Modelling of roof geometries from low-resolution LiDAR data for city-scale solar energy applications using a neighbouring buildings method

Gooding, James; Crook, R.; Tomlin, Alison S.

doi:10.1016/j.apenergy.2015.03.013

Cited by 54 publications

(21 citation statements)

References 24 publications

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“…Nevertheless, very few outliers with significantly large differences (up to 6°) occur. The latter observation is also reported by other research groups (e.g., Gooding et al [35], Truong-Hong and Laefer [39]). The differences of the plane sizes are larger for all data types, approximately 12%-13% with the exception of the results for LiDAR at the test site Karlsruhe (18.4%) which affect the resulting energy yield significantly.…”

Section: Roof Plane Extractionsupporting

confidence: 76%

“…The results of usable solar radiation obtained from different input raster data mentioned above are then compared. Gooding et al [35] have created a model-driven approach especially for low point densities by grouping similar buildings together to increase the number of points on the roof structures. The quality evaluation delivers an identification rate of 87% and a mean absolute error of 3.76˝for roof slopes.…”

Section: Suitability Of Roof Planes For Resmentioning

confidence: 99%

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Quality Assessment of Roof Planes Extracted from Height Data for Solar Energy Systems by the EAGLE Platform

et al. 2015

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Due to the increasing scarcity of fossil fuels and the upwards trend in energy costs over time, many countries-especially in Europe-have begun to modify their energy policies aiming to increase that percentage obtained from renewable energies. The EAGLE (FP7 program, European Commission) has developed a web-based platform to promote renewable energy systems (RES) in the public and private sectors, and to deliver a comprehensive information source for all interested users. In this paper, a comprehensive quality assessment of extracted roof planes suitable for solar energy installations (photovoltaic, solar thermal) from height data derived automatically from both LiDAR (Light Detection and Ranging) and aerial images will be presented. A shadow analysis is performed regarding the daily path of the sun including the shading effects of nearby objects (chimneys, dormers, vegetation, buildings, topography, etc.). A quality assessment was carried out for both LiDAR and aerial images of the same test sites in UK and Germany concerning building outline accuracy, extraction rate of roof planes and the accuracy of their geometric parameters (inclination and aspect angle, size). The benefit is an optimized system to extract roof planes for RES with a high level of detail, accuracy and flexibility (concerning different commonly available data sources) including an estimation of quality of the results which is important for individual house owners as well as for regional applications by governments or solar energy companies to judge their usefulness.

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Section: Roof Plane Extractionsupporting

confidence: 76%

Section: Suitability Of Roof Planes For Resmentioning

confidence: 99%

Quality Assessment of Roof Planes Extracted from Height Data for Solar Energy Systems by the EAGLE Platform

et al. 2015

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“…This application may benefit from attributes such as the address and type of building for additional analyses [108], and it is being supported by an increasing number of software implementations [109,110]. Furthermore, some researchers use dense point clouds rather than semantic 3D city models (e.g., [111][112][113][114]). For a comprehensive overview of research on solar potential applications see the recent review of Freitas et al [115].…”

Section: Estimation Of the Solar Irradiationmentioning

confidence: 99%

Applications of 3D City Models: State of the Art Review

Biljecki

Stoter

Ledoux

et al. 2015

IJGI

610

380

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In the last decades, 3D city models appear to have been predominantly used for visualisation; however, today they are being increasingly employed in a number of domains and for a large range of tasks beyond visualisation. In this paper, we seek to understand and document the state of the art regarding the utilisation of 3D city models across multiple domains based on a comprehensive literature study including hundreds of research papers, technical reports and online resources. A challenge in a study such as ours is that the ways in which 3D city models are used cannot be readily listed due to fuzziness, terminological ambiguity, unclear added-value of 3D geoinformation in some instances, and absence of technical information. To address this challenge, we delineate a hierarchical terminology (spatial operations, use cases, applications), and develop a theoretical reasoning to segment and categorise the diverse uses of 3D city models. Following this framework, we provide a list of identified use cases of 3D city models (with a description of each), and their applications. Our study demonstrates that 3D city models are employed in at least 29 use cases that are a part of more than 100 applications. The classified inventory could be useful for scientists as well as stakeholders in the geospatial industry, such as companies and national mapping agencies, as it may serve as a reference document to better position their operations, design product portfolios, and to better understand the market.

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“…on buildings), which may be performed on different sets of data, e.g. voxels (Hofierka and Zlocha 2012), lidar point clouds (Carneiro and Golay 2009, Jochem et al 2009, Yu et al 2009, Gooding et al 2015, and the ones with building data, e.g. derived with a combination of lidar and GIS data (Jakubiec and Reinhart 2013).…”

Section: General Overview Of the 3d Use Casementioning

confidence: 99%

Propagation of positional error in 3D GIS: estimation of the solar irradiation of building roofs

Biljecki

Heuvelink

Ledoux

et al. 2015

International Journal of Geographical Information Science

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While error propagation in GIS is a topic that has received a lot of attention, it has not been researched with 3D GIS data. We extend error propagation to 3D city models using a Monte Carlo simulation on a use case of annual solar irradiation estimation of building rooftops for assessing the efficiency of installing solar panels. Besides investigating the extension of the theory of error propagation in GIS from 2D to 3D, this paper presents the following contributions. We (1) introduce varying XY/Z accuracy levels of the geometry to reflect actual acquisition outcomes; (2) run experiments on multiple accuracy classes (121 in total); (3) implement an uncertainty engine for simulating acquisition positional errors to procedurally modelled (synthetic) buildings; (4) perform the uncertainty propagation analysis on multiple levels of detail (LODs); and (5) implement Solar3Dcity -a CityGML-compliant software for estimating the solar irradiation of roofs, which we use in our experiments. The results show that in the case of the city of Delft in the Netherlands, a 0.3/0.6 m positional uncertainty yields an error of 68 kWh/m 2 /year (10%) in solar irradiation estimation. Furthermore, the results indicate that the planar and vertical uncertainties have a different influence on the estimations, and that the results are comparable between LODs. In the experiments we use procedural models, implying that analyses are carried out in a controlled environment where results can be validated. Our uncertainty propagation method and the framework are applicable to other 3D GIS operations and/ or use cases. We released Solar3Dcity as open-source software to support related research efforts in the future.

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Modelling of roof geometries from low-resolution LiDAR data for city-scale solar energy applications using a neighbouring buildings method

Cited by 54 publications

References 24 publications

Quality Assessment of Roof Planes Extracted from Height Data for Solar Energy Systems by the EAGLE Platform

Quality Assessment of Roof Planes Extracted from Height Data for Solar Energy Systems by the EAGLE Platform

Applications of 3D City Models: State of the Art Review

Propagation of positional error in 3D GIS: estimation of the solar irradiation of building roofs

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