Currently, approximately 60% of the global population lives in urban areas (UN. Population Division, 2018). Incorrect quantification of the current and expected energy demands of buildings can lead to erroneous decisions and misguided planning for energy supply. Additionally, society is transitioning to adopting more sustainable energy sources to reduce environmental impacts. Solar gains play a major role in energy demand simulations. Therefore, it is important to perform precise calculations of the solar radiation for a given area of interest. However, this energy source faces challenges, such as shadowing, which rapidly decreases the performance of any solar panel, and it is constantly changing owing to the movement of the sun across the sky. Figure 1 shows a sketch of the considerations for computing shadowing calculations and the components of the solar irradiance. [...]@en

With the increasing adoption of semantic 3D city models, the relevance of applications in the field of Urban Building Energy Modelling (UBEM) has rapidly grown, as the building sector accounts for a large part of the total energy consumption. UBEM allows us to better understand the energy performance of the building stock and can contribute to defining refurbishment strategies. However, UBEM applications require lots of heterogeneous data, eventually advocating for standards for data interoperability. The Energy Application Domain Extension has been created to cope with UBEM data requirements and offers a standardised data model that builds upon the CityGML standard. The Energy ADE 1.0, released in 2018, creates new classes and adds new properties to existing classes of the CityGML 2.0 Core and Building modules. CityGML 3.0, released in 2021, has introduced several changes to the data model and its ADE mechanism. These changes render the Energy ADE incompatible with CityGML 3.0. This article presents how the Energy ADE has been ported to CityGML 3.0 to allow, on the one hand, for a lossless data conversion and, on the other hand, to exploit the new characteristics of CityGML 3.0 while keeping a logical symmetry between the ADE classes of both CityGML versions. The article describes the chosen methodology, the mapping strategies, the implementation steps, as well as the data conversion tests to check the validity of the “new” Energy ADE for CityGML 3.0.@en

Nowadays, our society is in the transit to adopt more sustainable energy sources to reduce our impact on the environment; one alternative is solar energy. However, this is highly affected by the surroundings, which might cause shadowing effects. In this paper, we present our method to perform shadowing calculations in urban areas using semantic 3D city models, which is split into five sections: Point Grid Generation, Sun-Ray Generation, Nightside Filtering, Bounding Volume Hierarchy and the intersection between the sun rays and the BVH to identify which locations are shadowed at a given moment (epoch). Our tests are performed in Rotterdam’s city center, a dense urban area in The Netherlands. Our initial results indicate that the computational time per 100 k grid points fluctuates within 0.2–0.7s.@en

This paper introduces a new plug-in for QGIS that allows to connect to the free and open-source 3D City Database to load CityGML data, structured as classic GIS layers, into QGIS. The user is therefore not required to be a CityGML specialist, or a SQL expert, as the plug-in takes care of hiding from the user most of the complexity in terms of underlying data model and database schema implementation. The user can therefore load CityGML thematic “layers” (e.g. for buildings, bridges, vegetation, terrain, etc.), explore their geometries in 2D and 3D and access and edit the associated attributes. At the same time, depending on the user privileges, it is possible to delete features from the database using either normal QGIS editing tools, or a “bulk delete” tool, also included. The plug-in is composed of two parts, a server-side one, which must be installed in the 3D City Database instance, and the client-side one, which runs as a QGIS plug-in in strict sense. A GUI-based tool is also provided for database administrators in order to install/uninstall the database-side part of the plug-in, and manage users and their privileges. All in all, the 3DCityDB-Tools plug-in facilitates the access to CityGML data for GIS practitioners from heterogeneous fields and expertise with the common denominator being the well-known QGIS environment.@en

Potato production systems present various phytosanitary problems. Among these, potato early dying (PED) caused by Verticillium spp. is a disease that is difficult to detect in its early stages and whose expression occurs in critical growing phases of the crop, such as tuber filling, generating a high economic impact. The objective of this work was to use spectral data to classify potato plants and identify the degree of severity of PED using spectral signatures and multispectral images captured on potato plants under greenhouse and commercial production conditions. Methods such as principal component analysis (PCA), random forest (RF), support vector machine (SVM), and artificial neural network (ANN) algorithms were implemented. All algorithms performed well; however, the RF was more accurate after iteration. The RF had a good capacity for indirect detection of PED, with an average accuracy of 60.9%. The wavelengths related to the red and red edges, especially from 710 to 735 nm, proved to be highly informative. As a result of the congruence between field and greenhouse data, the RECI, NDRE, VWI, and GRVI spectral indices were consistent with the discrimination of symptoms and PED severity levels. Identified wavelengths can be applied in the design of optical sensors that, together with the use of ML algorithms, can be implemented in the remote detection of early death in potato crops.@en

