Terrestrial Laser Scanning Measurements Research Articles

Estimating merchantable and non-merchantable wood volume in slash walls using terrestrial and airborne LiDAR

Slash walls are an effective forest management practice to prevent deer herbivory and promote forest regeneration following a timber harvest. However, the material cost, i.e. amount of wood material, needed for quality slash walls is unknown or at best based on highly uncertain empirical estimation. Quantifying how total and merchantable timber wood volume varies with width and height across slash walls will facilitate future planning and application of slash walls. In this study, we estimated wood volume per unit length (∼30.48 m) from total stem cross-sectional area in 40 randomly selected cut-through passages cut into 14 slash walls located at Cornell University’s Arnot Teaching and Research Forest (ATRF) in south-central New York. Within each passage we used Terrestrial Laser Scanning (TLS) to identify individual stems and obtain cross-sectional surface area. We found that TLS derived stem diameters were highly consistent with manual stem diameter measurements for 10 selected wall passages (N = 308, R2 = 0.933, RMSE = 1.881 cm). However, TLS tends to underestimate total cross-sectional area due to omission of small stem cross-sections (diameter < 5.08 cm). Cross-sections of small stems often have a low number of total points even when point density is high, especially when they are not facing the scanner. They are also more vulnerable to occlusion (i.e., lack of points due to blocking by other stems). TLS-based wood volume estimates were similar across both short and tall slash walls in the study with an average volume of 21.34 m3/30 m for short slash walls and 21.50 m3/30 m for tall slash walls, corresponding to 16.9 t dry biomass /30 m and 17.0 t dry biomass /30 m respectively. The small difference in woody volume was due to tall slash walls achieving additional height mainly through non-compacted small diameter crown and brush tops that have little woody volume. Average merchantable (diameter > 15.24 cm) and non-merchantable (diameter < 15.24 cm) timber fraction was 68.75 % and 31.35 % for short slash walls and 65.04 % and 34.96 % for tall slash walls. We further assessed slash wall height and width using Airborne Laser Scanning (ALS) for eight other tall slash walls. We found TLS measurements are representative of whole slash wall height and width variability based on ALS measurements. Our results provide novel data and methodology to estimate the construction cost of slash walls which are critical for optimizing slash wall applications.

Integration of Terrestrial Laser Scanning and field measurements data for tree stem volume estimation: Exploring parametric and non-parametric modeling approaches

Integration of Terrestrial Laser Scanning and field measurements data for tree stem volume estimation: Exploring parametric and non-parametric modeling approaches

Vector-autoregressive based vibration monitoring of wind energy turbines using laser scanner profile measurements

Structural health monitoring of wind energy turbines (WET) is crucial due to the potential presence of an imbalanced rotor, leading to adverse centrifugal forces. In this research, non-contact vibration monitoring of a WET is conducted using a terrestrial laser scanner (TLS) of the type Zoller+Fröhlich IMAGER 5016 in a two-dimensional (2D) profile mode, and with a rotation speed of 55 revolutions per second. The TLS profile measurements cover the entire pillar up to a height of 100 meter. Therefore, the challenges imposed by conventional measurement systems, such as accelerometers or inductive displacement transducers, are tackled through the high spatial resolution of the TLS measurements and non-contact measurement methods. Additionally, both time and cost are reduced regarding the sensor installation. In general, the WET is measured in two different directions to account for significant movements, both in the direction of the wind and perpendicular to it. To initiate the analysis, time series are generated from the profile measurements for various positions covering the entire pillar. A robust time-domain modal parameter identification approach based on the Vector-autoregressive (VAR) process with multivariate t-distributed random deviations (VAR-RT-MPI) is proposed to estimate modal parameters, including eigenfrequencies, eigenforms, and modal damping. Besides, it allows estimating unknown auto- and cross-correlation coefficients of the VAR process, the cofactor matrix, and the degrees of freedom of the t-distribution. The VAR-RT-MPI algorithm enables to jointly estimate the eigenfrequencies and damping ratio coefficients considering multiple time series. Additionally, the spatio-temporal model of the pillar is characterised based on the estimates of the amplitudes (in a submillimetre range) and phase shifts at different positions. Vibration monitoring was conducted on a WET located in Hannover, Germany, and the results were compared with a well-known covariance driven stochastic subspace identification (SSI-COV) approach.

