LiDAR and SfM-MVS Integrated Approach to Build a Highly Detailed 3D Virtual Model of Urban Areas

The three-dimensional reconstruction of buildings, road infrastructures, service networks, and cultural heritage in urban environments is relevant for many market segments and numerous functions in the management and coordination of public authorities. These stakeholders are showing increasing interest in modern acquisition and reconstruction technologies for digital models typical of the geomatic and computer vision disciplines. In this context, it is essential to methodically exploit the potential of active and passive instruments and apply multi-sensor integration techniques, to obtain metrically accurate and high-resolution products. This study proposes a multi-sensor and multi-scale approach for high-resolution 3D model reconstruction focused on a city portion of Turin (Italy). We performed an integrated survey based on LiDAR and photogrammetric techniques, both aerial and terrestrial. Then we produced a set of 3D digital products for (i) promoting the historical and artistic heritage through Virtual Reality (VR) applications, (ii) supporting the restoration of Baroque buildings, and (iii) providing advanced analysis concerning the alteration of the urban road system. The final output describes in detail the architectural elements investigated (e.g., 9,480,000 tringles to define the mesh of a statue). It emphasizes the need for deepening sensor integration and data fusion

Technical Guidelines to Extract and Analyze VGI from Different Platforms

An increasing number of Volunteered Geographic Information (VGI) and social media platforms have been continuously growing in size, which have provided massive georeferenced data in many forms including textual information, photographs, and geoinformation. These georeferenced data have either been actively contributed (e.g., adding data to OpenStreetMap (OSM) or Mapillary) or collected in a more passive fashion by enabling geolocation whilst using an online platform (e.g., Twitter, Instagram, or Flickr). The benefit of scraping and streaming these data in stand-alone applications is evident, however, it is difficult for many users to script and scrape the diverse types of these data. On 14 June 2016, a pre-conference workshop at the AGILE 2016 conference in Helsinki, Finland was held. The workshop was called “LINK-VGI: LINKing and analyzing VGI across different platforms”. The workshop provided an opportunity for interested researchers to share ideas and findings on cross-platform data contributions. One portion of the workshop was dedicated to a hands-on session. In this session, the basics of spatial data access through selected Application Programming Interfaces (APIs) and the extraction of summary statistics of the results were illustrated. This paper presents the content of the hands-on session including the scripts and guidelines for extracting VGI data. Researchers, planners, and interested end-users can benefit from this paper for developing their own application for any region of the world

Automatic Alignment of 3D Multi-Sensor Point Clouds

Automatic 3D point cloud alignment is a major research topic in photogrammetry, computer vision and computer graphics. In this research, two keypoint feature matching approaches have been developed and proposed for the automatic alignment of 3D point clouds, which have been acquired from different sensor platforms and are in different 3D conformal coordinate systems. The first proposed approach is based on 3D keypoint feature matching. First, surface curvature information is utilized for scale-invariant 3D keypoint extraction. Adaptive non-maxima suppression (ANMS) is then applied to retain the most distinct and well-distributed set of keypoints. Afterwards, every keypoint is characterized by a scale, rotation and translation invariant 3D surface descriptor, called the radial geodesic distance-slope histogram. Similar keypoints descriptors on the source and target datasets are then matched using bipartite graph matching, followed by a modified-RANSAC for outlier removal. The second proposed method is based on 2D keypoint matching performed on height map images of the 3D point clouds. Height map images are generated by projecting the 3D point clouds onto a planimetric plane. Afterwards, a multi-scale wavelet 2D keypoint detector with ANMS is proposed to extract keypoints on the height maps. Then, a scale, rotation and translation-invariant 2D descriptor referred to as the Gabor, Log-Polar-Rapid Transform descriptor is computed for all keypoints. Finally, source and target height map keypoint correspondences are determined using a bi-directional nearest neighbour matching, together with the modified-RANSAC for outlier removal. Each method is assessed on multi-sensor, urban and non-urban 3D point cloud datasets. Results show that unlike the 3D-based method, the height map-based approach is able to align source and target datasets with differences in point density, point distribution and missing point data. Findings also show that the 3D-based method obtained lower transformation errors and a greater number of correspondences when the source and target have similar point characteristics. The 3D-based approach attained absolute mean alignment differences in the range of 0.23m to 2.81m, whereas the height map approach had a range from 0.17m to 1.21m. These differences meet the proximity requirements of the data characteristics and the further application of fine co-registration approaches

Terrestrial Laser Scanner and Close Range Photogrammetry point clouds accuracy assessment for the structure deformations monitoring

