{"title":"将绿地措施纳入中国浙江未来城镇规划","authors":"Yuanzhao Wang, ChengHe Guan","doi":"10.1177/23998083241274913","DOIUrl":null,"url":null,"abstract":"Various spatial indices have been used by scholars to evaluate the built environment of towns. However, previous analysis has fallen short in systematically addressing the distribution of green space in future town planning. This paper fills the gap by integrating green space indices in an expanded urban intensity framework and comparing existing conditions (2018) and future planning schemes (2030) of eleven towns in Zhejiang Province, China. In this paper, we computed spatial indices in ARCGIS and FRAGSTATS, used correlation analysis in STATA for statistical analysis, and adopted demographic, economic, and environmental variables to validate the selected indices. The results show that: (1) The future planning schemes can result in either reduction of green spaces in town centers or uneven distribution of green spaces; (2) Validation of green space indicators reveals observable association with the normalized difference vegetation index (NDVI), which implies that the chosen framework can effectively reflect the condition of greenery; and (3) The regulatory detailed planning does not always improve the future spatial layout of towns, especially after considering green space distributions. These findings emphasize the importance of suitable spatial layouts of green spaces over large monolithic blocks for effective planning. Moreover, achieving optimal urban intensity necessitates a balanced distribution of the built and green spaces. Finally, the integration of green space factors and the adoption of a comprehensive approach, as highlighted in this study, can serve as a valuable guide for town planners and policymakers in different jurisdictions to achieve more desirable spatial layouts.","PeriodicalId":11863,"journal":{"name":"Environment and Planning B: Urban Analytics and City Science","volume":"41 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating green space measures into future town planning in Zhejiang, China\",\"authors\":\"Yuanzhao Wang, ChengHe Guan\",\"doi\":\"10.1177/23998083241274913\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Various spatial indices have been used by scholars to evaluate the built environment of towns. However, previous analysis has fallen short in systematically addressing the distribution of green space in future town planning. This paper fills the gap by integrating green space indices in an expanded urban intensity framework and comparing existing conditions (2018) and future planning schemes (2030) of eleven towns in Zhejiang Province, China. In this paper, we computed spatial indices in ARCGIS and FRAGSTATS, used correlation analysis in STATA for statistical analysis, and adopted demographic, economic, and environmental variables to validate the selected indices. The results show that: (1) The future planning schemes can result in either reduction of green spaces in town centers or uneven distribution of green spaces; (2) Validation of green space indicators reveals observable association with the normalized difference vegetation index (NDVI), which implies that the chosen framework can effectively reflect the condition of greenery; and (3) The regulatory detailed planning does not always improve the future spatial layout of towns, especially after considering green space distributions. These findings emphasize the importance of suitable spatial layouts of green spaces over large monolithic blocks for effective planning. Moreover, achieving optimal urban intensity necessitates a balanced distribution of the built and green spaces. Finally, the integration of green space factors and the adoption of a comprehensive approach, as highlighted in this study, can serve as a valuable guide for town planners and policymakers in different jurisdictions to achieve more desirable spatial layouts.\",\"PeriodicalId\":11863,\"journal\":{\"name\":\"Environment and Planning B: Urban Analytics and City Science\",\"volume\":\"41 1\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environment and Planning B: Urban Analytics and City Science\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1177/23998083241274913\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environment and Planning B: Urban Analytics and City Science","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1177/23998083241274913","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Integrating green space measures into future town planning in Zhejiang, China
Various spatial indices have been used by scholars to evaluate the built environment of towns. However, previous analysis has fallen short in systematically addressing the distribution of green space in future town planning. This paper fills the gap by integrating green space indices in an expanded urban intensity framework and comparing existing conditions (2018) and future planning schemes (2030) of eleven towns in Zhejiang Province, China. In this paper, we computed spatial indices in ARCGIS and FRAGSTATS, used correlation analysis in STATA for statistical analysis, and adopted demographic, economic, and environmental variables to validate the selected indices. The results show that: (1) The future planning schemes can result in either reduction of green spaces in town centers or uneven distribution of green spaces; (2) Validation of green space indicators reveals observable association with the normalized difference vegetation index (NDVI), which implies that the chosen framework can effectively reflect the condition of greenery; and (3) The regulatory detailed planning does not always improve the future spatial layout of towns, especially after considering green space distributions. These findings emphasize the importance of suitable spatial layouts of green spaces over large monolithic blocks for effective planning. Moreover, achieving optimal urban intensity necessitates a balanced distribution of the built and green spaces. Finally, the integration of green space factors and the adoption of a comprehensive approach, as highlighted in this study, can serve as a valuable guide for town planners and policymakers in different jurisdictions to achieve more desirable spatial layouts.