Assessment of Relative Accuracy of AHN-2 Laser Scanning Data Using Planar Features

AHN-2 is the second part of the Actueel Hoogtebestand Nederland project, which concerns the acquisition of high-resolution altimetry data over the entire Netherlands using airborne laser scanning. The accuracy assessment of laser altimetry data usually relies on comparing corresponding tie elements, often points or lines, in the overlapping strips. This paper proposes a new approach to strip adjustment and accuracy assessment of AHN-2 data by using planar features. In the proposed approach a transformation is estimated between two overlapping strips by minimizing the distances between points in one strip and their corresponding planes in the other. The planes and the corresponding points are extracted in an automated segmentation process. The point-to-plane distances are used as observables in an estimation model, whereby the parameters of a transformation between the two strips and their associated quality measures are estimated. We demonstrate the performance of the method for the accuracy assessment of the AHN-2 dataset over Zeeland province of The Netherlands. The results show vertical offsets of up to 4 cm between the overlapping strips, and horizontal offsets ranging from 2 cm to 34 cm

The Application of LiDAR to Assessment of Rooftop Solar Photovoltaic Deployment Potential in a Municipal District Unit

A methodology is provided for the application of Light Detection and Ranging (LiDAR) to automated solar photovoltaic (PV) deployment analysis on the regional scale. Challenges in urban information extraction and management for solar PV deployment assessment are determined and quantitative solutions are offered. This paper provides the following contributions: (i) a methodology that is consistent with recommendations from existing literature advocating the integration of cross-disciplinary competences in remote sensing (RS), GIS, computer vision and urban environmental studies; (ii) a robust methodology that can work with low-resolution, incomprehensive data and reconstruct vegetation and building separately, but concurrently; (iii) recommendations for future generation of software. A case study is presented as an example of the methodology. Experience from the case study such as the trade-off between time consumption and data quality are discussed to highlight a need for connectivity between demographic information, electrical engineering schemes and GIS and a typical factor of solar useful roofs extracted per method. Finally, conclusions are developed to provide a final methodology to extract the most useful information from the lowest resolution and least comprehensive data to provide solar electric assessments over large areas, which can be adapted anywhere in the world

Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas

Raytracing-based methods are widely used for quantifying irradiation on building surfaces. Urban 3D surface models are necessary input for raytracing simulations, which can be generated from open-source point cloud data with the help of surface reconstruction algorithms. In research and engineering practice, various algorithms are being used for this purpose; each leading to different mesh topologies and corresponding performance. This paper compares the impacts of four different reconstruction algorithms by investigating their performance using DAYSIM raytracing simulations. The analysis is carried out for five configurations with various urban morphologies. Results show that the reconstructed models consistently underestimate the shading influence due to geometrical shrinkages that emerge from the various model generation procedures. The explicit algorithms, with Generic Delaunay a notable example, have better performance with less embedded error than the implicit algorithms in both daily and annual simulations. Results also show that diffuse irradiance is responsible for larger contributions to the overall error than direct components. This effect becomes more prominent when modeling reflected irradiation in urban environments. Additionally, the work shows that solar elevation and shading geometry types also affect the error magnitude. The paper concludes by providing reconstruction algorithm selection criteria for photovoltaic practitioners and urban energy planners

AVALIAÇÃO AUTOMÁTICA DA ACURÁCIA RELATIVA DE DADOS LIDAR AEROTRANSPORTADO

Neste trabalho é proposto um método automático para o controle da acurácia relativa de dados LiDAR (Light Detection and Ranging) aerotransportados usando superfícies planas, linhas retas e pontos. Primeiramente, é realizada uma filtragem dos dados LiDAR, através do filtro morfológico progressivo e o filtro RANSAC (Random Sample Consensus). Em seguida, as superfícies planas são extraídas automaticamente sobre os telhados encontrados nas faixas adjacentes através do algoritmos crescimento de região. Posteriormente, as correspondências entre as feições extraídas em cada faixa são estabelecidas e os parâmetros de transformação são estimados através de uma variante do método ICP. Finalmente, para avaliar simultaneamente a acurácia plani-altimétrica dos dados LiDAR são empregadas linhas retas extraídas a partir da interseção de planos adjacentes. Para avaliar o método proposto foi conduzido um experimento com dados LiDAR obtidos numa região urbanizada recoberta por 2 faixas com densidade de 1 ponto/m². A avaliação da acurácia relativa desses dados é realizada automaticamente e os resultados obtidos com o método proposto mostraram que a média das distâncias ponto-a-plano é de -0,0019 cm e a raiz quadrada do erro médio quadrático é de 6,04 cm

