Integration of Terrestrial Laser Scanning and UAS Photogrammetry in Geological Studies: Examples from Croatia

Terrestrial laser scanning (TLS) in combination with Unmanned Aircraft System (UAS) and modern computer based photogrammetry is currently the best approach for the acquisition of high-resolution 3D spatial information. Highly realistic 3D spatial data sets are becoming the basis for detailed geological studies, providing a multidisciplinary approach in the study and research of both underground and above ground sites. To emphasize the variety of possible implementations of these state-of-the-art methodologies, four characteristic and yet quite different case studies are presented where such geodetic techniques are successfully employed. The presented case studies demonstrate that TLS and UAS photogrammetry, as non-contact surveying methods, are able to reduce survey time and total project costs. As added value, they provide high-resolution data that can be analyzed in a virtual environment from a sedimentological or structural aspect. Stored digital documentation also allows future multi-temporal spatial data comparison at any timeframe and scale, thus enhancing any target geological data gathering and analyses at the studied sites

Space, Settlement, and Environment: Detecting Undocumented Maya Archaeological Sites with Remotely Sensed Data

This study utilizes an integrated remote sensing approach to augment settlement pattern research in the Yalahau Region of northern Quintana Roo, Mexico. The region has a long history of human occupation and an environment ranging from coasts, freshwater wetlands, forests, to fields and towns all above a porous karst geology. By utilizing various sensors (LiDAR, GeoEye and Landsat) and collection methods (satellite, aerial) as well as post-processing (band combinations, component analyses and indices) and cross-referencing the data, it is possible to generate a signature, which strongly correlates with evidence of prehistoric occupation. Field verification of a selection of identified signatures was conducted to assess the presence of human cultural material. The results of this investigation are presented together with other regional settlement pattern data in order to assess the status of a number of methodological and archaeological questions and supplement other regional data already available

Accurate, fast, and robust 3D city-scale reconstruction using wide area motion imagery

Multi-view stereopsis (MVS) is a core problem in computer vision, which takes a set of scene views together with known camera poses, then produces a geometric representation of the underlying 3D model Using 3D reconstruction one can determine any object's 3D profile, as well as knowing the 3D coordinate of any point on the profile. The 3D reconstruction of objects is a generally scientific problem and core technology of a wide variety of fields, such as Computer Aided Geometric Design (CAGD), computer graphics, computer animation, computer vision, medical imaging, computational science, virtual reality, digital media, etc. However, though MVS problems have been studied for decades, many challenges still exist in current state-of-the-art algorithms, for example, many algorithms still lack accuracy and completeness when tested on city-scale large datasets, most MVS algorithms available require a large amount of execution time and/or specialized hardware and software, which results in high cost, and etc... This dissertation work tries to address all the challenges we mentioned, and proposed multiple solutions. More specifically, this dissertation work proposed multiple novel MVS algorithms to automatically and accurately reconstruct the underlying 3D scenes. By proposing a novel volumetric voxel-based method, one of our algorithms achieved near real-time runtime speed, which does not require any special hardware or software, and can be deployed onto power-constrained embedded systems. By developing a new camera clustering module and a novel weighted voting-based surface likelihood estimation module, our algorithm is generalized to process di erent datasets, and achieved the best performance in terms of accuracy and completeness when compared with existing algorithms. This dissertation work also performs the very first quantitative evaluation in terms of precision, recall, and F-score using real-world LiDAR groundtruth data. Last but not least, this dissertation work proposes an automatic workflow, which can stitch multiple point cloud models with limited overlapping areas into one larger 3D model for better geographical coverage. All the results presented in this dissertation work have been evaluated in our wide area motion imagery (WAMI) dataset, and improved the state-of-the-art performances by a large margin.The generated results from this dissertation work have been successfully used in many aspects, including: city digitization, improving detection and tracking performances, real time dynamic shadow detection, 3D change detection, visibility map generating, VR environment, and visualization combined with other information, such as building footprint and roads.Includes bibliographical references

VGC 2023 - Unveiling the dynamic Earth with digital methods: 5th Virtual Geoscience Conference: Book of Abstracts