Accuracy comparison of terrestrial and airborne laser scanning and manual measurements for stem curve-based growth measurements of individual trees

Monitoring forest growth accurately is important for assessing and controlling forest carbon stocks that impact, for example, the atmospheric CO2 concentration and, consequently, the climate change. In prior studies, forest growth monitoring with laser scanning methods has resulted in relatively high errors. However, the contribution of reference measurement error to uncertainty in growth resolution has rarely been analysed, and the reference measurements are usually considered mostly flawless. In this study, a seven-year-long growth of individual trees was estimated using both airborne and terrestrial laser scanning (ALS, TLS) that have emerged as potential candidates for digital forest reference measurements. The growth values were derived for diameter at breast height (DBH) and stem volume between the years 2014 and 2021 using an indirect approach. The values obtained with laser scanning were paired with manual field measurements and also with each other to study pairwise errors. The pairwise comparison showed that even though all the three measurement methods produced good Pearson correlation coefficients for one-time measurements (all above 0.88), the coefficients for growth measurements were significantly lower (0.19–0.44 for DBH and 0.47–0.66 for stem volume). The best correlation and root mean squared deviation (RMSD) for DBH growth (ρ = 0.44, RMSD = 0.98 cm) and stem volume growth (ρ = 0.66, RMSD = 0.052 m3) was observed between the manual field measurements and the ALS-based growth measurement method, in which the tree stem curve was obtained from the 2021 point cloud, and the stem curve was predicted backwards for the year 2014 according to height growth. The ALS method suffered less from outlying values than the TLS-based growth measurement method, in which the growth was computed based on the difference of stem curves derived separately for the years 2014 and 2021. The study showed that observing the stem curve is a potential method for short-period growth monitoring. Using the pairwise comparison results, we further derived estimates for the mean and standard deviation of measurement error of each individual measurement method. For the manual measurements, the standard deviation of error was found to be approximately 0.4 cm for DBH growth and 0.03 m3 for volume growth, which were the lowest of the three methods but not by a large margin. This highlights the need for more accurate reference data as the accuracy of laser scanning-based growth estimation methods continues to approach the accuracy of manual measurements.

Evaluation of mobile laser scanning acquisition scenarios for automated wood volume estimation in a temperate hardwood forest using quantitative structural models

This study explores how data from a handheld mobile laser scanning (MLS) system and quantitative structural models (QSM) can be used to estimate tree structural attributes. Four MLS acquisition scenarios were investigated in a 1 ha temperate hardwood stand, including 15 and 35 m parallel lines, nine circular plots, and a 20 m × 20 m grid. Results were compared against terrestrial laser scanning and destructive field measurements. All acquisition scenarios yielded comparable results, except for the 35 m scenario, which showed greater variability. The 20 m × 20 m grid scenario showed the highest accuracy, with an RMSE of 0.41 m (2.07%) for tree height, 3.98 cm (14.93%) for diameter at breast height, 0.21 m³ (19.28%) for merchantable wood volume, and 0.07 m³ (10.11%) for merchantable stem volume. A bias &lt; 5% was observed for these key attributes, except for an 11.68% bias in merchantable wood volume. Overestimation of branch volume was identified as the primary source of bias related to merchantable wood volume. This study highlights MLS’s potential for accurate, non-destructive estimation of tree structural attributes, while pointing out the need to refine noise removal and to assess the most suitable acquisition scenarios for various forest types.

