Urban Roof Research Articles

Characteristics of Atmospheric Rivers and the Impact of Urban Roof Roughness on Precipitation during the “23.7” Extreme Rainstorm against the Background of Climate Warming

In July 2023, Baoding in Hebei Province experienced unprecedented torrential rainfall, breaking historical records and causing severe flooding. However, our understanding of the multi-scale circulation systems and physical mechanisms driving this extreme precipitation event remains incomplete. This study utilizes multi-source observational data and the Weather Research and Forecasting (WRF) numerical model to conduct a weather diagnosis and numerical simulation of this extreme rainfall event, focusing on the impact of atmospheric rivers (ARS) and urban rooftop roughness on the precipitation process against the background of climate warming. The study found that this extremely heavy rainstorm occurred in the circulation background formed by the factors of subtropical high ectopics, typhoon residual vortex retention, double typhoon water-vapor transmission, and stable high-level divergence. The ARS provided abundant moisture, with its vapor pathway significantly altered following the landfall of Typhoon Doksuri. The interaction between the ARS and the Taihang Mountains was crucial in triggering and intensifying the rainstorm in the foothills. Urbanization significantly affected the distribution of precipitation, with moderate urban roughness enhancing rainfall in and around the city, whereas excessive roughness suppressed it. These results contribute to a deeper understanding of the mechanisms behind extreme precipitation under climate change and provide a scientific basis for improving the forecasting and mitigation of such events.

Identification and Derivation of Emerging Contaminants in the Roof Rainwater Confluence

To identify emerging contaminants （ECs） in rainwater is a topic that has gradually received widespread attention. Rainwater resources, specifically urban roofs, play a crucial role in utilizing rainwater efficiently by understanding the occurrence and migration characteristics of pollutants in precipitation. This study selected a typical roof and studied the differences in rainwater quality and pollution occurrence at different collection stages during six rainfall events from March to May in 2023. Principal component analysis （PCA） and correlation analysis were used to explore the distribution, migration, and transformation of ECs in the collection process of roof rainwater. The findings revealed the presence of 44/54 ECs in wet deposition, dry and wet deposition, and roof runoff processes, with a total concentration range of 63.0 to 432.4 ng·L-1 and an average concentration of 166.8 ng·L-1. Notably, bisphenol A （BPA） exhibited the highest concentration, ranging from 14.7 to 265.6 ng·L-1, with an average concentration of 62.5 ng·L-1, followed by ofloxacin （OFX） and ethylhexyl methoxycinnamate （EHMC）, with detected concentrations up to 45.5 ng·L-1 and 44.8 ng·L-1. Dissolved organic matter （DOM）, nitrogen pollutants, and particulate matter were important factors affecting the occurrence characteristics of ECs, with a mantel correlation coefficient of up to 0.98 （P<0.01）. Based on the analysis of different rainfall events and collection stages, variations were observed in the accumulation pathways and contribution ratios of different pollutants. The wet deposition exhibited the highest content of ECs in the initial stage, whereas the dry and wet deposition and roof runoff processes displayed higher ECs content in the later stages. Additionally, the average ECs contribution rates of dry and wet deposition to roof runoff were 21.48% and 78.52%, respectively. Due to the influence of roof material and surface roughness retention performance, over 30% of ECs, including pharmaceuticals and personal care products （PPCPs）, endocrine-disrupting compounds （EDCs）, and pesticides, were deposited on the roof during the runoff collection. The results of this research can provide the theoretical foundation and technical support for the identification and control of ECs in urban roof runoff and for the safe storage of rainwater.

An Attention-Based Full-Scale Fusion Network for Segmenting Roof Mask from Satellite Images

Accurately segmenting building roofs from satellite images is crucial for evaluating the photovoltaic power generation potential of urban roofs and is a worthwhile research topic. In this study, we propose an attention-based full-scale fusion (AFSF) network to segment a roof mask from the given satellite images. By developing an attention-based residual ublock, the channel relationship of the feature maps can be modeled. By integrating attention mechanisms in multi-scale feature fusion, the model can learn different weights for features of different scales. We also design a ladder-like network to utilize weakly labeled data, thereby achieving pixel-level semantic segmentation tasks assisted by image-level classification tasks. In addition, we contribute a new roof segmentation dataset, which is based on satellite images and uses the roof as the segmentation target rather than the entire building to further promote the algorithm research of estimating roof area using satellite images. The experimental results on the new roof segmentation dataset, WHU dataset, and IAIL dataset demonstrate the effectiveness of the proposed network.