In this paper we show the results of several tests carried out using methods and instrumentation typical of an architectural survey, along with a set of metrological instrumentation, on a Reinforced Concrete (RC) beam subjected to increasing loads. The goal was to assess the accuracy in the displacements estimated by a medium quality terrestrial laser scanner (TLS) Focus 3d from Faro Technologies, and the low-cost digital camera Canon PowerShot S110 used in a Close Range Photogrammetry (CRP) survey. The software used for scan-data and point clouds processing was Reconstructor JRC Software v. 3.1.0, maintained by Gexcel Ltd, while the images processing was performed with the software Photoscan from Agisoft, which implements Structure from Motion (SfM) approach. Two processing strategies were used in the point clouds comparison: mesh2mesh and modelling the beam behavior fitting the contours of the beam with second order polynomials. Comparisons between the TLS and CRP techniques and the metrological equipment used in parallel highlighted the limits and potentialities of the two geomatic techniques used. It has been shown that modeling the behavior of the beam leads to significantly better results than using the mesh2mesh comparison. For the CRP the increase in accuracy was in the order of 40%, while for the TLS of 50%

Representing and Indexing Archaeological Information

The need to preserve and remember the past is a particular human trait. The richness of our cultural history is approached by a vast array of disciplines, that investigate and manage it. However, their effectiveness can be hindered by several technical issues. One of the concerns of experts in this area is the way the importance of cultural heritage is communicated in order to cultivate interest, curiosity and respect. Another concern is the lack of suitable tools that can handle the dimension and complexity of the collections with which they interact. With the emergence of digital tools and the creation of online repositories for the collections of cultural institutions, it is possible to suggest different solutions to tackle these problems. The proposed solution aims to facilitate access and interaction with cultural information, through the implementation of an application capable of integrating multiple forms of representation of historical artifacts. The application tackles two problems that arise from distinct goals. One is the need to represent, in a single view, collections of related items from different repositories. The other is how to, effectively, communicate the information associated with an artifact and its context. This MSc dissertation is part of a collaborative effort between NOVA LINCS researchers and several archaeological institutions of the Iberian Extremadura, aiming to develop tools that will support research and help sharing the cultural wealth of archaeological sites and artifacts from the region. In this dissertation, the developed application covers a general view of the aforementioned problems, while being flexible to the customization of the representation of cultural data. The solution was evaluated on usability and effectiveness on reaching the proposed goals, during a process that involved target audience users and experts in the area of culture and history, as well as human-computer interaction. The results provided positive conclusions

The role of control network in the accuracy of underground laser scanning surveys

Terrestrial laser scanning is used in various fields with numerous applications, one being the documentation of heritage sites. Often scans will be georeferenced with respect to a real-world coordinate system. This is done using either direct or indirect georeferencing techniques. The indirect georeferencing method was used in this research, which uses coordinated targets, referred to as Ground Control Points (GCPs), that are captured in the scan scene. Manufacturers suggest a minimum of three GCPs are used, should the z-axis not be vertical, with additional GCPs for redundancy. Ideally GCPs should be placed evenly around the extent of the scan scene. For heritage site documentation, this is not always feasible given the unique and complex nature of each site. This research investigates the quantity and spatial variability of GCPs used in a scan scene, and the subsequent effect on the point cloud accuracy. A control test network was established at the School of Surveying (SoS), where variations of GCP scenarios were investigated, which was then applied to a case study in Arras, France. The case study being a network of underground World War One tunnels that were excavated by the New Zealand Engineering Tunnelling Company (NZETC), known as the Ronville Tunnels. The results from the SoS test network show, in this particular instance, that there is little benefit in using additional GCPs in a scan scene, should the minimum (three) be placed evenly around the extent of the area being captured. Low redundancy solutions may reduce the accuracy and robustness of georeferencing solutions, as seen with the case where large errors were present where the minimum number of GCPs were used. Geometrically poor placement of GCPs shows an increased correlation between the check points root mean square errors and range from the GCP centroid. The case study results, where the scan scene extents were hundreds of metres long, showed that it is necessary to supplement the minimum number of GCPs to mitigate uncertainties in the point cloud dataset. Similar to a least squares estimation adjustment where there are less fixed stations, there is more uncertainty for an unknown position. GCPs should therefore, be placed spatially around the extents of the scan scene and where scan scene extents increase so should the number of GCPs

Update urban basemap by using the LiDAR mobile mapping system : the case of Abu Dhabi municipal system