Particle tracking in snow avalanches with in situ calibrated inertial measurement units

Abstract In the course of an artificially triggered avalanche, a particle tracking procedure is combined with supplementary measurements, including Global Navigation Satellite System (GNSS) positioning, terrestrial laser scanning and Doppler radar measurements. Specifically, an intertial measurement unit is mounted inside a rigid sphere, which is placed in the avalanche track. The sphere is entrained by the moving snow, recording translational accelerations, angular velocities and the flux density of Earth's magnetic field. Based on the recorded data, we present a threefold analysis: (i) a qualitative data interpretation, identifying different particle motion phases which are associated with corresponding flow regimes, (ii) a quantitative time integration algorithm, determining the corresponding particle trajectory and associated velocities on the basis of standard sensor calibration, and (iii) an improved quantitative evaluation relying on a novel in situ sensor calibration technique, which is motivated by the limitations of the given dataset. The final results, i.e. the evolution of the angular orientation of the sensor unit, translational and rotational velocities and estimates of the sensor trajectory, are assessed with respect to their reliability and relevance for avalanche dynamics as well as for future design of experiments.

High-resolution repeat topography of drifting ice floes in the Arctic Ocean from terrestrial laser scanning

Snow and ice topography impact and are impacted by fluxes of mass, energy, and momentum in Arctic sea ice. We measured the topography on approximately a 0.5 km2 drifting parcel of Arctic sea ice on 42 separate days from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS). These data are aligned into an ice-fixed, lagrangian reference frame such that topographic changes (e.g., snow accumulation) can be observed for time periods of up to six months. Using in-situ measurements, we have validated the vertical accuracy of the alignment to ± 0.011 m. This data collection and processing workflow is the culmination of several prior measurement campaigns and may be generally applied for repeat TLS measurements on drifting sea ice. We present a description of the data, a software package written to process and align these data, and the philosophy of the data processing. These data can be used to investigate snow accumulation and redistribution, ice dynamics, surface roughness, and they can provide valuable context for co-located measurements.

Pendugaan Cadangan Karbon Dengan Citra Sentinel-2B dan Terrestrial Laser Scanner Di Kawasan Hutan Dengan Tujuan Khusus (KHDTK) Pendidikan dan Pelatihan Kehutanan Fakultas Kehutanan Universitas Mulawarman

Measurement of forest carbon on the ground in a large scale is time-consuming and expensive. This research utilized remote sensing with Sentinel-2B image through its Vegetation Index and related those values with those obtained from field measurements and Terrestrial Laser Scanner (TLS). This study specifically compares the forest stand carbon value using TLS and field measurements and link it to the vegetation index. This study transforms the vegetation indices, i.e.: Transformed Vegetation Index (TVI), Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR) from Sentinel-2B imagery and relates them with field measurements and TLS. The calculation of carbon in forest stands using TLS revealed an average carbon of 151.35 ton/Ha. In contrast, in the field measurements, carbon was measured at 149.81 ton/Ha, and statistically, there was no difference between these two measurements. The relationship between the vegetation index and field measurements showed the best coefficient of correlation of TVI with (r) = 0.784 and (R2) = 0.524. The relationship between the vegetation index and TLS measurements showed the best coefficient of correlation of TVI with (r) = 0.759 and the coefficient of determination (R2) = 0.577.

East African megafauna influence on vegetation structure permeates from landscape to tree level scales

African savanna elephants (Loxodonta africana) can substantially modify their habitat through their interactions with woody vegetation. Nonetheless, the scale, intensity and characteristics of these relations are not yet fully understood. Consequently, it is unclear how vegetation-megafauna interactions can be disrupted by external factors, such as land management. This study attempted to quantify and characterize structural changes in vegetation caused by elephants, from landscape to tree level scales. We applied multi-scale geospatial tools, including airborne (ALS) and terrestrial laser scanning (TLS), to address the following questions: (1) How do elephants shape landscape level vegetation structure in conservation areas? (2) Are the impacts of elephants evident on individual tree architecture? Our study area was located at the Taita Hills Wildlife Sanctuary in South-eastern Kenya. The occurrence of elephants was estimated using elephant observation records and proximity to elephant tracks. Landscape level structure was assessed using tree density maps calculated based on individually detected treetops from ALS data. Next, TLS measurements of 72 trees were processed using quantitative structural modelling to characterize their architecture. Our results demonstrate a widespread influence of elephants on both landscape and tree level structural characteristics. This influence was strongly mediated by management, as we observed differences in vegetation structure inside and outside conservation areas. Tree density was up to 42% lower (5.84 trees/ha) in conservation areas than in non-conservation areas (10.17 trees/ha). Trees were relatively larger with closer proximity to elephant tracks, while smaller trees were more often observed in areas further away from elephants. At an architectural level, trees closer to elephant tracks had lower ratio between the crown length and the tree height, demonstrating a substantial influence of elephants on the morphological characteristics of trees. Our results highlight the importance of accounting for vegetation fauna interactions when planning conservation areas in African savannahs.