Conference proceedings of the 5th Virtual Geoscience Conference, 21-22 September 2023, held in Dresden. The VGC is a multidisciplinary forum for researchers in geoscience, geomatics and related disciplines to share their latest developments and applications.:Short Courses 9 Workshops Stream 1 10 Workshop Stream 2 11 Workshop Stream 3 12 Session 1 – Point Cloud Processing: Workflows, Geometry & Semantics 14 Session 2 – Visualisation, communication & Teaching 27 Session 3 – Applying Machine Learning in Geosciences 36 Session 4 – Digital Outcrop Characterisation & Analysis 49 Session 5 – Airborne & Remote Mapping 58 Session 6 – Recent Developments in Geomorphic Process and Hazard Monitoring 69 Session 7 – Applications in Hydrology & Ecology 82 Poster Contributions 9

Geometric data understanding : deriving case specific features

There exists a tradition using precise geometric modeling, where uncertainties in data can be considered noise. Another tradition relies on statistical nature of vast quantity of data, where geometric regularity is intrinsic to data and statistical models usually grasp this level only indirectly. This work focuses on point cloud data of natural resources and the silhouette recognition from video input as two real world examples of problems having geometric content which is intangible at the raw data presentation. This content could be discovered and modeled to some degree by such machine learning (ML) approaches like deep learning, but either a direct coverage of geometry in samples or addition of special geometry invariant layer is necessary. Geometric content is central when there is a need for direct observations of spatial variables, or one needs to gain a mapping to a geometrically consistent data representation, where e.g. outliers or noise can be easily discerned. In this thesis we consider transformation of original input data to a geometric feature space in two example problems. The first example is curvature of surfaces, which has met renewed interest since the introduction of ubiquitous point cloud data and the maturation of the discrete differential geometry. Curvature spectra can characterize a spatial sample rather well, and provide useful features for ML purposes. The second example involves projective methods used to video stereo-signal analysis in swimming analytics. The aim is to find meaningful local geometric representations for feature generation, which also facilitate additional analysis based on geometric understanding of the model. The features are associated directly to some geometric quantity, and this makes it easier to express the geometric constraints in a natural way, as shown in the thesis. Also, the visualization and further feature generation is much easier. Third, the approach provides sound baseline methods to more traditional ML approaches, e.g. neural network methods. Fourth, most of the ML methods can utilize the geometric features presented in this work as additional features.Geometriassa käytetään perinteisesti tarkkoja malleja, jolloin datassa esiintyvät epätarkkuudet edustavat melua. Toisessa perinteessä nojataan suuren datamäärän tilastolliseen luonteeseen, jolloin geometrinen säännönmukaisuus on datan sisäsyntyinen ominaisuus, joka hahmotetaan tilastollisilla malleilla ainoastaan epäsuorasti. Tämä työ keskittyy kahteen esimerkkiin: luonnonvaroja kuvaaviin pistepilviin ja videohahmontunnistukseen. Nämä ovat todellisia ongelmia, joissa geometrinen sisältö on tavoittamattomissa raakadatan tasolla. Tämä sisältö voitaisiin jossain määrin löytää ja mallintaa koneoppimisen keinoin, esim. syväoppimisen avulla, mutta joko geometria pitää kattaa suoraan näytteistämällä tai tarvitaan neuronien lisäkerros geometrisia invariansseja varten. Geometrinen sisältö on keskeinen, kun tarvitaan suoraa avaruudellisten suureiden havainnointia, tai kun tarvitaan kuvaus geometrisesti yhtenäiseen dataesitykseen, jossa poikkeavat näytteet tai melu voidaan helposti erottaa. Tässä työssä tarkastellaan datan muuntamista geometriseen piirreavaruuteen kahden esimerkkiohjelman suhteen. Ensimmäinen esimerkki on pintakaarevuus, joka on uudelleen virinneen kiinnostuksen kohde kaikkialle saatavissa olevan datan ja diskreetin geometrian kypsymisen takia. Kaarevuusspektrit voivat luonnehtia avaruudellista kohdetta melko hyvin ja tarjota koneoppimisessa hyödyllisiä piirteitä. Toinen esimerkki koskee projektiivisia menetelmiä käytettäessä stereovideosignaalia uinnin analytiikkaan. Tavoite on löytää merkityksellisiä paikallisen geometrian esityksiä, jotka samalla mahdollistavat muun geometrian ymmärrykseen perustuvan analyysin. Piirteet liittyvät suoraan johonkin geometriseen suureeseen, ja tämä helpottaa luonnollisella tavalla geometristen rajoitteiden käsittelyä, kuten väitöstyössä osoitetaan. Myös visualisointi ja lisäpiirteiden luonti muuttuu helpommaksi. Kolmanneksi, lähestymistapa suo selkeän vertailumenetelmän perinteisemmille koneoppimisen lähestymistavoille, esim. hermoverkkomenetelmille. Neljänneksi, useimmat koneoppimismenetelmät voivat hyödyntää tässä työssä esitettyjä geometrisia piirteitä lisäämällä ne muiden piirteiden joukkoon

