Solar maps are becoming a popular resource and are available via the web to help plan investments for the benefits of renewable energy. These maps are especially useful when the results have high accuracy. LiDAR technology currently offers high-resolution data sources that are very suitable for obtaining an urban 3D geometry with high precision. Three-dimensional visualization also offers a more accurate and intuitive perspective of reality than 2D maps. This paper presents a new method for the calculation and visualization of the solar potential of building roofs on an urban 3D model, based on LiDAR data. The paper describes the proposed methodology to (1) calculate the solar potential, (2) generate an urban 3D model, (3) semantize the urban 3D model with different existing and calculated data, and (4) visualize the urban 3D model in a 3D web environment. The urban 3D model is based on the CityGML standard, which offers the ability to consistently combine geometry and semantics and enable the integration of different levels (building and city) in a continuous model. The paper presents the workflow and results of application to the city of Vitoria-Gasteiz in Spain. This paper also shows the potential use of LiDAR data in different domains that can be connected using different technologies and different scales.

Georeferenced 3D models are an increasingly common choice to store and display urban data in many application areas. CityGML is an open and standardized data model, and exchange format that provides common semantics for 3D city entities and their relations and one of the most common options for this kind of information. Currently, creating and maintaining CityGML models is costly and difficult. This is in part because both the creation of the geometries and the semantic annotation can be complex processes that require at least some manual work. In fact, many publicly available CityGML models have errors. This paper proposes a method to facilitate the regular maintenance of correct city models in CityGML. This method is based on the continuous deployment strategy and tools used in software development, but adapted to the problem of creating, maintaining and deploying CityGML models, even when several people are working on them at the same time. The method requires designing and implementing CityGML deployment pipelines. These pipelines are automatic implementations of the process of building, testing and deploying CityGML models. These pipelines must be run by the maintainers of the models when they make changes that are intended to be shared with others. The pipelines execute increasingly complex automatic tests in order to detect errors as soon as possible, and can even automate the deployment step, where the CityGML models are made available to their end users. In order to demonstrate the feasibility of this method, and as an example of its application, a CityGML deployment pipeline has been developed for an example scenario where three actors maintain the same city model. This scenario is representative of the kind of problems that this method intends to solve, and it is based on real work in progress. The main benefits of this method are the automation of model testing, every change to the model is tested in a repeatable way; the automation of the model deployment, every change to the model can reach its end users as fast as possible; the systematic approach to integrating changes made by different people working together on the models, including the possibility of keeping parallel versions with a common core; an automatic record of every change made to the models (who did what and when) and the possibility of undoing some of those changes at any time.

Historic urban areas are complex and inter-reliant systems, vulnerable to natural hazards. Over the recent years, the increase frequency in extreme precipitation events and sea-level rise, have impacted on a large number of historic areas, growing concern over disaster mitigation related to climate change. Most of the changes in the climatological indicators may have adverse impacts on historic areas, leading to physical, social and cultural consequences and should be included in urban planning practice. The importance of addressing cultural heritage in disaster risk has also been included in The Sendai Framework, considering the dimensions of vulnerability, adaptive capacity and exposure through systematic evaluation. Urban planning decisions involve an understanding of complex interactions between different aspects of the city, in its constructive, social, economic, environmental and cultural system. The analysis of these interactions requires a systemic approach as the components operate on different spatial and temporal scales and generate a large amount of data. This information can be used to determine the vulnerability of historic areas by assessing it at the building level, through the creation of typologies representing the building stock, often characterized by similarities and common constructive elements. The comprehension of the information can be supported and homogenized by a multi-scale urban model, to facilitate the understanding of interactions and the link among the different disciplines involved. This paper describes the methodology proposed for vulnerability mapping in historic urban areas, by using a categorization method supported by an information strategy and a multi-scale urban model.

The holistic modelling approach required for the long-term integrated urban energy planning is becoming a big challenge since the complexity of cities, as well as their commitments are increasing rapidly. Many municipalities require technical support during the definition of the direction of their long-term energy transition plans. Innovative modelling approaches and the ex-ante impact assessment are necessary steps of the process since the direction adopted by the city will have many long-lasting implications not only in the energy and climate dimensions but also in their social and economic development. This paper presents the overall methodological and modelling approach and the initial results of the developed Advanced Integrated Urban Planning process that has been validated by its application in the cities of Helsinki, Hamburg and Nantes.

Georeferenced 3D models represent an increasingly accepted solution for storing and displaying information at urban scale. CityGML, as standard data model for the representation, storage and exchange of 3D city models, represent a very attractive solution which combines 3D geometric and semantic information in a single data model. In this paper we present an approach to visualize semantic and 3D information of historical centers using open standards. Also, three client applications are presented targeting different agents with different needs with the characteristic that all the information is got from an unique extended CityGML data model.