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A sustainable development perspective on urban-scale roof greening priorities and benefits

Jie Shao, Wei Yao, Lei Luo, Linzhou Zeng, Zhiyi He, Puzuo Wang, Huadong Guo

TL;DR

This study develops a reproducible, data-driven framework to prioritize roof greening at the building scale in Hong Kong, integrating geospatial big data across environmental, socioeconomic, and climatic indicators. It finds that about 85% of buildings have retrofit potential, with a total feasible area ~63.9 km^2 and substantial potential gains in greenspace exposure, alongside measurable but modest impacts on urban heat and carbon offsets. The analysis highlights significant economic benefits (~HK$318 million per year) driven by energy savings and carbon mechanisms, while emphasizing constraints from building age and urban microclimates. The approach offers a transferable methodology for urban planners seeking to leverage roof greening as a component of sustainable city development, and it underscores the importance of equitable access to greenspace through integrated planning and policy.

Abstract

Greenspaces are tightly linked to human well-being. Yet, rapid urbanization has exacerbated greenspace exposure inequality and declining human life quality. Roof greening has been recognized as an effective strategy to mitigate these negative impacts. Understanding priorities and benefits is crucial to promoting green roofs. Here, using geospatial big data, we conduct an urban-scale assessment of roof greening at a single building level in Hong Kong from a sustainable development perspective. We identify that 85.3\% of buildings reveal potential and urgent demand for roof greening. We further find green roofs could increase greenspace exposure by \textasciitilde61\% and produce hundreds of millions (HK\$) in economic benefits annually but play a small role in urban heat mitigation (\textasciitilde0.15\degree{C}) and annual carbon emission offsets (\textasciitilde0.8\%). Our study offers a comprehensive assessment of roof greening, which could provide reference for sustainable development in cities worldwide, from data utilization to solutions and findings.

A sustainable development perspective on urban-scale roof greening priorities and benefits

TL;DR

This study develops a reproducible, data-driven framework to prioritize roof greening at the building scale in Hong Kong, integrating geospatial big data across environmental, socioeconomic, and climatic indicators. It finds that about 85% of buildings have retrofit potential, with a total feasible area ~63.9 km^2 and substantial potential gains in greenspace exposure, alongside measurable but modest impacts on urban heat and carbon offsets. The analysis highlights significant economic benefits (~HK$318 million per year) driven by energy savings and carbon mechanisms, while emphasizing constraints from building age and urban microclimates. The approach offers a transferable methodology for urban planners seeking to leverage roof greening as a component of sustainable city development, and it underscores the importance of equitable access to greenspace through integrated planning and policy.

Abstract

Greenspaces are tightly linked to human well-being. Yet, rapid urbanization has exacerbated greenspace exposure inequality and declining human life quality. Roof greening has been recognized as an effective strategy to mitigate these negative impacts. Understanding priorities and benefits is crucial to promoting green roofs. Here, using geospatial big data, we conduct an urban-scale assessment of roof greening at a single building level in Hong Kong from a sustainable development perspective. We identify that 85.3\% of buildings reveal potential and urgent demand for roof greening. We further find green roofs could increase greenspace exposure by \textasciitilde61\% and produce hundreds of millions (HK\$) in economic benefits annually but play a small role in urban heat mitigation (\textasciitilde0.15\degree{C}) and annual carbon emission offsets (\textasciitilde0.8\%). Our study offers a comprehensive assessment of roof greening, which could provide reference for sustainable development in cities worldwide, from data utilization to solutions and findings.
Paper Structure (11 sections, 6 equations, 5 figures)

This paper contains 11 sections, 6 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Results
  3. Roof greening priorities
  4. Roof greening benefits
  5. Discussion
  6. Methods
  7. Research design
  8. Environmental data
  9. Extraction of building attributes
  10. Measurement of indicator and priority
  11. Benefit evaluation of green roofs

Figures (5)

  • Figure 1: $\vert$ Potential green roofs in Hong Kong. A combination of roof geometric properties (slope and area) and building age was used to identify potential green roofs, where buildings with roof slopes exceeding 15 degrees, areas smaller than 10 m$^2$, or those older than 60 years are deemed unsuitable for greening retrofit.
  • Figure 2: $\vert$ Roof greening indicators in Hong Kong.a, Greenspace coverage rate within a 500-meter horizontal radius of buildings. b, The horizontal distance of the building to the nearest main road. c, Distribution of building categories. d, Median monthly income distribution by interpolating the income of 540 housing estates and all districts in 2021. e1-e4, The surface temperature by season in 2021 derived from multi-temporal Landsat-8 images (e1: spring; e2: summer; e3: autumn; e4: winter). f, Precipitation distribution in Hong Kong obtained by interpolating records from 139 weather stations in 2021.
  • Figure 3: $\vert$ Roof greening priorities in Hong Kong.a, Distribution of roof greening priority, the greening priority is almost all above 0.7 in Kowloon Peninsula, varies between 0.6 and 0.75 in Hong Kong Island, and mainly distributes below 0.7 in New Territories. b, Boxplot depicting the distribution of priority values across each district.
  • Figure 4: $\vert$ Simulation of air temperature at 2 meters above the ground for the four seasons.a, The distribution of air temperature before and after roof greening, as well as their difference. b, The daily temperature variation under bare roof (BR) and green roof (GR) conditions. c, Temperature reduced by green roofs.
  • Figure 5: $\vert$ The correlation (c) between monthly income (a) and greenspace coverage rate (b) of buildings.a, The income data used in this analysis is derived from the monthly median income of 540 housing estates in 2021, according to Hong Kong government statistics. b, The greenspace coverage rate refers to the proportion of greenspace coverage area within a 500-meter horizontal radius of the building.