Geospatial Approaches to Improve Water Availability through Demand Assessment in Agriculture Based on Treated Wastewater: A Case Study of Weinstadt, Baden-Württemberg

The sustainable management of water scarcity is a globally crucial issue. Germany has established efficient water management systems, but the agricultural sector still struggles with water scarcity as the demand surpasses the available water supply. In this work, the primary aim was to establish a framework for making water accessible for irrigation and additional use in households through the effective utilization of recycled water from wastewater treatment facilities. The research inquiries were focused on evaluating the changes in the CROPWAT agricultural irrigation model, determining the spatial distribution of zonal severity, estimating the capacity of urban roof catchments, and evaluating the economic value addition of retreated water from the existing wastewater treatment plant supply. According to the findings, the annual amount of water required for agriculture in the designated study location is approximately 2.9 million m3. Although there is no initial need for irrigation water, the demand for irrigation water increases during the development, active growth, and mature stages of maize, winter wheat, and wine grapes, reaching around 189 mm, 223 mm, and 63 mm, respectively. According to our observations, the annual water supply in Weinstadt is around 4 million m3. On the other hand, the compensated volume of water to the current water supply calculated from the urban roof rainfall is estimated to be 0.8 million m3, which is considered valuable from an economic standpoint. This economically efficient volume of water would reduce the current treated water supply, which indicates an opportunity for enhanced agricultural irrigation.

Assessing multifunctional retrofit potential of urban roof areas and evaluating the power and carbon benefits under efficient retrofit scenarios

Green roof installations and photovoltaic (PV) systems are widely employed roof retrofits that aid cities in mitigating climate change impacts, while avoiding the need for increased land utilization. By integrating PV systems with vegetation on urban roofs, a photovoltaic-green (PV-Green) system can be achieved for multifunctional use of the roof space, thereby simultaneously achieving PV and greening benefits. However, current research solely based on one retrofit type cannot meet the requirement for assessing the multifunctional retrofit potential of urban roofs. In this study, an assessment method is proposed to identify and quantify the multiple retrofit potential of urban roofs by integrating roof attributes (slope, orientation, and area), roof type (gable or flat), solar attributes (radiation and irradiation duration), and biogeochemical simulation. Moreover, three roof retrofit scenarios, Scenario 1 (S1): maximization of PV-Green roofs, Scenario 2 (S2): maximization of PV economic benefits, and Scenario 3 (S3): maximization of public subjective well-being through roof greening, were designed to allocate the use of urban roof spaces and evaluate their respective potential power and carbon benefits at the city scale. Using Shanghai's downtown as an example, the results showed that 85,722 roofs (or 7310.86 ha) were available for multifunctional use. S1 revealed that applying PV-Green roofs can increase the additional green biomass by 0.74 × 107 kg C/yr compared to only installing PV roofs. Moreover, S1 produced the highest power output of 2.31 × 1010 kWh/yr to meet 15.4% of Shanghai's electricity demand. S2 identified 609 flat roofs and 70,527 gable roofs that were uneconomical for PV system installation. This indicated that the solar radiation received by most gable roofs was insufficient to cover the installation cost. S3 offered a biomass production of 1.48 × 107 kg C/yr and increased carbon stocks in Shanghai by 0.87%. This assessment method provides urban planners and policymakers with an analytical tool to optimize the use of urban roof spaces, thereby enhancing urban livability and sustainability.

An innovative method for evaluating the urban roof photovoltaic potential based on open-source satellite images

The large-scale use of solar energy is an important means of achieving carbon neutrality. In cities, large stocks of building roofs are ideal for photovoltaic (PV) installations. However, the difficulty in acquiring urban building stock data limits the assessment of urban roof PV potential. Therefore, an instance segmentation model was used to extract all the roofs and their corresponding deep features from high-resolution open-source satellite maps. Subsequently, a multi-round semi-supervised clustering process was proposed to classify similar roofs. Finally, the total urban roof area was evaluated, involving pitched roof area correction. The PV available area ratios of all roofs were estimated by sampling each roof cluster to obtain the available roof area for PV installation. The corresponding urban PV potential capacity and energy generation were calculated. The proposed method was applied and validated in the Yangpu District of Shanghai, China. The results showed that the total building roof area of Yangpu District was 11.16 km2, and the roof PV available area ratio (Ra s) varied between 0.4 and 0.92. The available roof area for PV installation was 7.46 km2. The PV installation area and capacity were 4.14 km2 and 913.74 MW, respectively. The annual PV energy production was 940.34 GW h.

