Ground Profile Recovery from Aerial 3D LiDAR-based Maps

The paper presents the study and implementation of the ground detection methodology with filtration and removal of forest points from LiDAR-based 3D point cloud using the Cloth Simulation Filtering (CSF) algorithm. The methodology allows to recover a terrestrial relief and create a landscape map of a forestry region. As the proof-of-concept, we provided the outdoor flight experiment, launching a hexacopter under a mixed forestry region with sharp ground changes nearby Innopolis city (Russia), which demonstrated the encouraging results for both ground detection and methodology robustness.Comment: 8 pages, FRUCT-2019 conferenc

The use of terrestrial laser scanning for measurements in shallow-water : correction of the 3D coordinates of the point cloud

Although acoustic measurements are a wide-spread technique in the field of bathymetry, most systems require a water depth of at least 2 m. Furthermore, mapping shallow-water depths with acoustic techniques is expensive and complicated. Over the last decades, the use of laser scanning for mapping riverbeds has increased. However, the level of accuracy and the point density which can be obtained by Airborne Laser Scanning (ALS), and Airborne Laser Bathymetry (ALB) in particular, are not as high as those of terrain measurements originating from ALS. Moreover, ALS and ALB are not yet suited for mapping shallow-water beds. Therefore, more recent research focuses on the use of Terrestrial Laser Scanning (TLS) from either a fixed or static position (STLS) or from a mobile platform (MTLS). An obvious advantage of using STLS and MTLS is that both the river beds and the river banks can be modelled by means of the same data acquisition system. This ensures a seamless integration of data sets describing both dry and wet surfaces, and thus of topography and bathymetry. However, although STLS and MTLS have the potential to produce high resolution point clouds of shallow-water riverbeds and - banks, the resulting point clouds have to be corrected for the systematic errors in depth and distance that are caused by the refraction of the laser beam at its transition through the boundary of air and water. In this research a procedure was implemented to adjust the coordinates of every point situated beneath the water surface, based on the refractive index. The refractive index depends on the wavelength of the laser beam and the properties of the media the beam travels through. The refractive index for a laser beam with a wavelength of 532 nm varies by less than 1% for a wide range of temperature and salinity conditions. Nevertheless, during the case studies, it became clear that it is important to use an estimate of the refractive index which approaches the actual value as closely as possible in order to obtain accuracies of less than 1 to 2 cm. Therefore, the refractive index was determined for each specific case by using water samples

Integration of points cloud data from airborne and terrestrial laser scanner

The purpose of this study is trying to solve the shortage of the data due to the limitations of the laser scanner instrument in data collection. The data integration between ALS with TLS are able to provide complete data for used by other applications such as 3D model of building, 3D model of forestry mapping, documentation of historical building, forensic and many more. The scope of this study focusing on the scanning the UTM Eco-Home building using ALS and TLS. The UTM Eco-Home building was chosen because it has a unique design and structure that can be test the capabilities of the laser scanner instruments. The ALS used to scan the roof top of the building and the TLS used to scan the façade of the building. The laser scanner instruments are used in data collection are to ensure that is no part of the building are missed to scan. After completing scanning the UTM Eco-Home building process, the dataset used for integration through registration method using man-made. The man-made is chosen because the characteristic of man-made can be seen in both dataset. The level of accuracy is assessed by comparison method with the conventional measurement using total station. The result from the integration is using for many purposes for example 3D city modelling, 3D forestry mapping, 3D topographic mapping, historical documentation and others

Automated Structural-level Alignment of Multi-view TLS and ALS Point Clouds in Forestry

Access to highly detailed models of heterogeneous forests from the near surface to above the tree canopy at varying scales is of increasing demand as it enables more advanced computational tools for analysis, planning, and ecosystem management. LiDAR sensors available through different scanning platforms including terrestrial, mobile and aerial have become established as one of the primary technologies for forest mapping due to their inherited capability to collect direct, precise and rapid 3D information of a scene. However, their scalability to large forest areas is highly dependent upon use of effective and efficient methods of co-registration of multiple scan sources. Surprisingly, work in forestry in GPS denied areas has mostly resorted to methods of co-registration that use reference based targets (e.g., reflective, marked trees), a process far from scalable in practice. In this work, we propose an effective, targetless and fully automatic method based on an incremental co-registration strategy matching and grouping points according to levels of structural complexity. Empirical evidence shows the method's effectiveness in aligning both TLS-to-TLS and TLS-to-ALS scans under a variety of ecosystem conditions including pre/post fire treatment effects, of interest to forest inventory surveyors

Assessment of handheld mobile terrestrial laser scanning for estimating tree parameters

Sustainable forest management heavily relies on the accurate estimation of tree parameters. Among others, the diameter at breast height (DBH) is important for extracting the volume and mass of an individual tree. For systematically estimating the volume of entire plots, airborne laser scanning (ALS) data are used. The estimation model is frequently calibrated using manual DBH measurements or static terrestrial laser scans (STLS) of sample plots. Although reliable, this method is time-consuming, which greatly hampers its use. Here, a handheld mobile terrestrial laser scanning (HMTLS) was demonstrated to be a useful alternative technique to precisely and efficiently calculate DBH. Different data acquisition techniques were applied at a sample plot, then the resulting parameters were comparatively analysed. The calculated DBH values were comparable to the manual measurements for HMTLS, STLS, and ALS data sets. Given the comparability of the extracted parameters, with a reduced point density of HTMLS compared to STLS data, and the reasonable increase of performance, with a reduction of acquisition time with a factor of 5 compared to conventional STLS techniques and a factor of 3 compared to manual measurements, HMTLS is considered a useful alternative technique