#Digital terrain model transection software#

#Digital terrain model transection software#

This has been driven by the ubiquity of digital cameras and major increases in automation arising from scientific outputs from the computer vision discipline (e.g., interest operators, feature point matching, and dense point cloud extraction Granshaw and Fraser, 2015), which have been implemented in easy-to-use software packages. The reinvention of photogrammetry-a technique that has advanced in line with photographic innovations-has recently intensified the adoption of three-dimensional (3-D) spatial data by geoscientists. , and Squelch as a small subset of papers providing snapshots of developments through time). This is exemplified by rapid adoption across the many arms of the geoscience subdisciplines (see, e.g., McCaffrey et al. The evolving state of the art can be followed through the scientific literature, from early adoption to the status quo. Computing hardware has developed to facilitate field-based acquisition ( Weng et al., 2012 Kehl et al., 2017), and more analysis tools are available in geographical information systems (GIS). Laser scanning (lidar), global navigation satellite systems (GNSS), digital photogrammetry (also referred to as structure from motion ), and imaging remote sensing have all evolved heavily over the last two decades, and are distinguished by unprecedented resolution, precision, and ease of use. The use of digital spatial data is becoming commonplace in many areas of the geosciences (for example in geology, geomorphology, cryospheric science, volcanology, natural hazards, hydrology, energy, infrastructure, and mining). The motivation and an overview of the software are described, illustrated by example usage scenarios from outcrop geology, multi-sensor data fusion, and geophysical-geospatial data integration. High-quality visual output can be generated for dissemination to aid researchers with communication of their results. In addition, it features novel data integration and visualization of 3-D topography with image sources such as logs and interpretation panels, supplementary wavelength imagery, geophysical data sets, and georeferenced maps and images. The software allows measurement and interpretation via digitizing in the 3-D scene.

This contribution presents LIME, a lightweight and high-performance 3-D software for interpreting and co-visualizing 3-D models and related image data. Interpretation and measurement is essential for quantitative analysis of 3-D data sets, and qualitative methods are valuable for presentation purposes, for planning, and in education. In addition, fusion of surface geometry with imaging sensors, such as multispectral, hyperspectral, thermal, and ground-based radar, and geophysical methods creates complex and visual data sets that provide a fundamental spatial framework to address open geoscience research questions.Дespite the current ease of acquiring and processing 3-D photo-textured models, the accessibility of tools for analyzing and presenting data remains problematic, characterized by steep learning curves and custom solutions for individual geoscience applications.

This rapid adoption is driven by recent innovations in acquisition hardware, software automation, and sensor platforms, including unmanned aerial vehicles. The use of three-dimensional (3-D), photo-textured representations of topography from laser scanning and photogrammetry is becoming increasingly common across the geosciences.