COST-EFFICIENT METHODS OF DERIVING SLOPE INFORMATION FOR ROAD SEGMENTS IN DRIVER-ASSISTANCE APPLICATIONS

Abstract. An advanced driver-assistance system (ADAS) is any of a group of technologies that assist drivers in driving and parking functions. Through a safe human-machine interface, ADAS increase car and road safety. These Advanced driver-assistance systems rely on special maps with extended geometry and attribute information. This extra information includes slope, curvature, and speed limit. ADAS-enabled maps are usually rather expensive in the industry. This paper is focused on finding cost-efficient alternatives for generating the slope aspect of ADAS maps. Slope and height information is not only used in ADAS but is a critical aspect of calculating electronic vehicle (EV) ranges, and truck fuel-efficiency calculations as well. ADAS slope information usually requires high-accuracy surveys. This paper researches the possible generation of slope information for road segments with the use of digital elevation models (DEM) or crowdsourcing with low-cost sensors and Kalman filtering. The first approach is based on globally available DEMs with interpolation and filtering with road geometry. DEMs have variable accuracy depending on the type of technology used in producing them. Such technologies include photogrammetry, aerial and terrestrial laser scanning (ALS, TLS), or aerial or space radar measurements. The other method is by using low-cost GPS and IMU sensors for generating altitude profiles. These produced altitude profiles are compared with a profile generated from a high-accuracy survey using large-resolution DEMs produced by aerial photogrammetry or aerial laser scanning. This paper proposes metrics with which these datasets can be compared, one is using the height differences, and the other compares the slope values at discrete common points. In the conclusion, the paper tries to find use cases for the low-accuracy data.

Features of inventory of green plantings by automated terrestrial laser scanning methods

The aim of this work is to investigate the process of obtaining necessary information about the metric parameters of small-area arrays, linearly arranged and individual green plantings on predominantly urbanized territories, and to apply the results of data processing in the compilation of topographic and special maps from the corresponding scanning materials. Methodology. For this purpose, terrestrial laser scanning methods, dynamic laser scanning as a data source for tree-level mapping of the territory, and as an information base for filling in the respective cadastres are subject to research. The possibilities of using data from these methods to obtain information about green plantings using modern software tools have been explored. Based on terrestrial laser scanning data performed in accordance with the requirements of regulatory spatial reference documents, data processing of terrestrial laser scanning was carried out using automated methods, namely the Terrasolid software suite. The need for more than 40% coverage of the tree trunk with a point cloud obtained from laser scanning to eliminate possible errors in determining the relevant parameters due to the heterogeneity of the structure of different tree trunks has been confirmed. Preliminary processing of scanning materials was carried out using FARO Scene 2020 software. Scientific novelty and practical significance. An experiment was conducted to analyze the creation of both a plan-altitude and an information base regarding green plantings on selected objects within the Zakarpattia region. The process of collecting data on green plantings was improved by using terrestrial laser scanning and partial GNSS measurements, instead of traditional topographic-geodetic methods. A table containing information on green planting data has been created for the studied objects' territory. Automated methods were used to gather this information, including details about their location in the adopted coordinate system and the trunk diameter at a height of 1.3 meters.

