The road towards achievement of the climate protection goals requires, among the rest, a thorough rethinking of the energy planning tools (and policies) at all levels, from local to global. Nevertheless, it is in the cities where the largest part of energy is produced and consumed, and therefore it makes sense to focus the attention particularly on the cities as they yield great potentials in terms of energy consumption reduction and efficiency increase. As a direct consequence, a comprehensive knowledge of the demand and supply of energy resources, including their spatial distribution within urban areas, is therefore of utmost importance. Precise, integrated knowledge about 3D urban space, i.e. all urban (above and underground) features, infrastructures, their functional and semantic characteristics, and their mutual dependencies and interrelations play a relevant role for advanced simulation and analyses. As a matter of fact, what in the last years has proven to be an emerging and effective approach is the adoption of standard-based, integrated semantic 3D virtual city models, which represent an information hub for most of the above-mentioned needs. In particular, being based on open standards (e.g. on the CityGML standard by the Open Geospatial Consortium), virtual city models firstly reduce the effort in terms of data preparation and provision. Secondly, they offer clear data structures, ontologies and semantics to facilitate data exchange between different domains and applications. However, a standardised and omni-comprehensive urban data model covering also the energy domain is still missing at the time of writing (January 2018). Even CityGML falls partially short when it comes to the definition of specific entities and attributes for energy-related applications. Nevertheless, and starting from the current version of CityGML (i.e. 2.0), this article describes the conception and the definition of an Energy Application Domain Extension (ADE) for CityGML. The Energy ADE is meant to offer a unique and standard-based data model to fill, on one hand, the above-mentioned gap, and, on the other hand, to allow for both detailed single-building energy simulation (based on sophisticated models for building physics and occupant behaviour) and city-wide, bottom-up energy assessments, with particular focus on the buildings sector. The overall goal is to tackle the existing data interoperability issues when dealing with energy-related applications at urban scale. The article presents the rationale behind the Energy ADE, it describes its main characteristics, the relation to other standards, and provides some examples of current applications and case studies already adopting it.

There is a need in the humanities for a 3D WebGIS with analytical tools that allow researchers to analyze 3D models linked to spatially referenced data. Geographic Information Systems (GIS) allow for complex spatial analysis of 2.5D data. For example, they offer bird’s eye views of landscapes with extruded building footprints, but one cannot ‘get on the ground’ and interact with true 3D models from a pedestrian perspective. Meanwhile, 3D models and virtual environments visualize data in 3D space, but analytical tools are simple rotation or lighting effects. The MayaArch3D Project is developing a 3D WebGIS—called QueryArch3D—to allow these two distinct approaches to ‘talk to each other’ for studies of architecture and landscapes—in this case, the eighth-century Maya kingdom of Copan, Honduras. With this tool, researchers can search and query, in real time via a virtual reality (VR) environment, segmented 3D models of multiple resolutions (as well as computer-assisted design and reality-based) that are linked to attribute data stored in a spatial database. Beta tests indicate that this tool can assist researchers in expanding questions and developing new analytical methods in humanities research. This article summarizes the results of a pilot project that started in 2009, with an art historian and an archaeologist’s collaborative research on the ancient Maya kingdom and UNESCO World Heritage site of Copan in Honduras—called MayaArch3D. The project researches innovative approaches to integrate GIS, 3D digital models, and VR environments online for teaching and research on ancient architecture and landscapes. It has grown into an international, interdisciplinary project that brings together art historians, archaeologists, and cultural resource managers with experts in remote sensing, photogrammetry, 3D modeling, and VR. The Start Up Phase was funded by two National Endowment for the Humanities, Digital Humanities Start-Up grants to the University of New Mexico (PI: Jennifer von Schwerin) and developed and beta tested a pipeline and prototype 3D WebGIS—called QueryArch3D. The prototype version is available at http://mayaarch3d.org/project-history/). Project results indicate that it is possible to bridge the gap between 3D and GIS to create a resource for researchers of Maya architecture to compare and analyze 3D models and archaeological data in the context of a geographically referenced, VR landscape.

A bottom-up building energy modelling at the urban scale based on Geographic Information System and semantic 3D city models can provide quantitative insights to tackle critical urban energy challenges. Nevertheless, incomplete information is a common obstacle to produce reliable modelling results. The residential building heating demand simulation performance gap caused by input uncertainties is discussed in this study. We present a data-driven urban scale energy modelling framework from open-source data harmonization, sensitivity analysis, heating demand simulation at the postcode level to Bayesian calibration with six years of training data and two years of validation data. Comparing the baseline and the calibrated simulation results, the averaged absolute percentage errors of energy use intensity in the study area have significantly improved from 25.0% to 8.3% and from 19.9% to 7.7% in two validation years, while ${\mathrm{C}\mathrm{V}\mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}}_{2016}=11.5\mathrm{\%}$ and ${\mathrm{C}\mathrm{V}\mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}}_{2017}=13.2\mathrm{\%}$. The overall methodology is extendable to other urban contexts.

The aim of this study is the estimation of solar irradiance on building roofs in complex Alpine landscapes. Very high resolution geometric models of the building roofs are generated by means of advanced automated image matching methods. Models are combined with raster and vector data sources to estimate the incoming solar radiation hitting the roofs. The methodology takes into account for atmospheric effects, site latitude and elevation, slope and aspect of the terrain as well as the effects of shadows cast by surrounding buildings, chimneys, dormers, vegetation and terrain topography. An open source software solution has been developed and applied to a study area located in a mountainous site and containing some 1250 residential, commercial and industrial buildings. The method has been validated by data collected with a pyranometer and results made available through a prototype WebGIS platform.