A geographic information system-based large scale visibility assessment tool for multi-criteria photovoltaic planning on urban building roofs

Integration of photovoltaics (PV) into the urban environment will play a major role in the energy transition. However, installing PV systems on building roofs can be challenging, particularly for monumental buildings with strict architectural and social value restrictions. Assessing roof surface visibility is, therefore, key to finding as much permitted roof surface area as possible that may be used for PV installation. In this study, a GIS-based large-scale visibility assessment tool is developed that can assist in evaluating roof visibility, using LiDAR, road networks, and cadastral data as inputs. The tool delivers multi-level outputs, including maps of roof binary visibility, roof visual amplitude, roof PV system layout, roof PV system AC yield, and roof PV module visibility. After optimization, an average speed of 0.12 s/m2 is achieved. For each roof surface, an additional sensitivity analysis has been conducted. This step determines the optimal values for two visibility analysis parameters: assessment range and observer spacing, balancing the computational demand and result accuracy. Application of this workflow to the monumental buildings on the TU Delft campus revealed that approximately 2.68 GWh/year of electricity could be harvested from imperceptible PV modules, while an additional 0.42 GWh/year of energy is attributed to PV modules with medium visibility, and 0.37 GWh/year of energy is associated with PV modules with high visibility. This modeling workflow supports the multi-criteria decision-making process for urban roof PV planning.

Physiological differences of green-leaf and variegated - leaf ivy (hedera helix L.) Cultivars

To screen sun-resistant cultivars of ivy for the three-dimensional greening of urban roofs and balconies, the chlorophyll content, photosynthetic response index, and chlorophyll fluorescence parameters of 5 green-leaf and 5 variegated leaf cultivars of ivy were measured, and compared the photosynthetic characteristics of different cultivars. Results showed that ivy seedlings were very shade tolerant. The photosynthetic adaptation range, maximum net photosynthetic rate, and electron transfer efficiency of the PSII reaction center of the green-leaf ivy cultivars were significantly higher than those of the variegated ivy cultivars. The photochemical conversion efficiency and photosynthetic capacity of Hedera helix ‘Shamrock’ were higher than those of the other tested green-leaf cultivars, suggesting that Hedera helix ‘Shamrock’ had a strong light tolerance. The differences in photosynthetic characteristics among the variegated cultivars were greater than those within the green-leaf cultivars. Among the tested cultivars, Hedera helix ‘Mini Kolibri’ had a relatively high light adaptation range and high light efficiency potential. Bangladesh J. Bot. 52(2): 539-549, 2023 (June) Special

Physiological differences of green-leaf and variegated - leaf ivy (hedera helix L.) Cultivars

To screen sun-resistant cultivars of ivy for the three-dimensional greening of urban roofs and balconies, the chlorophyll content, photosynthetic response index, and chlorophyll fluorescence parameters of 5 green-leaf and 5 variegated leaf cultivars of ivy were measured, and compared the photosynthetic characteristics of different cultivars. Results showed that ivy seedlings were very shade tolerant. The photosynthetic adaptation range, maximum net photosynthetic rate, and electron transfer efficiency of the PSII reaction center of the green-leaf ivy cultivars were significantly higher than those of the variegated ivy cultivars. The photochemical conversion efficiency and photosynthetic capacity of Hedera helix ‘Shamrock’ were higher than those of the other tested green-leaf cultivars, suggesting that Hedera helix ‘Shamrock’ had a strong light tolerance. The differences in photosynthetic characteristics among the variegated cultivars were greater than those within the green-leaf cultivars. Among the tested cultivars, Hedera helix ‘Mini Kolibri’ had a relatively high light adaptation range and high light efficiency potential. Bangladesh J. Bot. 52(2): 539-549, 2023 (June) Special

COLORED ROOFS: A SOLUTION TO MITIGATION UHI AND REDUCING URBAN SURFACE HEATING

The city is a built-up urban space and multifunctional structures that ensure safety, health and the best shelter for humans. All its built structures had various urban roofs influenced by different climate circumstances. That creates peculiarities and changes within the urban local climate and an increase in the impact of urban heat islands (UHI) with wastage of energy. The research question is less information dealing with the renovation of existing urban roofs using color as a strategy to mitigate the impact of UHI. In order to achieve local urban sustainability; the research focused on solutions using different materials and treatments to reduce urban surface heating emissions. The results showed that the new and old technologies, products, and the materials are complying with the principles of urban sustainability and have the local possibility of reducing urban roof heating, mitigating UHI and creating a sustainable urban environment at a low cost.