Solar energy is becoming increasingly important with the transition towards green and sustainable energy. Predicting solar irradiance is one of the core steps to optimise solar energy utilisation when planning and scheduling power grids. Accurate solar irradiance prediction can also help forecast microclimate conditions, enabling the analysis of citizens and planning of optimal intervention strategies for heating or cooling behaviour. This paper discusses a novel approach to computing the solar potential of buildings at the city level with promising scalability using semantic 3D city models. Experiments are conducted at different locations in the Netherlands. We evaluate our results by comparing them to the statistical Dutch data, and CitySim shows huge discrepancies in summer.@en

Current GIS software offer tools to perform the solar irradiance calculations. However, these computations based their work on data assumptions or generalisations to speed up their processing time. In this work, a method is shown to perform the calculation using very high and very low spatial resolution open datasets. The results show that there too detailed raster data like 50cm horizontal spatial resolution DSM does not improve the calculations compared to lower resolution datasets.@en

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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Indoor navigation is a complex task for people and especially for visually impaired ones. This research proposes an indoor navigation system oriented to visually impaired users, integrating the OGC IndoorGML and CityGML standards with Bluetooth Low Energy devices (BLE) by using the RSSI signal loss value and the Weighted Path Loss-techniques to calculate the user's location. This paper describes the design of the system and its implementation as a functional prototype in a mobile web application. Several operational tests were conducted to determine both the accuracy and precision of the user location. The user's positioning results show a root-mean-squared error (RMSE) of 0.88 m in a scenario with obstacles and no height difference of the BLE devices location, and a RMSE of 1.06 m in a scenario with obstacles and height difference. These results confirm the potential of the implemented prototype to grow into a fully operational system.

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3D city models are frequently used to acquire and store energy-related information of buildings for energy applications. In this context, CityGML is the most common data model, and the Energy ADE, one of its most complex extensions, provides a systematic way of storing detailed energy-related data in XML format. Contrarily, even though CityGML's JSON-based encoding, CityJSON, has an extension mechanism, an energy-related CityJSON Extension is missing. This paper, therefore, presents the first results of the development of a CityJSON Energy Extension and space heating demand calculation is utilized as the use case. The simplified version of the Energy ADE, called the Energy ADE KIT profile, is used to create a semi-direct translation to the CityJSON Energy Extension. This Extension is then validated through the official validator of CityJSON and the use case, and improvements are made considering the validation results. The space heating demand is calculated according to the Dutch standard NTA 8800 for a subset of Rijssen-Holten in the Netherlands although the solar gains calculation requires further review. The results show that the final CityJSON Energy Extension provides full support for space heating demand calculations based on the NTA 8800 and eliminates the deep hierarchical structure of the Energy ADE. A comparison on CityJSON file sizes shows a 25.2 MB increase after the required input data is stored in a CityJSON + Energy Extension file, which is not significant considering the high amount of data stored in the file. Overall, this paper shows that the CityJSON Energy Extension could provide an easy-to-use alternative to the CityGML Energy ADE.

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This document introduces the process for the creation of a testbed for energy applications based on a semantic 3D city model for the municipality of Rijssen-Holten in The Netherlands. The creation of this dataset requires the consolidation from multiple data sources as well as a lot of manual work so the authors can warranty as much as possible the quality of the dataset so in can be used in several use cases. The data is stored following the OGC standard CityGML v2.0 and contain the geometrical and semantical information of CityObjects from the thematic modules Building, Vegetation and Relief. This data set consolidates the open weather data from the closest weather station to the study area located in Heino in the Netherlands. We discuss the decisions taken during the manual data collection process and we present some use cases that have already consume the dataset at the time of writing this document.