Basemaps are the main resource used in urban planning and in building and infrastructure asset management. These maps are used by citizens and by private and public stakeholders. Therefore, accurate, up-to-date geoinformation of reference are needed to provide a good service. In general, basemaps have been updated by aerial photogrammetry or field surveying, but these methods are not always possible and alternatives need to be sought. Current limitations and challenges that face traditional field surveys include areas with extreme weather, deserts or artic environments, and flight restrictions due to proximity with other countries if there is not an agreement. In such cases, alternatives for large-scale are required. This thesis proposes the use of a mobile mapping system (MMS) to update urban basemaps. Most urban features can be extracted from point cloud using commercial software or open libraries. However, there are some exceptions: manhole covers, or hidden elements even with captures from defferent perspective, the most common building corners. Therefore, the main objective of this study was to establish a methodology for extracting manholes automatically and for completing hidden corners of buildings, so that urban basemaps can be updated. The algorithm developed to extract manholes is based on time, intensity and shape detection parameters, whereas additional information from satellite images is used to complete buildings. Each municipality knows the materials and dimensions of its manholes. Taking advantage of this knowledge, the point cloud is filtered to classify points according to the set of intensity values associated with the manhole material. From the classified points, the minimum bounding rectangles (MBR) are obtained and finally the shape is adjusted and drawn. We use satellite imagery to automatically digitize the layout of building footprints with automated software tools. Then, the visible corners of buildings from the LiDAR point cloud are imported and a fitting process is performed by comparing them with the corners of the building from the satellite image. Two methods are evaluated to establish which is the most suitable for adjustment in these conditions. In the first method, the differences in X and Y directions are measured in the corners, where LiDAR and satellite data are available, and is often computed as the average of the offsets. In the second method, a Helmert 2D transformation is applied. MMS involves Global Navigation Satellite Systems (GNSS) and Inertial Measurement Units (IMU) to georeference point clouds. Their accuracy depends on the acquisition environment. In this study, the influence of the urban pattern is analysed in three zones with varied urban characteristics: different height buildings, open areas, and areas with a low and high level of urbanization. To evaluate the efficiency of the proposed algorithms, three areas were chosen with varying urban patterns in Abu Dhabi. In these areas, 3D urban elements (light poles, street signs, etc) were automatically extracted using commercial software. The proposed algorithms were applied to the manholes and buildings. The completeness and correctness ratio, and geometric accuracy were calculated for all urban elements in the three areas. The best success rates (>70%) were for light poles, street signs and road curbs, regardless of the height of the buildings. The worst rate was obtained for the same features in peri-urban areas, due to high vegetation. In contrast, the best results for trees were found in theses areas. Our methodology demonstrates the great potential and efficiency of mobile LiDAR technology in updating basemaps; a process that is required to achieve standard accuracy in large scale maps. The cost of the entire process and the time required for the proposed methodology was calculated and compared with the traditional method. It was found that mobile LiDAR could be a standard cost-efficient procedure for updating maps.La cartografía de referencia es la principal herramienta en planificación urbanística, y gestión de infraestructuras y edificios, al servicio de ciudadanos, empresas y administración. Por esta razón, debe estar actualizada y ser lo más precisa posible. Tradicionalmente, la cartografía se actualiza mediante fotogrametría aérea o levantamientos terrestres. No obstante, deben buscarse alternativas válidas para escalas grandes, porque no siempre es posible emplear estas técnicas debido a las limitaciones y retos actuales a los que se enfrenta la medición tradicional en algunas zonas del planeta, con meteorología extrema o restricciones de vuelo por la proximidad a la frontera con otros países. Esta tesis propone el uso del sistema Mobile Mapping System (MMS) para actualizar la cartografía urbana de referencia. La mayoría de los elementos pueden extraerse empleando software comercial o librerías abiertas, excepto los registros de servicios. Los elementos ocultos son otro de los inconvenientes encontrados en el proceso de creación o actualización de la cartografía, incluso si se dispone de capturas desde diferentes puntos de vista. El caso más común es el de las esquinas de edificios. Por ello, el principal objetivo de este estudio es establecer una metodología de extracción automática de los registros y completar las esquinas ocultas de los edificios para actualizar cartografía urbana. El algoritmo desarrollado para la detección y extracción de registros se basa en parámetros como el tiempo, la intensidad de la señal laser y la forma de los registros, mientras que para completar los edificios se emplea información adicional de imágenes satélite. Aprovechando el conocimiento del material y dimensión de los registros, en disposición de los gestores municipales, el algoritmo propuesto filtra y clasifica los puntos de acuerdo a los valores de intensidad. De aquellos clasificados como registros se calcula el mínimo rectángulo que los contiene (Minimum Bounding Rectangle) y finalmente se ajusta la forma y se dibuja. Las imágenes de satélite son empleadas para obtener automáticamente la huella de los edificios. Posteriormente, se importan las esquinas visibles de los edificios obtenidas desde la nube de puntos y se realiza el ajuste comparándolas con las obtenidas desde satélite. Para llevar a cabo este ajuste se han evaluado dos métodos, el primero de ellos considera las diferencias entre las coordenadas XY, desplazándose el promedio. En el segundo, se aplica una transformación Helmert2D. MMS emplea sistemas de navegación global por satélite (Global Navigation Satellite Systems, GNSS) e inerciales (Inertial Measurement Unit, IMU) para georreferenciar la nube de puntos. La precisión de estos sistemas de posicionamiento depende del entorno de adquisición. Por ello, en este estudio se han seleccionado tres áreas con distintas características urbanas (altura de edificios, nivel de urbanización y áreas abiertas) de Abu Dhabi con el fin de analizar su influencia, tanto en la captura, como en la extracción de los elementos. En el caso de farolas, señales viales, árboles y aceras se ha realizado con software comercial, y para registros y edificios con los algoritmos propuestos. Las ratios de corrección y completitud, y la precisión geométrica se han calculado en las diferentes áreas urbanas. Los mejores resultados se han conseguido para las farolas, señales y bordillos, independientemente de la altura de los edificios. La peor ratio se obtuvo para los mismos elementos en áreas peri-urbanas, debido a la vegetación. Resultados opuestos se han conseguido en la detección de árboles. El coste económico y en tiempo de la metodología propuesta resulta inferior al de métodos tradicionales. Lo cual demuestra el gran potencial y eficiencia de la tecnología LiDAR móvil para la actualización cartografía de referenciaPostprint (published version

