing green index model and proposed a new gr...
| Main Authors: | , , , |
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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/11/3/445 |
| _version_ | 1797446141518807040 |
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| author | Zhiming Li Xiyang Chen Zhou Shen Zhengxi Fan |
| author_facet | Zhiming Li Xiyang Chen Zhou Shen Zhengxi Fan |
| author_sort | Zhiming Li |
| collection | DOAJ |
| description | High-quality urban green space (UGS) is an integral part of a livable city. The scientific evaluation of UGS has great value for improving the quality and efficiency of green spaces. In this study, we integrated the water and walking networks into the existing green index model and proposed a new green index: the building blue–green index (BBGI). Using this method, we analyzed the quality of green spaces within 300 m of 2138 buildings located in 13 communities in the Mochou Lake subdistrict in Nanjing, China. The results revealed that the green-space quality of high-rise, low-density buildings was greater than that of low-rise, high-density buildings. In addition, buildings close to water had higher green-space quality, while impervious surfaces reduced green-space quality. Furthermore, the connectivity and orientation of the road network indicated that even if a community was close to large parks and water bodies, there would still be lower green-space quality. This study’s findings highlight the usefulness of evaluation methods for green-space quality that combine blue and green spaces. We also propose feasible measures for improving neighborhood green-space planning and land management. |
| first_indexed | 2024-03-09T13:35:56Z |
| format | Article |
| id | doaj.art-52162de476a943138d89558357315df4 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T13:35:56Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-52162de476a943138d89558357315df42023-11-30T21:11:59ZengMDPI AGLand2073-445X2022-03-0111344510.3390/land11030445Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, ChinaZhiming Li0Xiyang Chen1Zhou Shen2Zhengxi Fan3College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, ChinaCollege of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, ChinaSuzhou Polytechnic Institute of Agriculture, Suzhou 215008, ChinaSchool of Architecture, Southeast University, Nanjing 210096, ChinaHigh-quality urban green space (UGS) is an integral part of a livable city. The scientific evaluation of UGS has great value for improving the quality and efficiency of green spaces. In this study, we integrated the water and walking networks into the existing green index model and proposed a new green index: the building blue–green index (BBGI). Using this method, we analyzed the quality of green spaces within 300 m of 2138 buildings located in 13 communities in the Mochou Lake subdistrict in Nanjing, China. The results revealed that the green-space quality of high-rise, low-density buildings was greater than that of low-rise, high-density buildings. In addition, buildings close to water had higher green-space quality, while impervious surfaces reduced green-space quality. Furthermore, the connectivity and orientation of the road network indicated that even if a community was close to large parks and water bodies, there would still be lower green-space quality. This study’s findings highlight the usefulness of evaluation methods for green-space quality that combine blue and green spaces. We also propose feasible measures for improving neighborhood green-space planning and land management.https://www.mdpi.com/2073-445X/11/3/445urban green spacebuilding blue–green indexneighborhoodhigh-resolution remoting-sensing imagenetwork analysisChina |
| spellingShingle | Zhiming Li Xiyang Chen Zhou Shen Zhengxi Fan Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, China Land urban green space building blue–green index neighborhood high-resolution remoting-sensing image network analysis China |
| title | Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, China |
| title_full | Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, China |
| title_fullStr | Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, China |
| title_full_unstemmed | Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, China |
| title_short | Evaluating Neighborhood Green-Space Quality Using a Building Blue–Green Index (BBGI) in Nanjing, China |
| title_sort | evaluating neighborhood green space quality using a building blue green index bbgi in nanjing china |
| topic | urban green space building blue–green index neighborhood high-resolution remoting-sensing image network analysis China |
| url | https://www.mdpi.com/2073-445X/11/3/445 |
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