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In the last 15 years semantic 3D city models have seen a steady growth in terms of creation and adoption. Many cities world-wide have now at least one city model which can be used for several applications. Energy- and sustainability-related topics are among those that have experienced a noteworthy increase of interest from the Geomatics community. 3D city models have become a steady component of Urban Energy Modelling, in which bottom-up approaches are developed to assess, for example, the energy efficiency of the building stock and to explore different scenarios of building refurbishment. Within this context, this paper focuses on investigating how much party walls can contribute to the energy demand estimation of a building. For this reason, two approaches to compute party walls are described and compared. The nature and the magnitude of their differences, as well as their possible impact on downstream applications, are considered in order to shed light on whether discrepancies in the amount of computed party wall area might lead to significant differences in terms energy demand of the residential building stock. The case study area is located in the Netherlands and encompasses the municipality of Rijssen-Holten.

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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.

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The rapid and precise detection of diseases and plant disorders is the basis for the adequate and timely design of management strategies. Currently, there are several non-destructive alternatives that allow early detection, highlighting the use of spectral cameras attached to unmanned aerial vehicles (UAVs). The objective of this research was to evaluate the use of multispectral cameras on UAVs to discriminate vascular wilt caused by Verticillium spp., (VW), waterlogging stress (WL), and an unknown alteration (UA) in commercial potato (Solanum tuberosum) variety “Diacol Capiro” crops. Plots were monitored during the crop cycle, performing the visual characterization of the diseases and disorders present. Five spectral band images were acquired using a MicaSense RedEdge spectral camera attached to a Map-T680 hexacopter drone to extract the bands and calculate the vegetation indices that were calibrated and evaluated to determine their ability to discriminate between diseased and healthy plants based on a generalized linear model (GLM) and Kappa index. Additionally, the supervised random forest classification method was implemented, optimized, and evaluated using the accuracy, area under receiver operating characteristic curve (ROC-AUC), kappa index, and inference error based on k-fold cross-validation. After algorithms optimization our results show a classifier accuracy, kappa and ROC-AUC values to VW, WL and UA between 73.5–82.5%, 0.56–0.71, 0.97–0.98, and 35 37.5–51.9%, 0.07–0.06, and 0.88–0.94 for plots 1 and 2, respectively. This study reports an approach to the use of multispectral cameras attached to UAVs as a tool with potential for the detection of diseases and physiological disorders in commercial potato crops.

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This article shows the development of an optimal location model, designed to respond to the deficit in the supply of justice facilities in the city of Bogotá D.C. - Colombia. This optimal location model considers criteria of spatial efficiency and territorial justice, as well as normative, geographical and social aspects that limit the selection of optimal sites and uses multicriteria analysis techniques based on fuzzy logic. This model aims to be a contribution to the planning and planning processes of the urban territory and constitutes a tool for spatial analysis focused on attending to the needs of security and coexistence in the city. El presente artículo muestra el desarrollo de un modelo de localización óptima, diseñado para responder ante el déficit en la oferta de equipamientos de justicia en la ciudad de Bogotá D. C. – Colombia. Este modelo de localización óptima tiene en cuenta criterios de eficiencia espacial y justicia territorial, así como aspectos normativos, geográficos y sociales que limitan la selección de los sitios óptimos, y utiliza técnicas de análisis multicriterio basado en lógica difusa. Este modelo pretende ser un aporte a los procesos de planificación y ordenación del territorio urbano y constituye una herramienta de análisis espacial enfocado en la atención de necesidades de seguridad y convivencia en la ciudad.@en

3D city models are playing a growing role worldwide as sources of integrated information upon which different urban applications are developed. In the context of urban planning and design, semantic 3D city models can provide plenty of qualitative and quantitative information about the urban context and of the area(s) to be transformed. This paper takes inspiration and continues a work recently published in which several design parameters and Key Performance Indicators are computed from a semantic 3D city model, and later used in a GIS-supported urban design process to develop a new area. As many of such parameters are derived from the gross volume of the building stock, this paper investigates whether and to which extent different building stock models might affect the estimation of the gross volume. The study is carried out in anticipation of the upcoming LoD2-based, country-wide model of the Netherlands that is being finalised by our team. At the same time, the paper investigates whether and which information can be obtained regarding the quality of the LoD2 model from a comparison with the LoD1 one, with a focus on volume calculation.

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