Speleogenesis and Delineation of Megaporosity and Karst Geohazards Through Geologic Cave Mapping and LiDAR Analyses Associated with Infrastructure in Culberson County, Texas

The Gypsum Plain region of the Delaware Basin hosts approximately 1800 km2 of the Castile Formation outcrop. A myriad of karstic developments from closed sinkholes to large multi-kilometer cave systems have been documented within the region. Karst studies on the distribution and speleogenetic evolution within Castile strata began within the last decade with ever increasing data resolution. In this study, a combination of both physical field surveys and analyses of high resolution (~30 cm accuracy) LiDAR data was used to create a theoretical model for karst development across the region. This idealized model considers speleogenetic formation type variations (hypogene and epigene), the density of karstic features based on lithology variations, and the connection between the local hydrostratigraphic setting and the regional hydrogeological framework. Field studies included physical mapping of 20 km2 of the Gypsum Plain from the Castile’s western outcrop to where it dips into the subsurface to the east. These surface surveys involved the recording of all surfically-expressed karstic phenomena and the mapping of all enterable caves so that the speleogenetic evolution could be analyzed. The way in which hypogene and epigene caves are surfically expressed across the region indicates that many of the caves have been affected by either multi-stage epigenetic development or multi-stage hypogenetic development with epigenetic overprinting. Through the use of the methods outlined above, surficial karst manifestations vary across the region, from hypogenetic exposures in the west and epigenetic phreatic / vadose exposures in the east. Additionally, supplementary LiDAR data was used to create digital elevation models (DEM) so that the effectiveness of physical field surveys versus remote sensing techniques could be determined. Previous works in the area by Stafford et al., (2008b) determined that remote sensing preserved only 36% of all karstic features found through physical field surveys. Given today’s advancements in remote sensing accuracy, this study determined that on average LiDAR analysis identifies almost seven times more karstic features than physical surveys over a given area

Unmanned Aircraft System Assessments of Landslide Safety for Transportation Corridors

An assessment of unmanned aircraft systems (UAS) concluded that current, off-the-shelf UAS aircraft and cameras can be effective for creating the digital surface models used to evaluate rock-slope stability and landslide risk along transportation corridors. The imagery collected with UAS can be processed using a photogrammetry technique called Structure-from-Motion (SfM) which generates a point cloud and surface model, similar to terrestrial laser scanning (TLS). We treated the TLS data as our control, or “truth,” because it is a mature and well-proven technology. The comparisons of the TLS surfaces and the SFM surfaces were impressive – if not comparable is many cases. Thus, the SfM surface models would be suitable for deriving slope morphology to generate rockfall activity indices (RAI) for landslide assessment provided the slopes. This research also revealed that UAS are a safer alternative to the deployment and operation of TLS operating on a road shoulder because UAS can be launched and recovered from a remote location and capable of imaging without flying directly over the road. However both the UAS and TLS approaches still require traditional survey control and photo targets to accurately geo-reference their respective DSM.List of Figures ...................................................................................................... vi List of Abbreviations ......................................................................................... vii Acknowledgments ................................................................................................ x Executive Summary ............................................................................................. xi CHAPTER 1 INTRODUCTION .......................................................................... 1 CHAPTER 2 LITERATURE REVIEW ................................................................ 4 2.1 Landslide Hazards .................................................................................... 4 2.2 Unmanned Aircraft Systems Remote Sensing.......................................... 6 2.3 Structure From Motion (SfM) .................................................................. 7 2.4 Lidar terrain mapping ............................................................................... 8 CHAPTER 3 STUDY SITE/DATA .................................................................. 11 CHAPTER 4 METHODS ................................................................................ 13 4.1 Data Collection ............................................................................................. 13 4.1.1 Survey Control ..................................................................................... 14 4.1.2 TLS Surveys ........................................................................................ 16 4.1.3 UAS Imagery ....................................................................................... 17 4.1.4 Terrestrial Imagery Acquisition ........................................................... 19 4.2 Data Processing ............................................................................................ 20 4.2.1 Survey Control ..................................................................................... 20 4.2.2 TLS Processing .................................................................................... 20 4.2.3 SfM Processing .................................................................................... 21 4.2.4 Surface Generation .............................................................................. 22 4.3 Quality Evaluation ........................................................................................ 23 4.3.1 Completeness ....................................................................................... 23 4.3.2 Data Density/Resolution ...................................................................... 23 4.3.3 Accuracy Assessment .......................................................................... 23 4.3.2 Surface Morphology Analysis ............................................................. 24 4.2.6 Data Visualization ............................................................................... 25 CHAPTER 5 RESULTS ................................................................................. 27 v 5.1 UTIC DSM evaluation.................................................................................. 27 5.1.1 Completeness evaluation ..................................................................... 28 5.1.2 Data Density Evaluation ...................................................................... 29 5.1.3 Accuracy Evaluation............................................................................ 30 5.2 Geomorphological Evaluation ...................................................................... 32 CHAPTER 6 DISCUSSION ............................................................................ 35 6.1 Evaluation of UAS efficiencies .................................................................... 35 6.2 DSM quality and completeness .................................................................... 37 6.3 Safety and operational considerations .......................................................... 37 CHAPTER 7 CONCLUSIONS AND RECOMMENDATIONS ................................ 40 7.1 Technology Transfer..................................................................................... 41 7.1.1 Publications ......................................................................................... 41 7.1.2 Presentations ........................................................................................ 42 7.1.3 Multi-media outreach .......................................................................... 43 6.4 Integration of UAS and TLS data ................................................................. 44 REFERENCES .............................................................................................. 4

