A New Method for UAV Lidar Precision Testing Used for the Evaluation of an Affordable DJI ZENMUSE L1 Scanner

Evaluating the effectiveness of Mangrove rehabilitation: A novel approach for sustainable coastal management

We used UAV-LiDAR technology and other advanced remote sensing techniques to evaluate mangrove rehabilitation projects along the eroding shoreline of the Upper Gulf of Thailand. Our results delineate the necessary biophysical conditions for successfully rehabilitating mangroves, establishing optimal conditions under which mangroves can naturally re-establish and thrive. Furthermore, we investigated the effectiveness of different coastal defense structures in fostering mangrove recolonization. Our analysis shows that nearshore breakwaters markedly outperform submerged breakwaters and bamboo fences, with a success rate of over 65% by significantly reducing wave energy that aids sediment trapping. These findings suggest that refinements in the configuration of coastal structures, including the elevation of breakwater crests and selective deployment of bamboo fences, will enhance mangrove rehabilitation success. These insights affirm the role of UAV-LiDAR surveys for optimizing mangrove restoration initiatives, thereby facilitating sustainable development for coastlines plagued by erosion. The insights gleaned offer a blueprint for bolstering the success rate of mangrove rehabilitation projects, directing them toward sustainable coastal development.

Morphodynamics of a composite sand-cobble beach in response to extratropical cyclone Fiona and seasonal wave variability

Climate change is driving higher coastal water levels, and models project accelerated future sea-level rise and coastal storm intensification. These dynamics paired with anthropogenic coastal alterations will drive drastic coastal change worldwide. Composite beaches with mixed sediment sizes warrant detailed study as these exhibit complex morphodynamics in response to changing hydrodynamics due to the distinct transport thresholds of different sediment types. This study uses a novel multi-method approach to investigate a composite sand-cobble beach in Atlantic Canada experiencing a shortening seasonal sand-covered period. Hydrodynamic forcing and associated beach changes were monitored over a focused eight-month period, while satellite-based visual imagery and reconstructed wave data were analyzed over longer periods. Results show that intra-annual wave energy changes drive sand dynamics, with reduced summer wave energy facilitating short-term deposition. Long-term positive trends were identified in late spring wave heights, which likely contribute to the shortening sand-covered period. Seasonal dynamics were overwhelmed by extratropical cyclone Fiona, which made landfall on September 24, 2022, generating significant wave heights up to 6.8 m in the bay, mobilizing sediment, and steepening cobble berms. A new index approach based on visual imagery facilitated the investigation of beach sand appearance/disappearance using the relative redness of sand compared to cobble. Finally, the UAV-based surveys yielded high-resolution orthomosaics and LiDAR-based elevation mapping, and highlighted pronounced longshore variability in erosion and deposition during Fiona. The beach mostly recovered to pre-storm conditions in <4 months, which indicates that proposed beach nourishment activities may only experience temporary success. The longer-term results showing a conversion of sand to cobble suggest that loss of sandy beach habitat is likely to increase, even without shoreline migration or coastal squeeze driven by sea-level rise.

Study of the Precise Determination of Pipeline Geometries Using UAV Scanning Compared to Terrestrial Scanning, Aerial Scanning and UAV Photogrammetry

Transmission pipelines belong to technical infrastructure, the condition of which is subject to periodic monitoring. The research was to verify whether aerial measurement methods, especially UAV laser scanning, could determine the geometric shape of pipelines with a precision similar to that of terrestrial scanning, adopted as a reference method. The test object was a section of a district heating pipeline with two types of surfaces: matte and glossy. The pipeline was measured using four methods: terrestrial scanning, airborne scanning, UAV scanning and the structure from motion method. Then, based on the reference terrestrial scanning data, pipeline models were created, with which all methods were compared. The comparison made it possible to find that only the UAV scanning yielded results consistent with those of the terrestrial scanning for all the pipes. The differences usually did not exceed 10 mm, sometimes reaching 20 mm. The structure from motion method yielded unstable results. For the old, matte pipes, the results were similar to those of the UAV scan; however, for the new, shiny pipes, the differences were up to 60 mm.