A model-based approach to addressing energy demand in sustainable urban systems

Sustainable cities address their citizens’ environmental, social, economic, cultural, and institutional needs in an integrated manner. In order to successfully transform urban systems in this context, key enabling technologies must be investigated that can facilitate such changes. In addition, computer-based modeling approaches for analyzing the benefits of such technologies for urban organizations and activities are highly desirable. In this paper, we propose a model-based approach to address sustainable urban environments that employs green edge computing technology to meet the energy and digital service requirements of urban systems. By utilizing the solar energy potential of urban roofs, this technology can be adapted to meet the crucial demands for power arising from digital activity in various urban contexts. As a result of its unique features, the proposed modeling framework is a valuable analysis tool for assisting decision-making to improve the quality of urban systems.

Long-Distance Pollen Dispersal in Urban Green Roof and Ground-Level Habitats

Long-distance pollen dispersal is critical for gene flow in plant populations, yet pollen dispersal patterns in urban habitats such as green roofs have not been extensively studied. Pollen dispersal patterns typically are assessed either by fitting non-linear models to the relationship between the degree of pollen dispersal and distance to the pollen source (i.e., curve fitting), or by fitting probability density functions (PDFs) to pollen dispersal probability histograms (i.e., PDF fitting). Studies using curve fitting typically report exponential decay patterns in pollen dispersal. However, PDF fitting typically produces more fat-tailed distributions, suggesting the exponential decay may not be the best fitting model. Because the two approaches may yield conflicting results, we used both approaches to examine pollen dispersal patterns in the wind-pollinated Amaranthus tuberculatus and the insect-pollinated Solanum lycopersicum at two green roof and two ground-level sites in the New York (NY, United States) metropolitan area. For the curve fitting analyses, the exponential decay and inverse power curves provided good fits to pollen dispersal patterns across both green roof and ground-level sites for both species. Similar patterns were observed with the PDF fitting analyses, where the exponential or inverse Gaussian were the top PDF at most sites for both species. While the curve fitting results are consistent with other studies, the results differ from most studies using PDF fitting, where long-distance pollen dispersal is more common than we observed. These results highlight the need for further research to compare curve and PDF fitting for predicting pollen dispersal patterns. And, critically, while long-distance pollen dispersal may be an important component of overall pollen dispersal for A. tuberculatus and S. lycopersicum in both urban green roof and ground-level sites, our results suggest it potentially may occur to a lesser extent compared with plants in less-urban areas.

The Sustainable Prescription: Benefits of Green Roof Implementation for Urban Hospitals

If worldwide healthcare was a country, it would be the fifth largest emitter of greenhouse gases on the planet. The increase in global temperatures, combined with the negative impacts of urbanization, has made it more important than ever to introduce green spaces where possible. With climate change worsening, human health, both physically and mentally is on decline, making the effects of climate change especially pressing to the stability of healthcare systems. In order to mitigate the lasting impacts of climate change on healthcare facilities, a holistic solution is needed. Access to green space in hospitals has been shown to reduce emotional distress, improve mental health, increase socialization and community connection, increase physical activity, decrease cardiovascular and respiratory diseases, decrease pain management needs and hospital stay lengths and increase both patients' and staffs' overall satisfaction at the facility. Beyond benefiting those interacting with the hospital, green roofs have the ability to reduce the urban heat island effect, improve stormwater mitigation, increase biodiversity, and absorb toxins and pollutants through air filtration. Additionally, green roofs can offer lower maintenance costs and higher energy savings than traditional roofs, and improve patient satisfaction, which can result in future funding opportunities. However, the upfront and upkeep costs of installing a green roof can vary and must be considered before implementation. In this review, we explore the symbiotic relationship between urban green roofs and hospital/patient wellness through the lens of sustainability, which includes environmental, societal, and economic impacts. We review scientific journal articles investigating benefits of green space and green roofs and highlight examples of green roofs on hospitals in the United States; together, these approaches display the environmental, societal, and economic benefits of green roofs installed on healthcare facilities. This review offers insight to hospitals, decision makers, and government systems on the importance of green roofs in urban areas and how these infrastructures can support the economic growth of the institute. Using our framework, decision makers and planners for urban hospitals can evaluate how the addition of green roofs to their healthcare facilities can contribute to increased environmental resiliency, community health, and patient satisfaction.