UM MÉTODO ADAPTATIVO PARA REGISTRO DE DADOS RGB-D

Neste trabalho é apresentado um método adaptativo para registro e mapeamento de ambientes internos com regiões de pouca textura usando dados derivados de câmeras RGB-D. Basicamente, quatro pontos principais envolvidos no desenvolvimento do método são aqui discutidos: a calibração dos sensores integrados no dispositivo Kinect; o registro dos pares de nuvens de pontos 3D adquiridas sucessivamente pelo sensor de imageamento; a inclusão de pesos no algoritmo ICP baseado em abordagem ponto-a-ponto; e o refinamento dos parâmetros de transformação empregando uma análise de consistência global. A calibração dos sensores é feita usando o método de Zhang. O modelo de corpo rígido 3D é empregado para calcular os parâmetros de transformação. Um método adaptativo é proposto para inclusão de pesos baseados na precisão teórica das medidas de profundidade. Um modelo linear capaz de refinar simultaneamente o conjunto de parâmetros de transformação é proposto para a análise da consistência global. Experimentos foram conduzidos para avaliar a eficiência do método proposto e os resultados obtidos mostraram sua potencialidade

Avaliação automática de acurácia relativa de dados LiDAR aerotransportado

Orientadores : Prof. Dr. Daniel Rodrigues dos SantosDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências da Terra, Programa de Pós-Graduação em Ciências Geodésicas. Defesa: Curitiba, 17/03/2015Inclui referências : f. 97-100Resumo: Neste trabalho é proposto um método automático para o controle da qualidade posicional relativa de dados LiDAR aerotransportados através da comparação de feições pontuais, lineares e superfícies planas correspondentes extraídas em faixas adjacentes. O método proposto permite a avaliação simultânea da acurácia altimétrica e planimétrica com elevado grau de automação e a detecção de erros sistemáticos sem a necessidade de empregar dados externos. O método é dividido em quatro etapas. Primeiramente, é realizado um pré-processamento seguido de uma filtragem dos dados LiDAR. Em seguida, as superfícies planas são extraídas automaticamente sobre os telhados encontrados nas faixas adjacentes. Posteriormente, as correspondências entre as feições extraídas em cada faixa são estabelecidas e os parâmetros de rotação e translação são estimados através de uma variante do método ICP. A variação do método ICP proposta tem por finalidade minimizar o somatório da distância entre pontos e planos correspondentes. Por fim, para realizar a avaliação simultânea da acurácia altimétrica e planimétrica, são empregadas linhas retas extraídas a partir da interseção de planos adjacentes. Para avaliação do método proposto foram conduzidos experimentos com dados obtidos por varredura LiDAR em duas regiões distintas, sendo uma delas recoberta por 2 faixas com densidade de 1 ponto/m² e a outra recoberta por 11 faixas com densidade de 5 ponto/m². Os resultados encontrados mostram a eficiência e a potencialidade do método proposto. Palavras-Chave: LiDAR. RANSAC. ICP. Superfícies Planas. Linhas Retas.Abstract: An automatic method for internal quality control evaluation of airborne LiDAR data by comparing corresponding planar, linear and punctual features extracted in overlapping strips is proposed. The proposed method allows the simultaneous evaluation of altimetric and planimetric relative accuracy, systematic errors detection using no external data and the high degree of automation. Our method work following four main tasks. First, the LiDAR data is pre-processed and filtered. Then, the planar surfaces are automatically extracted from the planar roofs in both strips. After, the correspondences between extracted features in each strip are established and the rotation and translation parameters are estimated by a variant of ICP method. This variant aims to minimize the sum of the distance between points and corresponding planes. Finally, in order to evaluate simultaneously planimetric and altimetric accuracy, straight lines formed by the intersection of two adjacent surface planes are used. Experiments were conducted to evaluate the proposed method, using LiDAR data obtained from two different regions. In the first experiment was used 2 overlapping LiDAR strips, whose density is 1 point / m², while in the last experiment was used 11 overlapping LiDAR strips with a point density of 5 point / m². The results obtained showed the efficiency and the potential of the proposed method. Keywords: LiDAR. RANSAC. ICP. Planar surfaces. Straight lines

Development of a novel data acquisition and processing methodology applied to the boresight alignment of marine mobile LiDAR systems

