Danilo Schneider

Terrestrial lidar and hyperspectral data fusion products for geological outcrop analysis

Close-range hyperspectral imaging is an emerging technique for remotely mapping mineral content and distributions in inaccessible geological outcrop surfaces, allowing subtle chemical variations to be identified with high resolution and accuracy. Terrestrial laser scanning (lidar) is an established method for rapidly obtaining three-dimensional geometry, with unparalleled point density and precision. The combination of these highly complementary data types - 3D topography and surface properties - enables the production of value-added photorealistic outcrop models, adding new information that can be used for solving geological problems. This paper assesses the benefits of merging lidar and hyperspectral imaging, and presents qualitative and quantitative means of analysing the fused datasets. The integration requires an accurate co-registration, so that the 2D hyperspectral classification products can be given real measurement units. This stage is reliant on using a model that correctly describes the imaging geometry of the hyperspectral instrument, allowing image pixels and 3D points in the lidar model to be related. Increased quantitative analysis is then possible, as areas and spatial relationships can be examined by projecting classified material boundaries into 3D space. The combined data can be interpreted in a very visual manner, by colouring and texturing the lidar geometry with hyperspectral mineral maps. Because hyperspectral processing often results in several image products and classifications, these can be difficult to analyse simultaneously. A novel visualisation method is presented, where photorealistic lidar models are superimposed with multiple texture-mapped layers, allowing blending between conventional and hyperspectral imaging products to assist with interpretation and validation. The advantages and potential of the data fusion are illustrated with example outcrop data.

Distortion correction of all-reflective unobscured optical-power zoom objective

We present the correction of distortion for a novel type of an all-reflective zoom objective. The all-reflective unobscured optical-power zoom (OPZ) objective with four mirrors has been previously designed and presented. The magnification of the OPZ can be varied by changing the curvatures of the first and the last mirror, which results in a zoom factor of 3. However, the objective exhibits significant distortion. For the unobscured design principle, we present the basic distortion model with its different types of distortion. Based on simulation data of the objective design, we optimized the parameters of the model and verified that model by applying it to images taken with the objective.

Integration of photogrammetry and acoustic emission analysis for assessing concrete structures during loading tests

This paper focuses on space- and time-resolved crack detection in concrete structures by combining photogrammetric techniques with acoustic emission analysis. For the photogrammetric measurements, the surface of reinforced concrete members is textured with a random pattern. A consumer-grade digital camera is used to observe the region of interest during the loading tests. In a sequence of images, cracks are visualized by detecting discrepancies in local displacement vector fields, which are obtained from matching algorithms applied to consecutive images. Critical areas of concrete samples are additionally equipped with several acoustic emission sensors to monitor the crack formation and propagation by acoustic emission analysis. The parameter-based method is used to record specific parameters in real time and enables the distinction between bending or shear cracks depending on the signal energy and duration. During the loading tests, information about the crack prolongation is used to derive the time of transition from stable to unstable phase. The acoustically detected shear cracks are monitored in the images to track growth and to stop the experiment before a critical bearing status is reached. Thus, shear cracks can be localized temporally and locally on the surface and inside the structure. In a next step, the detected cracks have to be checked for certain properties providing information about the condition of the structure. Indicators with high level significance referring to structures with no or low advance notice of failure constitute a focal point of further research.

Close range hyperspectral and lidar data integration for geological outcrop analysis

The use of spatial data collection techniques in geology has increased significantly in recent years, with methods such as laser scanning (lidar) becoming popular. However, the remote mapping of rock properties within the geological outcrops remains a major challenge. This study develops a workflow for combining and utilising ground based hyperspectral and laser scanning data. This workflow is presented for two case studies, each with different geological settings and mineral composition. Multiple hyperspectral and lidar scans were acquired to gain both spectral and geometric data. Mixture Tuned Matched Filtering was utilised to extract and map geological features from the spectral images, resulting in thematic images. This combination of geometrically accurate lidar data and spectral mapping of lithology has significant implications for the improved collection of geological data.