Similarity and Change Detection of Relief in a Proglacial River Valley (Scott River, SW Svalbard)

This study focuses on contemporary geomorphic changes in the proglacial valley floor of the Scott River catchment (northwest of Wedel Jarlsberg Land, southwestern Spitsbergen). The similarity and variability of landforms along the entire 3.3 km length of the unglaciated valley floor was assessed using precision terrestrial laser scanning (TLS) measurements made in July/August 2010–2013. Digital terrain models (DTMs) were generated from the high-resolution TLS survey data, followed by a geomorphon map, which was then used for a similarity and changes of morphology analysis performed with GeoPAT2 software. The study revealed a large spatial variation of contemporary processes shaping the valley floor and changes in its morphology. Their spatial distribution relates to the geologically determined split of the valley floor into three morphological zones separated by gorges. The upper gorge cuts the terminal moraine rampart, which limits the uppermost section of the valley floor, which is up to 700 m wide and is occupied by the outwash plain. The study showed that this is the area characterised by the greatest dynamics of contemporary geomorphic processes and relief changes. The similarity index value here is characterised by a large spatial variation that in some places reaches values close to 0. In the middle section stretching between the upper gorge (cutting the terminal moraine) and the lower gorge (cutting the elevated marine terraces), a much smaller variability of processes and landforms is observed, and the found changes of the valley floor relief mainly include the area of braided channel activity. Similarity index values in this zone do not fall below 0.65. The lowest section, the mouth of the alluvial fan, on the other hand, is characterised by considerable spatial differentiation. The southern part of the fan is stable, while the northern part is intensively re-shaped and has a similarity index that locally falls below 0.5. The most dynamic changes are found within the active channel system along the entire length of the unglaciated section of the Scott River. The peripheral areas, located in the outer zones of the valley floor, show great stability.

An approach for considering the object surface properties in a TLS stochastic model.

The interaction between laser beams and backscattering object surfaces lies at the fundamental working principle of any Terrestrial Laser Scanning (TLS) system. Optical properties of surfaces such as concrete, metals, wood, etc., which are commonly encountered in structural health monitoring of buildings and structures, constitute an important category of systematic and random TLS errors. This paper presents an approach for considering the random errors caused by object surfaces. Two surface properties are considered: roughness and reflectance. The effects on TLS measurements are modeled stepwise in form of a so-called synthetic variance-covariance matrix (SVCM) based on the elementary error theory. A line of work is continued for the TLS stochastic model by introducing a new approach for determining variances and covariances in the SVCM. Real measurements of cast stone façade elements of a tall building are used to validate this approach and show that the quality of the estimation can be improved with the appropriate SVCM.

Evaluating the potential of airborne hyperspectral LiDAR for assessing forest insects and diseases with 3D Radiative Transfer Modeling

Accurately monitoring forest insects and diseases disturbances is important for managing forests and implementing effective forest quality improvement measures. However, monitoring disturbances in the lower and middle parts of the forest canopy with traditional remote sensing technologies is difficult. A new sensor called hyperspectral LiDAR (HSL) makes the monitoring of these forest disturbances possible, however, its applicability to canopy scale has not been fully studied due to the current hardware limitation. This paper assessed the potential of airborne hyperspectral LiDAR (AHSL) for monitoring forest insects and diseases stress using 3D radiative transfer modeling and in-situ measurements. A virtual 3D forest scene with explicitly described structures was first reconstructed from terrestrial laser scanning and field measurement data, upon which a number of different insects and diseases disturbance scenarios with different damage locations and stress levels were defined. AHSL point cloud and the corresponding hyperspectral image (HI) were then simulated with large-scale and remote sensing image simulation (LESS) model for each combination of the different damage locations and stress levels. LiDAR point cloud from different layers of the simulated AHSL point cloud were then extracted and rasterized into images with 3-m spatial resolution, which, along with the hyperspectral images, were used to test the insect and disease monitoring ability by using a random forest model. Results show that AHSL has significant higher overall accuracies (OA: 65.95% ∼ 89.45%) than HI (OA: 33.99% ∼ 57.02%) for predicting insects and diseases stress levels. Compared to AHSL, HI is affected by a variety of factors such as soil and shadows, resulting in poorer monitoring capability for different damage locations, with the highest classification accuracy in the case of entire canopy damage (OA: 57.02%). For AHSL, it has good classification accuracy for all damage locations, with the lowest accuracy in the case of lower canopy damage (OA: 65.95%). This study demonstrates that AHSL is a promising and reliable tool to monitor forest disturbances, especially for structural and spectral changes in the lower and middle parts of canopy, which may have great potential for early detecting forest insects and diseases.