Le système LiDAR mobile (SLM) est une technologie d'acquisition de données de pointe qui permet de cartographier les scènes du monde réel en nuages de points 3D. Les applications du SLM sont très vastes, de la foresterie à la modélisation 3D des villes, en passant par l'évaluation de l'inventaire routier et la cartographie des infrastructures portuaires. Le SLM peut également être monté sur diverses plateformes, telles que des plateformes aériennes, terrestres, marines, etc. Indépendamment de l'application et de la plateforme, pour s'assurer que le SLM atteigne sa performance optimale et sa meilleure précision, il est essentiel de traiter correctement les erreurs systématiques du système, spécialement l'erreur des angles de visée à laquelle on s'intéresse particulièrement dans cette thèse. L'erreur des angles de visée est définie comme le désalignement rotationnel des deux parties principales du SLM, le système de positionnement et d'orientation et le scanneur LiDAR, introduit par trois angles de visée. En fait, de petites variations angulaires dans ces paramètres peuvent causer des problèmes importants d'incertitude géométrique dans le nuage de points final et il est vital d'employer une méthode d'alignement pour faire face à la problématique de l'erreur des angles de visée de ces systèmes. La plupart des méthodes existantes d'alignement des angles de visée qui ont été principalement développées pour les SLM aériens et terrestres, tirent profit d'éléments in-situ spécifiques et présents sur les sites de levés et adéquats pour ces méthodes. Par exemple, les éléments linéaires et planaires extraits des toits et des façades des maisons. Cependant, dans les environnements sans présence de ces éléments saillants comme la forêt, les zones rurales, les ports, où l'accès aux éléments appropriées pour l'alignement des angles de visée est presque impossible, les méthodes existantes fonctionnent mal, voire même pas du tout. Par conséquent, cette recherche porte sur l'alignement des angles de visée d'un SLM dans un environnement complexe. Nous souhaitons donc introduire une procédure d'acquisition et traitement pour une préparation adéquate des données, qui servira à la méthode d'alignement des angles de visée du SLM. Tout d'abord, nous explorons les différentes possibilités des éléments utilisés dans les méthodes existantes qui peuvent aider à l'identification de l'élément offrant le meilleur potentiel pour l'estimation des angles de visée d'un SLM. Ensuite, nous analysons, parmi un grand nombre de possibles configurations d'éléments (cibles) et patrons de lignes de balayage, celle qui nous apparaît la meilleure. Cette analyse est réalisée dans un environnement de simulation dans le but de générer différentes configurations de cibles et de lignes de balayage pour l'estimation des erreurs des angles de visée afin d'isoler la meilleure configuration possible. Enfin, nous validons la configuration proposée dans un scénario réel, soit l'étude de cas du port de Montréal. Le résultat de la validation révèle que la configuration proposée pour l'acquisition et le traitement des données mène à une méthode rigoureuse d'alignement des angles de visée qui est en même temps précise, robuste et répétable. Pour évaluer les résultats obtenus, nous avons également mis en œuvre une méthode d'évaluation de la précision relative, qui démontre l'amélioration de la précision du nuage de points après l'application de la procédure d'alignement des angles de visée.A Mobile LiDAR system (MLS) is a state-of-the-art data acquisition technology that maps real-world scenes in the form of 3D point clouds. The MLS's list of applications is vast, from forestry to 3D city modeling and road inventory assessment to port infrastructure mapping. The MLS can also be mounted on various platforms, such as aerial, terrestrial, marine, and so on. Regardless of the application and the platform, to ensure that the MLS achieves its optimal performance and best accuracy, it is essential to adequately address the systematic errors of the system, especially the boresight error. The boresight error is the rotational misalignment offset of the two main parts of the MLS, the positioning and orientation system (POS) and the LiDAR scanner. Minor angular parameter variations can cause important geometric accuracy issues in the final point cloud. Therefore, it is vital to employ an alignment method to cope with the boresight error problem of such systems. Most of the existing boresight alignment methods, which have been mainly developed for aerial and terrestrial MLS, take advantage of the in-situ tie-features in the environment that are adequate for these methods. For example, tie-line and tie-plane are extracted from building roofs and facades. However, in low-feature environments like forests, rural areas, ports, and harbors, where access to suitable tie-features for boresight alignment is nearly impossible, the existing methods malfunction or do not function. Therefore, this research addresses the boresight alignment of a marine MLS in a low-feature maritime environment. Thus, we aim to introduce an acquisition procedure for suitable data preparation, which will serve as input for the boresight alignment method of a marine MLS. First, we explore various tie-features introduced in the existing ways that eventually assist in the identification of the suitable tie-feature for the boresight alignment of a marine MLS. Second, we study the best configuration for the data acquisition procedure, i.e., tie-feature(s) characteristics and the necessary scanning line pattern. This study is done in a simulation environment to achieve the best visibility of the boresight errors on the selected suitable tie-feature. Finally, we validate the proposed configuration in a real-world scenario, which is the port of Montreal case study. The validation result reveals that the proposed data acquisition and processing configuration results in an accurate, robust, and repeatable rigorous boresight alignment method. We have also implemented a relative accuracy assessment to evaluate the obtained results, demonstrating an accuracy improvement of the point cloud after the boresight alignment procedure