Space-time analytics of human physiology for urban planning.

Recent advancements in mobile sensing and wearable technologies create new opportunities to improve our understanding of how people experience their environment. This understanding can inform urban design decisions. Currently, an important urban design issue is the adaptation of infrastructure to increasing cycle and e-bike use. Using data collected from 12 cyclists on a cycle highway between two municipalities in The Netherlands, we coupled location and wearable emotion data at a high spatiotemporal resolution to model and examine relationships between cyclists' emotional arousal (operationalized as skin conductance responses) and visual stimuli from the environment (operationalized as extent of visible land cover type). We specifically took a within-participants multilevel modeling approach to determine relationships between different types of viewable land cover area and emotional arousal, while controlling for speed, direction, distance to roads, and directional change. Surprisingly, our model suggests ride segments with views of larger natural, recreational, agricultural, and forested areas were more emotionally arousing for participants. Conversely, segments with views of larger developed areas were less arousing. The presented methodological framework, spatial-emotional analyses, and findings from multilevel modeling provide new opportunities for spatial, data-driven approaches to portable sensing and urban planning research. Furthermore, our findings have implications for design of infrastructure to optimize cycling experiences

Methods for Real-time Visualization and Interaction with Landforms

This thesis presents methods to enrich data modeling and analysis in the geoscience domain with a particular focus on geomorphological applications. First, a short overview of the relevant characteristics of the used remote sensing data and basics of its processing and visualization are provided. Then, two new methods for the visualization of vector-based maps on digital elevation models (DEMs) are presented. The first method uses a texture-based approach that generates a texture from the input maps at runtime taking into account the current viewpoint. In contrast to that, the second method utilizes the stencil buffer to create a mask in image space that is then used to render the map on top of the DEM. A particular challenge in this context is posed by the view-dependent level-of-detail representation of the terrain geometry. After suitable visualization methods for vector-based maps have been investigated, two landform mapping tools for the interactive generation of such maps are presented. The user can carry out the mapping directly on the textured digital elevation model and thus benefit from the 3D visualization of the relief. Additionally, semi-automatic image segmentation techniques are applied in order to reduce the amount of user interaction required and thus make the mapping process more efficient and convenient. The challenge in the adaption of the methods lies in the transfer of the algorithms to the quadtree representation of the data and in the application of out-of-core and hierarchical methods to ensure interactive performance. Although high-resolution remote sensing data are often available today, their effective resolution at steep slopes is rather low due to the oblique acquisition angle. For this reason, remote sensing data are suitable to only a limited extent for visualization as well as landform mapping purposes. To provide an easy way to supply additional imagery, an algorithm for registering uncalibrated photos to a textured digital elevation model is presented. A particular challenge in registering the images is posed by large variations in the photos concerning resolution, lighting conditions, seasonal changes, etc. The registered photos can be used to increase the visual quality of the textured DEM, in particular at steep slopes. To this end, a method is presented that combines several georegistered photos to textures for the DEM. The difficulty in this compositing process is to create a consistent appearance and avoid visible seams between the photos. In addition to that, the photos also provide valuable means to improve landform mapping. To this end, an extension of the landform mapping methods is presented that allows the utilization of the registered photos during mapping. This way, a detailed and exact mapping becomes feasible even at steep slopes