With recent advancements in unmanned aircraft system (UAS) technology, along with the miniaturization of airborne laser scanning systems, capabilities of unmanned laser scanning (ULS) systems have increased. Traditional terrestrial laser scanning surveys provide high density point clouds (hundreds - thousands of pts/m2) of a focus area, but have limited field-of-view and line-of-sight due to the constrained static nature of the system. While airborne and mobile laser scanning platforms relieve many of these limitations, lower point density (airborne), confined operation pathways (mobile), and higher operational costs become a factor. Here we present results from ULS data acquired over the Hilo Deep Draft Harbor Breakwater in Hawaii in June 2018. Inspecting the breakwater for failures and instabilities is of vital importance for Hilo. At three kilometers length and exposure to open ocean, a terrestrial laser scanning survey of the breakwater is not possible. Airborne and mobile laser scanning are not ideal due to reduced point densities and site access, respectively. In June 2018, using a RIEGL RiCOPTER with VUX laser system, the authors collected highresolution data over the above water breakwater extents. For below water surfaces, a Riegl BDF-1 bathymetric depth finder was operated from the same UAS, used to generate profiles of subaqueous surfaces of the breakwater. These bathymetric transects supplement the detailed topographic data collected above water on the breakwater. We discuss the operational concerns in both project planning and acquisition phases, as well as detailed analysis of the resulting data, used for a rigorous structure inspection program.
Recent advances in remote sensing technology have expanded the acquisition and fusion of active lidar and passive hyperspectral imagery (HSI) from exclusively airborne observations to include terrestrial modalities. In contrast to airborne collection geometry, hyperspectral imagery captured from terrestrial cameras is prone to extensive solar shadowing on vertical surfaces leading to reductions in pixel classification accuracies or outright removal of shadowed areas from subsequent analysis tasks. We demonstrate the use of lidar spatial information for sub-pixel HSI shadow detection and the restoration of shadowed pixel spectra via empirical methods that utilize sunlit and shadowed pixels of similar material composition. We examine the effectiveness of radiometrically calibrated lidar intensity in identifying these similar materials in sun and shade conditions and further evaluate a restoration technique that leverages ratios derived from the overlapping lidar laser and HSI wavelengths. Simulations of multiple lidar wavelengths, i.e., multispectral lidar, indicate the potential for HSI spectral restoration that is independent of the complexity and costs associated with rigorous radiometric transfer models, which have yet to be developed for horizontal-viewing terrestrial HSI sensors. The spectral restoration performance of shadowed HSI pixels is quantified for imagery of a geologic outcrop through improvements in spectral shape, spectral scale, and HSI band correlation.
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