<jats:p>Abstract. The interest in and use of 3D models in built environments is rapidly increasing, and they are now a key component of decision-making in areas including climate change mitigation (e.g., calculating solar panel potential, flood modelling, modelling housing age for retrofitting of thermal insulation), urban planning and cadastral systems (modelling rights, restrictions and responsibilities in complex buildings, streamlining the process to issue planning permits, design of existing or new developments) and infrastructure (construction, transport, utility management and modelling, asset management). 3D models are also an integrator for the data underpinning smart cities – knowing where a sensor is in 3D space allows the data to be integrated with the surrounding context – for example, noise data could be integrated with traffic information. Reflecting this interest, national mapping and cadastral agencies (NMCA) including Ordnance Survey (GB) are now increasingly generating 3D mapping at national scale, and there is extensive research as to how this data can be integrated with another emerging source of 3D models such as building information modelling (BIM).These trends were evident during the 3rd BIM/GIS Integration Workshop and 15th 3DGeoInfo 2020 events, which were co-hosted by University College London and Ordnance Survey (GB) in September 2020. The workshop and conference brought together international researchers from academia, industry, government and national mapping and cadastral agencies in the field of 3D geoinformation, in an interdisciplinary gathering of researchers in the fields of data collection, data management, data quality, data analysis, advanced modelling approaches, applications, users, visualisation, augmented reality, artificial intelligence and many more.This year’s theme was Users and Use Cases. The workshop and conference covered a wide range of topics including 3D data acquisition and processing, 3D city modelling and related standards, visualisation and dissemination of 3D data, augmented and virtual reality, 3D and Artificial Intelligence/Machine Learning. Three sessions of the BIM/GIS Integration Workshop were dedicated to Applications of BIM/GIS Integration, and an entire day of 3DGeoInfo 2020 to Users and Use Cases within 3DGeoInfo. Additionally, two sessions were specifically aimed at NMCA participants.Although initially intended to be a face-to-face event in London, the team rapidly adjusted to the emerging COVID-19 situation, identifying an online solution that facilitated and encouraged participant interaction. This meant that the events could still provide a platform for learning, discussion, and exchange of ideas that they have been able to in previous years, as well as providing opportunities to promote international collaboration in these topics. This special issue of the ISPRS International Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences contains 22 papers selected by double-blind peer review carried out by a minimum of three reviewers. It includes research on topics including data modelling, indoor 3D, standards (IndoorML, CityGML, CityJSON), cadastral systems, pedestrian navigation, infrastructure, visualisation, point cloud management, data interoperability, data quality, generating national 3D datasets and planning/permit processes amongst others. </jats:p>

<jats:p>Abstract. The interest in and use of 3D models in built environments is rapidly increasing, and they are now a key component of decision-making in areas including climate change mitigation (e.g., calculating solar panel potential, flood modelling, modelling housing age for retrofitting of thermal insulation), urban planning and cadastral systems (modelling rights, restrictions and responsibilities in complex buildings, streamlining the process to issue planning permits, design of existing or new developments) and infrastructure (construction, transport, utility management and modelling, asset management). 3D models are also an integrator for the data underpinning smart cities – knowing where a sensor is in 3D space allows the data to be integrated with the surrounding context – for example, noise data could be integrated with traffic information. Reflecting this interest, national mapping and cadastral agencies (NMCA) including Ordnance Survey (GB) are now increasingly generating 3D mapping at national scale, and there is extensive research as to how this data can be integrated with another emerging source of 3D models such as building information modelling (BIM).These trends were evident during the 3rd BIM/GIS Integration Workshop and 15th 3DGeoInfo 2020 events, which were co-hosted by University College London and Ordnance Survey (GB) in September 2020. The workshop and conference brought together international researchers from academia, industry, government and national mapping and cadastral agencies in the field of 3D geoinformation, in an interdisciplinary gathering of researchers in the fields of data collection, data management, data quality, data analysis, advanced modelling approaches, applications, users, visualisation, augmented reality, artificial intelligence and many more.This year’s theme was Users and Use Cases. The workshop and conference covered a wide range of topics including 3D data acquisition and processing, 3D city modelling and related standards, visualisation and dissemination of 3D data, augmented and virtual reality, 3D and Artificial Intelligence/Machine Learning. Three sessions of the BIM/GIS Integration Workshop were dedicated to Applications of BIM/GIS Integration, and an entire day of 3DGeoInfo 2020 to Users and Use Cases within 3DGeoInfo. Additionally, two sessions were specifically aimed at NMCA participants.Although initially intended to be a face-to-face event in London, the team rapidly adjusted to the emerging COVID-19 situation, identifying an online solution that facilitated and encouraged participant interaction. This meant that the events could still provide a platform for learning, discussion, and exchange of ideas that they have been able to in previous years, as well as providing opportunities to promote international collaboration in these topics. This special issue of the ISPRS International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences contains 23 papers selected by a double-blind peer review involving a minimum of two reviewers, presenting research on topics including visualisation, point cloud management, virtual reality, data interoperability, data quality, generating national 3D datasets, indoor 3D, urban planning/permits and underground data management. </jats:p>

<jats:p>Abstract. Cities are facing important challenges due to population growth and massive development of high-rises and complex structures above and below the ground surface. In that respect, having an efficient land-use regulation framework in force is necessary for cities. In investigating current practices for processing spatial data when issuing building permits, in many cases, the planned building is drawn on 2D plans with cross-sections to represent their 3D dimensions. In complex multilevel developments, this method has significant shortcomings like the requirement of managing numerous plans and sections, and uncertainty in decisions more specifically when checking land-use regulations comprising 3D components (e.g. height limits, overhanging objects, solar rights). In order to support issuing a building permit and moving towards the establishment of 3D smart cities, this paper presents an inventory for land-use regulations with 3D components and functional classification of their possible conflicts. Two functional classifications of possible conflicts in a building permit process from two points of view (i.e. data integration process, and magnitude of land-use regulation conflicts) are proposed. These results are placed in the context of having 3D city models that integrate land-use regulation information. </jats:p>

