The Application of LiDAR Data for the Solar Potential Analysis Based on Urban 3D Model

Abstract

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.

Remote Sensing for Monitoring Photovoltaic Solar Plants in Brazil Using Deep Semantic Segmentation

“…The present research had the following methodological steps (Figure 1 nighttime light satellite imagery [50][51][52], among others. In solar energy, many studies use remote sensing images, such as solar energy estimates [53][54][55][56], solar power plant site selection [57][58][59][60][61][62], PV potential on building rooftops [63][64][65][66], and area estimation [67,68].…”

“…Remote sensing data (aerial photography and satellite imagery) enable inspection periodically, and have been widely used in the electrical sector for effective maintenance of electrical lines [39][40][41], thermal monitoring from nuclear power plants [42][43][44][45], environmental changes from hydroelectric dams [46][47][48][49], and energy consumption using nighttime light satellite imagery [50][51][52], among others. In solar energy, many studies use remote sens-ing images, such as solar energy estimates [53][54][55][56], solar power plant site selection [57][58][59][60][61][62], PV potential on building rooftops [63][64][65][66], and area estimation [67,68].…”

Editorial for Special Issue “Remote Sensing in Applications of Geoinformation”

“…Three dimensional visualization also offers a more accurate and intuitive perspective of reality than 2D maps. The paper by Prieto et al [7] presents a new method for the calculation and visualization of the solar potential of building roofs in an urban 3D model, based on LiDAR data. The paper describes the proposed methodology to (a) calculate the solar potential, (b) generate an urban 3D model, (c) semanticize the urban 3D model with different existing and calculated data and (d) visualize the urban 3D model in a 3D web environment.…”

606. Retos metodológicos para estudiar la vulnerabilidad demográfica y residencial a nivel intraurbano ante los cambios en las fuentes estadísticas habituales

“…Así, recurriendo al modelo de datos estándar CityGML y más exactamente a los niveles de detalle LOD 56 2 y 3 se puede integrar información volumétrica con materiales de fachadas, cubiertas, etc. Estos modelos contarían con aplicaciones de interés tanto en la temática que nos ocupa, como en otros temas relevantes en entornos urbanos, como son la planificación urbana, o dotación de las redes y servicios, entre otros 57 .…”