Small Urban Green Roof Plots Near Larger Green Spaces May Not Provide Additional Habitat for Birds

Global wildlife populations are in decline, in part, due to urbanization. However, in urban landscapes, green infrastructure such as green roofs are being created to provide habitat for wildlife. Green roof isolation, planting heterogeneity, and size can all influence wildlife biodiversity, as may the age of a green roof. When new habitat is created, wildlife use of these new habitats is expected to increase over time. To test this expectation for birds, we monitored bird activity prior to and after installation of small green roof plots on six buildings located within New York City parks. Contrary to expectations, bird activity and bird species richness did not increase after green roof plot installation, nor did they increase over a period of 4 years following installation. These unexpected results may reflect the relatively small size of the plots or the fact that the plots were on buildings located within urban parks. Bird activity and bird species richness varied widely between roofs, and the composition of rooftop bird species may have been more influenced by the characteristics of the surrounding landscapes than the presence of the green roof plots. These findings suggest that small urban green roofs within a larger and, potentially, higher quality habitat may not provide additional habitat for foraging birds. Urban green roofs have numerous ecological and environmental benefits, but the size and characteristics of landscapes surrounding a green roof need to be considered when installing green roofs as wildlife habitat.

MULTIPLE ENDMEMBER SPECTRAL MIXTURE ANALYSIS OF DESIS IMAGE TO IDENTIFY ROOFTOPS IN KIGALI

Abstract. The development and increase of multi and hyperspectral sensors in the recent years have significantly improved urban structure analysis and interpretation. The current study is the first to investigate the potential of DESIS hyperspectral images for the detection or identification of urban roof materials. After field campaigns in 2014, 2015 and 2018 to collect ground truth points and rooftops radiometric properties; a linear spectral mixture, implemented using a non-negative least squares (NNLS) regression based on the sequential coordinate-wise algorithm (SCA) was applied on a DESIS image from 2020 of Kigali city to identify the different rooftops material and color. Although results show that most endmembers were predicted with a very low probability, the study proved that the combination of spectral mixture and hyperspectral data such as DESIS have great potential in the detection of rootops material. The presented study also highlghted a number of challenges resulting from the choice of spectral mixture algorithm and colinearity between materials.

Lessons from New York High Line Green Roof: Conserving Biodiversity and Reconnecting with Nature

The concept of sustainable urban design has appeared in different perspectives to minimize and reduce the negative impacts of urban expansion in terms of climatic and environmental drawbacks. One of the undeniable approaches of sustainable urban design is the adoption of green urban roofs. Green roofs are seen to have a substantial role in addressing and resolving environmental issues in the context of climate change. Research investigations have indicated that green roofs have a remarkable impact on decreasing rainwater runoff, reducing the heat island effect in urban spaces, and increasing biodiversity. Nevertheless, green roofs in urban spaces as a competent alternative to nature remains a standing question. To what extent can green roofs mimic the biodiversity that is seen in nature? Moreover, to what level is this approach practical for achieving a tangible reconnection with nature, or so-called biophilia? This study attempts to discuss the essence and impact of green roofs in urban spaces based on a case study approach. The study reflected lessons from the New York High Line Green Roof regarding biophilia and biodiversity in this case study. It concludes with key lessons that can be transferred to other urban spaces with similar settings.

Pollinators on Green Roofs: Diversity and Trait Analysis of Wild Bees (Hymenoptera: Anthophila) and Hoverflies (Diptera: Syrphidae) in an Urban Area (Geneva, Switzerland)

Green roofs can provide food resources to several insect groups. For pollinators found in cities, as are wild bees and hoverflies, the existence of a wide variety of green infrastructures is crucial to ensure their development and survival. In order to investigate if wild bees and hoverflies use green roofs and how local and landscape factors influence their abundance and diversity, sampling of these insects was done in 2017 using cornet traps on extensive green roofs of two types: 1) urban green roofs (30% of green spaces in a 200m radius). There were 62 wild bee species and 10 hoverfly species identified during the 22-week sampling period. For the latter, no differences in richness and abundance were found between roofs and between roof types. Most hoverfly species were associated with xero-thermophilic habitats. Regarding wild bees, no difference in abundance and richness was observed between roofs. However, urban roofs showed significantly lower abundances compared to mixed landscape roofs. Local and landscape factors influenced the pollinator communities: the percentage of attractive plant species on roofs was positively correlated with the abundance of wild bees and the percentage of green areas in a 600 m radius was positively correlated with their richness. The traits analysis showed no difference between roofs and between roof types. Our results highlight the important role of green roofs in supplying food resources for urban pollinators instead of providing suitable nesting habitats. The abundance of attractive plant species for pollinators and diversified landscape surrounding green roofs seem to be key factors in order to promote these wild pollinators in cities.