The Effectiveness of a UAV-Based LiDAR Survey to Develop Digital Terrain Models and Topographic Texture Analyses

This study presents a comparison of data acquired from three LiDAR sensors from different manufacturers, i.e., Yellow Scan Mapper (YSM), AlphaAir 450 Airborne LiDAR System CHC Navigation (CHC) and DJI Zenmuse L1 (L1). The same area was surveyed with laser sensors mounted on the DIJ Matrice 300 RTK UAV platform. In order to compare the data, a diverse test area located in the north-western part of the Lublin Province in eastern Poland was selected. The test area was a gully system with high vegetation cover. In order to compare the UAV information, LiDAR reference data were used, which were collected within the ISOK project (acquired for the whole area of Poland). In order to examine the differentiation of the acquired data, both classified point clouds and DTM products calculated on the basis of point clouds acquired from individual sensors were compared. The analyses showed that the largest average height differences between terrain models calculated from point clouds were recorded between the CHC sensor and the base data, exceeding 2.5 m. The smallest differences were recorded between the L1 sensor and ISOK data-RMSE was 0.31 m. The use of UAVs to acquire very high resolution data can only be used locally and must be subject to very stringent landing site preparation procedures, as well as data processing in DTM and its derivatives.

Surface Monitoring of an MSW Landfill Based on Linear and Angular Measurements, TLS, and LIDAR UAV

Surface monitoring of landfills is crucial not only during their operation but also for later land restoration and development. Measurements concern environmental factors, such as leachate, migration of pollutants to water, biogas, and atmospheric emissions, and geotechnical factors, such as stability and subsidence. Landfill subsidence can be measured using modern surveying techniques. Modern measurement methods for landfill body displacement monitoring and their control after restoration and adaptation as recreational areas include terrestrial laser scanning (TLS), and scanning and low-altitude photogrammetric measurements from an unmanned aerial vehicle (UAV). The acquired measurement data in the form of 3D point clouds should be referenced to the local control network to enable a comprehensive analysis of data acquired using various techniques, including geotechnical sensors such as benchmarks, piezometers, and inclinometers. This study discusses the need for surface monitoring of municipal solid waste (MSW) landfills. A properly 3-D mapped landfill mass is the basis for ensuring the geotechnical safety of the restored landfill. Based on archival data and current measurements of the Radiowo landfill (Poland), this study compares the advantages and limitations of the following measurement techniques: linear and angular measurements, satellite measurements, TLS, and UAV scanning and photogrammetry, considering specific conditions of the location and vegetation of the landfill. Solutions for long-term monitoring were proposed, considering the cost and time resolution necessary for creating a differential model of landfill geometry changes.

The Influence of the Quality of Digital Elevation Data on the Modelling of Terrain Vehicle Movement

This study investigated digital terrain models and options for their evaluation and effective usage. The most important result of this study was the introduction of the slope reduction method for low-detail elevation models. It enabled accurate results of passability analyses by performing adjustments of slopes. In addition, the goal was to determine the strengths and weaknesses of selected data for use in cross-country mobility analyses, followed by recommendations on how to use these databases efficiently to obtain accurate results. The selection of elevation databases (1 m, 5 m, 10 m, 30 m) was determined by the focus of data development projects of NATO and current scientific research projects of the Ministry of Defence of the Czech Republic. Key findings showed potential for use in practise for all tested elevation models. Efficient usage of low-detail models in CCM analyses is limited; nevertheless, they can be augmented with additional vector data or automated remote-sensing technologies.

Determination of Forest Structure from Remote Sensing Data for Modeling the Navigation of Rescue Vehicles

One of the primary purposes of forest fire research is to predict crisis situations and, also, to optimize rescue operations during forest fires. The research results presented in this paper provide a model of Cross-Country Mobility (CCM) of fire brigades in forest areas before or during a fire. In order to develop a methodology of rescue vehicle mobility in a wooded area, the structure of a forest must first be determined. We used a Digital Surface Model (DSM) and Digital Elevation Model (DEM) to determine the Canopy Height Model (CHM). DSM and DEM data were scanned by LiDAR. CHM data and field measurements were used for determining the approximate forest structure (tree height, stem diameters, and stem spacing between trees). Due to updating the CHM and determining the above-mentioned forest structure parameters, tree growth equations and vegetation growth curves were used. The approximate forest structure with calculated tree density (stem spacing) was used for modeling vehicle maneuvers between the trees. Stem diameter data were used in cases where it was easier for the vehicle to override the trees rather than maneuver between them. Although the results of this research are dependent on the density and quality of the input LiDAR data, the designed methodology can be used for modeling the optimal paths of rescue vehicles across a wooded area during forest fires.