Navigating virtual heritage applications for historic cities in the Middle East

This paper discusses conceptual and practical framework for the development of virtual heritage platforms as a research, educational and engagement tool that brings historic spaces and buildings back to the recognition of the public eye of the ordinary user. It not only reproduces historical scenes through physical modelling of archaeological sites or data, but, more importantly, through serial narratives where life is explored and practiced in motion, and where cultural-feed brings meaning, experiences and understanding to the socio-cultural context. The paper first introduces a brief and summary database of case studies of examples of virtual heritage platforms and outputs that are suitable to different purposes and audiences. It, then, looks at the context and production of VH in Egypt, as an example of Middle Eastern cities with vast heritage sites and advanced technological provisions. It reports on the process and findings of an AHRC-funded project, Virtual Heritage Cairo, that aimed to investigate difficulties, technological and skill gaps amongst stakeholders and local start-ups that would otherwise enable VH in Egypt to become regional power

Feasibility studies of terrestrial laser scanning in Coastal Geomorphology, Agronomy, and Geoarchaeology

Terrestrial laser scanning (TLS) is a newer, active method of remote sensing for the automatic detection of 3D coordinate points. This method has been developed particularly during the last 20 years, in addition to airborne and mobile laser scanning methods. All these methods use laser light and additional angle measurements for the detection of distances and directions. Thus, several thousands to hundreds of thousands of polar coordinates per second can be measured directly by an automatic deflection of laser beams. For TLS measurements, the coordinates and orientation of the origin of the laser beam can be determined to register different scan positions in a common coordinate system. These measurements are usually conducted by Global Navigation Satellite Systems or total station surveying, but also identical points can be used and data driven methods are possible. Typically, accuracies and point densities of a few centimetres to a few millimetres are achieved depending on the method. The derived 3D point clouds contain millions of points, which can be evaluated in post-processing stages by symbolic or data-driven methods. Besides the creation of digital surface and terrain models, laser scanning is used in many areas for the determination of 3D objects, distances, dimensions, and volumes. In addition, changes can be determined by multi-temporal surveys. The terrestrial laser scanner Riegl LMS Z-420i was used in this work in combination with the Differential Global Positioning System system Topcon Hiper Pro, based on Real Time Kinematic (RTK-DGPS). In addition to the direct position determination of the laser scanner, the position of a self-developed reflector on a ranging pole was measured by the RTK-DGPS system to accurately derive the orientation of each measured point cloud. Moreover, the scanner is equipped with an additional, mounted camera Nikon D200 to capture oriented pictures. These pictures allow colouring the point cloud in true colours and thus allow a better orientation. Furthermore, the pictures can be used for the extraction of detailed 3D information and for texturing the 3D objects. In one of the post-processing steps, the direct georeferencing by RTK-DGPS data was refined using the Multi Station Adjustment, which employs the Iterative Closest Point algorithm. According to the specific objectives, the point clouds were then filtered, clipped, and processed to establish 3D objects for further usage. In this dissertation, the feasibility of the method has been analysed by investigating the applicability of the system, the accuracy, and the post-processing methods by means of case studies from the research areas of coastal geomorphology, agronomy, and geoarchaeology. In general, the measurement system has been proven to be robust and suitable for field surveys in all cases. The surveys themselves, including the selected georeferencing approach, were conducted quickly and reliably. With the refinement of the Multi Station Adjustment a relative accuracy of about 1 cm has been achieved. The absolute accuracy is about 1.5 m, limited by the RTK-DGPS system, which can be enhanced through advanced techniques. Specific post-processing steps have been conducted to solve the specific goals of each research area. The method was applied for coastal geomorphological research in western Greece. This part of the study deals with 3D reconstructed volumes and corresponding masses of boulders, which have been dislocated by high energy