Geodaysit 2023

In cities, the building sector is the main responsible for energy consumption and carbon dioxide emissions. However, there is a high potential for energy saving by renovating the buildings themselves and the decision-making process to primarily focus on them in the development of smart cities. Several policies have been drafted to set a path towards the mitigation of such impacts, decarbonising the energy supply and reducing the total energy demand. Nevertheless, from a smart city-oriented perspective, it is crucial to elaborate tools to support the choices of policymakers and make citizens aware. Remotely sensed data can be used for assessing the current state, thus simulating possible improvements. Existing literature shows extensive use of infrared thermography for assessing discrete buildings, while little has been done on a district or urban scale.

In this contribution, we present the potential of Aerial Infrared Thermography and LiDAR point clouds for defining energy uses and the potential photovoltaic production. First, AIT is used for energy classification, a key parameter for estimating the current energy demand. Then, two alternative retrofitting scenarios – proposing an improvement by two classes and an upgrade of the whole building stock to meet the highest standards – are compared in terms of primary energy savings and prevented emissions. Options are taken into account also considering the energy supply option, with the possibility of installing photovoltaic panels to power heating pumps as an alternative to traditional heating methods, i.e. district heating and natural gas boilers.

In addition to Infrared thermography, aerial LiDAR point clouds are also key data for planning and managing the energy resources in cities. The efficiency of solar panels primarily depends on the incidence angle of the radiation on the panels and, therefore, proper planning is crucial for the installation and setup of solar plants. One of the possible applications of LiDAR point clouds for the energy sector is to support this phase to maximise efficiency. Thanks to the 3D classified LiDAR point clouds, it is possible to extract the buildings with precise restitution of the pitches, their dimension and orientation, then categorising them into planar/flat, slant or dome types in order to estimate the angle of incidence of sunlight radiations and to better assess the maximum solar potential. In this way, an accurate data sheet for each building can be drafted, reporting precise data on theoretical production and usable surface.

Future developments are related to the development of three-dimensional energy models, to be updated regularly, able to describe precisely the current situation and simulate alternative scenarios. The state of the art smart city digital twins can be also employed for the purpose of urban energy management and to capture and understand the urban energy complexities with respect to time. The concept of energy community can be also introduced at a local level where neighbourhoods generate and share the energy generated from renewable sources.

The new concept of Digital Twins (DT) as a city model is interlinked with the Smart City applications on many levels, like interactivity between virtual model and real world, simulations and analysis of present and planned city, emergency planning and management to mention a few. The strength of DT is related to the incorporation of time as a fourth dimension, considering the time as a variable that modifies the data and the semantic information. The aim of this emerging concept DT is provide a physical infrastructure, data, information and procedures for the management of a complex system, in order to offer to the public administration a platform for designing, testing, simulations and analysis of present and planned city, and offer through web-sharing high quality urban 3D model as open data to all operators in Open Source (OS) environments. There are several applications to share on the web a 3D model, but the lack of a detailed and adequately sized development platform is a bottleneck in this contest. The purposes of this work are based on the Torino DT project, source data for the 3D model had been acquired from images and point clouds data sets from 2022. The first step after the acquisition phase have been the source data processing, in order to build up a 3D model of the entire city. There have been rapid technological developments in the field of photogrammetric and LiDAR techniques to produce detailed and accurate 3D models. 3D point clouds from the state of the art LiDAR and photogrammetry provides a powerful collection of geometric elements of a scene with their position, orientation and shape in the 3D space. There are numerous computer vision programs like 3D Zephyr, VisualSfM, meshroom, WebODm etc which offers OS solutions for the 3D reconstruction processing from 2D images. The processing capabilities of these open source solutions are comparable as compared to the commercial ones in terms of geometric features and information. These open source tools are adequate for the research purposes to explore the potential of 3D models from photogrammetry and LiDAR. 3D model is based on a reality mesh model with a specific and well-known work-flow. The next step is share, part of, the 3D model in OS environments that can be accessed with JavaScript code like Cesium platform. 3D web platforms analyzed in this work reflect the ever greater interest in OS software, interoperability and collaboration standards, in order to work in the openness ecosystem. This research field open the way to new opportunities, for instance DT as Open Data. The free availability of an urban 3D model, build up from the reality, could create a new order of opportunity for future model updates or utilizations, especially for real estate operators. Furthermore, particular attention has been paid to model update with collaborative and crowdsourcing solutions, with the perspective to develop a community able to use and update the 3D model.