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Conventional metrics for evaluating equality in urban green space planning, primarily based on two-dimensional green space (2DGS) area coverage, are insufficient for characterizing the intricate distribution of green resources in three-dimensional space. These traditional measures overlook the substantial contributions of vertical vegetation structures, such as trees and shrubs, to urban ecological health, biodiversity, and aesthetic quality, potentially leading to suboptimal planning outcomes. To address this gap, this study establishes a novel analytical framework that synergizes high-precision remote sensing with advanced machine learning to enable a precise and comprehensive assessment of equality in three-dimensional green volume (3DGV) allocation, thereby supporting more integrated and effective urban green planning. The framework was implemented in the main city of Nanjing through four sequential stages: 1) 2DGS Extraction: Precise delineation of surface green coverage was achieved by applying a Support Vector Machine (SVM) classifier to high-resolution remote sensing imagery, generating an accurate foundational map for spatial analysis. 2) 3DGV Modeling and Calculation: A robust Random Forest regression model was developed to estimate 3DGV across the entire study area. This model was trained using detailed field-measured 3DGV data from sample plots and a suite of spectral vegetation indices derived from satellite data, effectively capturing non-linear relationships to ensure reliable volume inversion. 3) Accessibility-Based Equity Measurement: The equity of access to green resources was evaluated using the Two-Step Floating Catchment Area (2SFCA) method. This approach calculated the accessible 3DGV for each residential community by balancing the spatial supply of green volume with local population demand, highlighting fine-grained spatial disparities in availability. 4) Comparative Equity Analysis: The overall equity level was quantified using the Gini coefficient for accessible 3DGV, while the location quotient identified units with relative surplus or deficit. A direct comparison of equity indicators derived from 3DGV and conventional 2DGS metrics revealed the distinct analytical insights provided by the volumetric perspective. The analysis yields several key findings. First, inequalities in 2DGS distribution are amplified in the 3DGV, indicating that area-based disparities lead to even greater volumetric imbalances. Second, the dynamics of 3DGV are more complex and sensitive; it exhibits a lagged and non-linear response to significant changes in surface greenery, making its equity patterns during urbanization more volatile than those of 2DGS. This underscores the critical limitation of relying solely on planar metrics, as they mask these heightened and more sensitive volumetric inequalities. Therefore, the study concludes that achieving equitable green space allocation requires planning policies and regulatory interventions specifically designed to monitor and manage 3DGV. The proposed framework offers a multidimensional, scientifically robust basis for spatial decision-making, providing innovative methodology for advancing sustainable and just urban green environments.

, authors=Conghui ZHOU, Yuan ZONG, authorsList=Conghui ZHOU, Yuan ZONG, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281678088786395830, articleId=1281678088283079348, tenantId=1146029695717560320, journalId=1281213114968444942, language=CN, title=基于机器学习的三维绿量可达公平性演进研究, columnId=1281678083010827152, journalTitle=中国园林, columnName=风景园林理论, runingTitle=null, highlight=null, articleAbstract=

传统公平性测度聚焦于二维用地面积，无法准确反映绿色资源实际分配情况。将高精度遥感影像数据与机器学习技术结合，以南京主城区为例，通过二维绿斑提取、三维绿量测算、可达公平性衡量、公平性演进特征分析4个环节展开研究。结果显示，在无外部干预情境下，二维绿斑分布不均将加剧三维绿量分配失衡。由于三维绿量在绿色空间大幅增减时分别呈现滞后性和急剧性特征，其在城镇化进程中的公平性变化较二维绿斑更为复杂，亟须专门调控手段来保障其公平配置。该成果能为绿色空间规划决策提供多维度依据，并为规划方法改良提供新思路。

, authors=周聪惠, 宗媛, authorsList=周聪惠, 宗媛, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=hchV15B0f1DFVZ3CpbobIw==, magXml=ycrIu/msQNtH1eu020j6Wg==, pdfUrl=null, pdf=WM3U++MGLsgzeSMEFP2OQg==, pdfFileSize=5168943, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=mB7Zcj3In/oruoZmQl5aJw==, mapNumber=null, fund=null)}, authors=[Author(id=1281678088970945208, tenantId=1146029695717560320, journalId=1281213114968444942, articleId=1281678088283079348, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281678089059025593, tenantId=1146029695717560320, journalId=1281213114968444942, articleId=1281678088283079348, authorId=1281678088970945208, language=EN, stringName=Conghui ZHOU, firstName=Conghui, middleName=null, lastName=ZHOU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=null, bio={"content":"

ZHOU Conghui, male, born in 1982 in Changsha, Hunan Province, Ph.D., Professor and Doctoral Supervisor at School of Architecture, Southeast University, Nationally Certified Urban and Rural Planner, research area: theory and methods of landscape architecture planning and design (Nanjing 210096)

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ZHOU Conghui, male, born in 1982 in Changsha, Hunan Province, Ph.D., Professor and Doctoral Supervisor at School of Architecture, Southeast University, Nationally Certified Urban and Rural Planner, research area: theory and methods of landscape architecture planning and design (Nanjing 210096)

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周聪惠　1982年生/男/湖南长沙人/博士/东南大学建筑学院教授，博士生导师/国家注册城乡规划师/研究方向为风景园林规划设计理论与方法（南京 210096）

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周聪惠　1982年生/男/湖南长沙人/博士/东南大学建筑学院教授，博士生导师/国家注册城乡规划师/研究方向为风景园林规划设计理论与方法（南京 210096）

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ZONG Yuan, female, born in 1999 in Jinhua, Zhejiang Province, Master's student of Architecture, Southeast University, research area: intelligent landscape planning and design methods (Nanjing 210096)

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ZONG Yuan, female, born in 1999 in Jinhua, Zhejiang Province, Master's student of Architecture, Southeast University, research area: intelligent landscape planning and design methods (Nanjing 210096)

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宗媛　1999年生/女/浙江金华人/东南大学建筑学院硕士/研究方向为智能化景观规划设计方法（南京 210096）

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宗媛　1999年生/女/浙江金华人/东南大学建筑学院硕士/研究方向为智能化景观规划设计方法（南京 210096）

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