Understanding the relationship between 2D and 3D green indices holds significant implications for governance, especially amid the escalating demand for urban green spaces during rapid urbanization. However, the existing studies reveal inconsistent results pertaining to the relationships between 2D and 3D green indices and lack a systematic examination of spatial attributes' influence on the relationships. This study addresses these gaps by 1) assessing the correlation between 2D and 3D green indices using high-resolution data, 2) identifying spatial attributes that alter the 2D-3D association, and 3) determining the thresholds of spatial attributes that significantly impact the 2D-3D relationships. The Moderation Model was initially introduced to evaluate the mechanisms within its respective field. High-resolution data was collected from a campus, focusing on key spatial attributes: tree cover density (TC), plot ratio (PR), and vegetation composition (VC). NDVI and GVI were chosen to represent the 2D and 3D green index. The results indicate a significant correlation between NDVI and GVI (R=0.478, p<0.005). TC was identified as the fundamental moderator of the association. A medium TC (32.46 %) was the threshold for a significant NDVI - GVI correlation. Only at low TC (0–10.82 %), interactive effects between spatial attributes were observed: VC (type (e)) substituted NDVI to affect GVI directly; Above a PR of 1.95, the correlation between NDVI and GVI diminishes. In general, NDVI cannot substitutes GVI in areas where TC is higher than 32.46 %, or in areas where TC is lower than 10.82 % with many tall buildings (higher than 8 floors). The findings innovatively reveal the dynamic variation and thresholds in the 2D-3D green index relationships based on site-specific attributes rather than the resolution of data. Practically, a decision-making tree of green index governance is then proposed for relevant stakeholders to choose according to different site conditions.

中文翻译：

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在高空间分辨率下，空间属性改变的 2D 和 3D 绿色指数之间的关系


了解 2D 和 3D 绿色指数之间的关系对治理具有重要意义，尤其是在快速城市化期间对城市绿色空间的需求不断增长的情况下。然而，现有的研究揭示了与 2D 和 3D 绿色指数之间关系有关的不一致结果，并且缺乏对空间属性对关系影响的系统检查。本研究通过以下方式解决了这些差距：1） 使用高分辨率数据评估 2D 和 3D 绿色指数之间的相关性，2） 识别改变 2D-3D 关联的空间属性，以及 3） 确定显著影响 2D-3D 关系的空间属性阈值。调节模型最初是为了评估其各自领域的机制而引入的。从校园收集了高分辨率数据，重点关注关键空间属性：树木覆盖密度 （TC）、容积率 （PR） 和植被组成 （VC）。选择 NDVI 和 GVI 来表示 2D 和 3D 绿色指数。结果表明 NDVI 与 GVI 之间存在显著相关性 （R=0.478，p<0.005）。TC 被确定为该协会的基本调节者。中等 TC （32.46 %） 是显著 NDVI - GVI 相关性的阈值。仅在低 TC （0–10.82 %） 下，观察到空间属性之间的交互效应：VC（类型 （e））替换 NDVI 直接影响 GVI;PR 高于 1.95，NDVI 和 GVI 之间的相关性减弱。一般来说，NDVI 不能在 TC 高于 32.46 % 的地区或 TC 低于 10.82% 且高层建筑众多（高于 8 层）的地区替代 GVI。 研究结果创新性地揭示了基于站点特定属性而不是数据分辨率的 2D-3D 绿色指数关系中的动态变化和阈值。在实践中，提出了绿色指数治理的决策树，供相关利益相关者根据不同的立地条件进行选择。