Abstract. The 3D BAG v. 2.0 dataset has been recently released: it is a country-wide dataset containing all buildings in the Netherlands, modelled in multiple LoDs (LoD1.2, LoD1.3 and LoD2.2). In particular, the LoD2.2 allows differentiating between different thematic surfaces composing the building envelope. This paper describes the first steps to test and use the 3D BAG 2.0 to perform energy simulations and characterise the energy performance of the building stock. Two well-known energy simulation software packages have been tested: SimStadt and CitySim Pro. Particular care has been paid to generate a suitable, valid CityGML test dataset, located in the municipality of Rijssen-Holten in the central-eastern part of the Netherlands, that has been then used to test the energy simulation tools. Results from the simulation tools have been then stored into the 3D City Database, additionally extended to deal with the CityGML Energy ADE. The whole workflow has been checked in order to guarantee a lossless dataflow.The paper reports on the proposed workflow, the issues encountered, some solutions implemented, and what the next steps will be.
Abstract. In this paper, five commonly used software tools to estimate solar radiation in the urban context (GRASS GIS, ArcGIS, SimStadt, CitySim and Ladybug) are run on the same test site and are compared in terms of input data requirements, usability, and accuracy of the results. Spatial and weather data have been collected for an area located in the Brazilian city of São Paulo, in the district of Santana. The test area surrounds a weather station, for which meteorological data of the last 15 years have been collected and used as ground truth when analysing and comparing the simulation results. In terms of spatial data, raster- and vector-based models of the study area have been generated in order to comply with the different input requirements. More specifically, in the case of the vector-based tools (SimStadt, CitySim and Ladybug), a common 3D model based on CityGML and containing buildings, vegetation (trees) and terrain has been generated and used as a common urban model. The paper presents the findings and discusses the results not only from a numerical point of view, but also from the perspective of the overall usability of the software in terms of data requirements, simulation time and task automatisation.
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