Evaluation of Photovoltaic Energy Saving Potential and Investment Value of Urban Buildings in China Based on GIS Technology

The environmental and energy crisis has become a problem that can not be ignored in today’s world and improving the proportion of renewable energy utilization is an important way to alleviate the problem. China has begun to vigorously develop rooftop photovoltaic systems, and it is urgent to analyze the photovoltaic potential of the country. In this paper, GIS technology is used to calculate the available area of a PV system on the roof of urban buildings in China. The installed capacity and annual power generation of a PV system on the roof of urban buildings in China are further calculated, and the investment cost analysis of the buildings with a PV system is carried out. The results show that Chinese mainland city rooftop photovoltaic area has reached 3.35 billion m2. If urban roofs are used for photovoltaic power generation in China, the annual photovoltaic power generation capacity will be 672 billion kWh, which is about 61% of the total annual electricity consumption of the whole society in 2020. On the other hand, the initial investment in the construction of an urban photovoltaic system is large, but most of them can realize the return of investment in a short period of 8–10 years. Moreover, in the effective life of the follow-up photovoltaic system, it will bring greater economic benefits, which is more than two times the initial investment. To further promote the process of social carbon peak and carbon neutrality in China, the construction of an urban photovoltaic system is very feasible.

Comparative Evaluation of Mapping Accuracy between UAV Video versus Photo Mosaic for the Scattered Urban Photovoltaic Panel

It is common practice for unmanned aerial vehicle (UAV) flight planning to target an entire area surrounding a single rooftop’s photovoltaic panels while investigating solar-powered roofs that account for only 1% of the urban roof area. It is very hard for the pre-flight route setting of the autopilot for a specific area (not for a single rooftop) to capture still images with high overlapping rates of a single rooftop’s photovoltaic panels. This causes serious unnecessary data redundancy by including the surrounding area because the UAV is unable to focus on the photovoltaic panel installed on the single rooftop. The aim of this research was to examine the suitability of a UAV video stream for building 3-D ortho-mosaics focused on a single rooftop and containing the azimuth, aspect, and tilts of photovoltaic panels. The 3-D position accuracy of the video stream-based ortho-mosaic has been shown to be similar to that of the autopilot-based ortho-photo by satisfying the mapping accuracy of the American Society for Photogrammetry and Remote Sensing (ASPRS): 3-D coordinates (0.028 m) in 1:217 mapping scale. It is anticipated that this research output could be used as a valuable reference in employing video stream-based ortho-mosaics for widely scattered single rooftop solar panels in urban settings.

Roofpedia: Automatic mapping of green and solar roofs for an open roofscape registry and evaluation of urban sustainability

Sustainable roofs, such as those with greenery and photovoltaic panels, contribute to the roadmap for reducing the carbon footprint of cities. However, research on sustainable urban roofscapes is rather focused on their potential and it is hindered by the scarcity of data, limiting our understanding of their current content, spatial distribution, and temporal evolution. To tackle this issue, we introduce Roofpedia, a set of three contributions: (i) automatic mapping of relevant urban roof typology from satellite imagery; (ii) an open roof registry mapping the spatial distribution and area of solar and green roofs of more than one million buildings across 17 cities; and (iii) the Roofpedia Index, a derivative of the registry, to benchmark the cities by the extent of sustainable roofscape in term of solar and green roof penetration. This project, partly inspired by its street greenery counterpart ‘Treepedia’, is made possible by a multi-step pipeline that combines deep learning and geospatial techniques, demonstrating the feasibility of an automated methodology that generalises successfully across cities with an accuracy of detecting sustainable roofs of up to 100% in some cities. We offer our results as an interactive map and open dataset so that our work could aid researchers, local governments, and the public to uncover the pattern of sustainable rooftops across cities, track and monitor the current use of rooftops, complement studies on their potential, evaluate the effectiveness of existing incentives, verify the use of subsidies and fulfilment of climate pledges, estimate carbon offset capacities of cities, and ultimately support better policies and strategies to increase the adoption of instruments contributing to the sustainable development of cities.