events. The boulder masses and other parameters, such as the height and distance to the current sea level, have been used in wave transport equations for the calculation of minimum wave heights and velocities of storm and tsunami scenarios and were compared to each other. A significant increase in accuracy of 30% on average compared with the conventional method of simply measuring the axes was detected. For comparison, annual measurements at seven locations in western Greece were performed over three years (2009-2011) and changes in the sediment budget were successfully detected. The base points of the RTK-DGPS system were marked and used every year. Difficulties arose in areas with high surface roughness and slight changes in the annual position of the laser scanner led to an uneven point density and generated non-existing changes. For this reason, all results were additionally checked by pictures of the mounted camera and a direct point cloud comparison. Similarly, agricultural plants were surveyed by a multi-temporal approach on a field over two years using the stated method. Plant heights and their variability within a field were successfully determined using Crop Surface Models, which represent the top canopy. The spatial variability of plant development was compared with topographic parameters as well as soil properties and significant correlations were found. Furthermore, the method was carried out with four different types of sugar-beet at a higher resolution, which was achieved by increasing the height of the measurement position. The differences between the crop varieties and their growth behaviour under drought stress were represented by the derived plant heights and a relation to biomass and the Leaf Area Index was successfully established. With regard to geoarchaeological investigations in Jordan, Spain, and Egypt, the method was used in order to document respective sites and specific issues, such as proportions and volumes derived from the generated 3D models were solved. However, a full coverage of complexly structured sites, like caves or early settlements is partially prevented by the oversized scanner, slow measurement rates, and the necessary minimum measurement distance. The 3D data can be combined with other data for further research by the common georeference. The selected method has been found suitable to create accurate 3D point clouds and corresponding 3D models that can be used in accordance with the respective research problem. The feasibility of the TLS method for various issues of the case studies was proven, but limitations of the used system have also been detected and are described in the respective chapters. Further methods or other, newer TLS systems may be better suited for specific cases

Reliving past architecture: virtual heritage and the reproduction of history through creative modes of heritage visualisation

Virtual heritage is a modern technological application that aims to transfer the experience of historic buildings, urban spaces and cities into an engaging experience of real-life quality for the ordinary people. Computer-simulated environments can simulate physical presence in places in the real world offering digital display of lost heritage that conveys inherent values in the education process for students in both pre-university as well as graduate education. For architecture and archaeological students, in particular, it virtually transfers them to another world where they engage with architectonics and quality of architecture. For conservators, historians and archaeologists, it helps develop a rich library and digital archive of details, information and data necessary in restoring historical sites, as well as heritage preservation where the 3D virtual models contain accurate data and help for restoration. This paper reports on recently completed research project on the development of virtual heritage platforms for medieval culture. It uncovers a conceptual framework for the development of virtual heritage platforms as a research, educational and engagement tool that brings historic spaces and buildings back to the recognition of the public eye of the ordinary user. It not only reproduces historical scenes through physical modelling of archaeological sites or data, but, more importantly, through serial narratives where life is explored and practised in motion, and where cultural-feed brings meaning, experiences and understanding to the socio-cultural context. The paper introduces a brief analysis of virtual heritage platforms that offer a variety of methods, techniques, contexts, and outputs that are suitable to different purposes and audiences. It offers a brief conclusion on how virtual heritage offer unique and unprecedented insights into historic architecture that would be otherwise invisible or unimaginable