This article focuses on decision making for retrofit investment of road networks in order to alleviate severe consequences of roadside tree blowdown during tropical cyclones. The consequences include both the physical damage associated with roadside trees and the functional degradation associated with road networks. A trilevel, two-stage, and multiobjective stochastic mathematical model was developed to dispatch limited resources to retrofit the roadside trees of a road network. In the model, a new metric was designed to evaluate the performance of a road network; resilience was considered from robustness and recovery efficiency of a road network. The proposed model is at least a nondeterministic polynomial-time hardness (NP-hard) problem, which is unlikely to be solved by a polynomial time algorithm. Pareto-optimal solutions for this problem can be obtained by a proposed trilevel algorithm. The random forest method was employed to transform the trilevel algorithm into a single-level algorithm in order to decrease the computation burden. Roadside tree retrofit of a provincial highway network on Hainan Island, China was selected as a case area because it suffers severely from tropical cyclones every year, where there is an urgency to upgrade roadside trees against tropical cyclones. We found that roadside tree retrofit investment significantly alleviates the expected economic losses of roadside tree blowdown, at the same time that it promotes robustness and expected recovery efficiency of the road network.

Fragrance is used in consumer products around the world. However, fragrance has been associated with adverse effects on indoor and outdoor air quality and human health. Questions arise, such as the following: Why does fragrance in products pose problems? What are sources of emissions and exposures? What are health and societal effects? What are possible solutions? This paper examines the issue of fragranced consumer products and its science and policy dimensions, with a focus on the implications for air quality and human health. Results include new findings and new questions for future research directions.

This paper provides a review of the changing nature of the water–energy nexus in urban water supply systems (UWSSs) due to the primary long-term drivers of climate change, population growth and technological development from the ‘energy for water’ perspective. We identify both the physical changes in UWSSs, as well as the changes in the attributes of the system, both of which contribute to the changing nature of the water–energy nexus. We provide an overview of responses to this change in the water–energy nexus through the lens of four application areas, namely long-term planning, system design, system operation and system rehabilitation, based on the review of 52 papers. Ten responses in three categories are found to be commonly considered in each of the four application areas. The three categories are energy or greenhouse gas reduction, integrated modelling and planning, and improving social benefits. The main drivers of these responses may vary with the application area. Based on the review outcomes, we outline the gaps in the responses in relation to the changing nature of the water–energy nexus in UWSSs, providing directions for future research on improving UWSS efficiency considering the long-term drivers.

Environmental water represents a key resource in managing freshwater ecosystems against pervasive threats. The impacts of climate change add further pressures to environmental water management, yet anticipating these impacts through modelling approaches remains challenging due to the complexities of the climate, hydrological and ecological systems. In this paper, we review the challenges posed by each of these three areas. Large uncertainties in predicting climatic changes and non-stationarities in hydrological and ecological responses make anticipating impacts difficult. In addition, a legacy of relying on modelling approaches informed by historic dependencies in environmental water science may confound the prediction of ecological responses when extrapolating under novel conditions. We also discuss applying ecohydrological methods to support decision-making and review applications of bottom-up climate impact assessments (specifically eco-engineering decision scaling) to freshwater ecosystems. These approaches offer a promising way of incorporating climatic uncertainty and balancing competing environmental objectives, but some practical challenges remain in their adoption for modelling environmental water outcomes under climate change.

Tunisia has a long history of coping with water scarcity, and the quantification of climate change impacts on runoff is important for future water management. A major requirement for such studies is an estimation of potential evapotranspiration (PET), which is challenging as many regions often lack the observational data needed for physically based PET equations. In this study, different PET estimation approaches were used to study the impact of PET estimation on discharge projections for catchments in Northern Tunisia. Discharge was simulated for five catchments using three rainfall-runoff models (RRMs): HBV, GR4 and IHACRES. A general differential split sample test (GDSST) was used for an RRM robustness evaluation based on subperiods with contrasting climatic conditions for the 1970–2000 period. Three cases with varying PET were considered: (1) daily calculated PET, (2) long-term daily mean PET with the same values for calibration and validation periods (calculated over the calibration period) and (3) long-term daily mean PET varying between calibration and validation periods (calculated over the calibration and validation period separately). Over the historical period, the comparison between cases 1 and 3 showed little impact of reduced PET information on the RRM performance and robustness. The comparison of cases 2 and 3 indicated a limited impact of varying PET between calibration and validation on the RRM results. The impact of varying levels of PET information on hydrological projections was also analysed over two future 30-year periods: mid-term period (2040–2070) and long-term period (2070–2100), with two representative concentration pathway scenarios (RCPs 4.5 and 8.5), by comparing cases 1 and 2. The projected discharge with constant PET (case 2) was generally lower than the projected discharge with variable PET (case 1) but the difference in volume change did not exceed 9% for both the time period and the RCP scenario considered. While PET slightly increased under the different climate change scenarios, actual evapotranspiration (AET) was found to decrease. These opposite trends of PET and AET can be attributed to the projected decrease in precipitation. Overall, our results demonstrate that discharge, in semi-arid regions like Northern Tunisia, is not sensitive to PET estimates since AET is mainly controlled by the availability of soil moisture. This finding is useful for performing studies of climate change impact on hydrological cycles in arid regions, as our study shows that simple PET estimation is a valid approach for such studies.