Application of terrestrial laser scanning measurements for wind turbine blade condition surveying

Application of terrestrial laser scanning measurements for wind turbine blade condition surveying

Integration of high-precision UAV laser scanning and terrestrial scanning measurements for determining the shape of a water tower

This study was aimed at integrating surveys from terrestrial laser scanning (TLS) and high-precision scanning performed by a drone (ULS) for a tower structure. This will allow a complete point cloud to be obtained for the entire object. Integrated measurements will eliminate gaps in the point cloud, characteristic of TLS or ULS separate measurements. Existing studies report ULS accuracy of a few cm, but the precision may be about 10 mm. Assuming that the ULS point cloud will be matched to the TLS cloud, which has higher accuracy, the high accuracy of the whole integrated model can be expected. The integration of the surveys was carried out for the water tower and a coherent model of the structure was obtained, with a mean merge error of 13 mm. Detailed comparative analyses were carried out in selected cross-sections, obtaining mostly a several-millimetre compliance of the results in the analysed categories.

StrucNet: a global network for automated vegetation structure monitoring.

Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Spaceborne measurements can provide large-scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three-dimensional vegetation structure at local scales. Here we demonstrate the potential of high-frequency ground-based laser scanning to systematically monitor structural changes in vegetation. We present a proof-of-concept high-temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high-temporal laser scanning that can allow upscaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways.

Crown-Level Structure and Fuel Load Characterization from Airborne and Terrestrial Laser Scanning in a Longleaf Pine (Pinus palustris Mill.) Forest Ecosystem

Airborne Laser Scanners (ALS) and Terrestrial Laser Scanners (TLS) are two lidar systems frequently used for remote sensing forested ecosystems. The aim of this study was to compare crown metrics derived from TLS, ALS, and a combination of both for describing the crown structure and fuel attributes of longleaf pine (Pinus palustris Mill.) dominated forest located at Eglin Air Force Base (AFB), Florida, USA. The study landscape was characterized by an ALS and TLS data collection along with field measurements within three large (1963 m2 each) plots in total, each one representing a distinct stand condition at Eglin AFB. Tree-level measurements included bole diameter at breast height (DBH), total height (HT), crown base height (CBH), and crown width (CW). In addition, the crown structure and fuel metrics foliage biomass (FB), stem branches biomass (SB), crown biomass (CB), and crown bulk density (CBD) were calculated using allometric equations. Canopy Height Models (CHM) were created from ALS and TLS point clouds separately and by combining them (ALS + TLS). Individual trees were extracted, and crown-level metrics were computed from the three lidar-derived datasets and used to train random forest (RF) models. The results of the individual tree detection showed successful estimation of tree count from all lidar-derived datasets, with marginal errors ranging from −4 to 3%. For all three lidar-derived datasets, the RF models accurately predicted all tree-level attributes. Overall, we found strong positive correlations between model predictions and observed values (R2 between 0.80 and 0.98), low to moderate errors (RMSE% between 4.56 and 50.99%), and low biases (between 0.03% and −2.86%). The highest R2 using ALS data was achieved predicting CBH (R2 = 0.98), while for TLS and ALS + TLS, the highest R2 was observed predicting HT, CW, and CBD (R2 = 0.94) and HT (R2 = 0.98), respectively. Relative RMSE was lowest for HT using three lidar datasets (ALS = 4.83%, TLS = 7.22%, and ALS + TLS = 4.56%). All models and datasets had similar accuracies in terms of bias (&lt;2.0%), except for CB in ALS (−2.53%) and ALS + TLS (−2.86%), and SB in ALS + TLS data (−2.22%). These results demonstrate the usefulness of all three lidar-related methodologies and lidar modeling overall, along with lidar applicability in the estimation of crown structure and fuel attributes of longleaf pine forest ecosystems. Given that TLS measurements are less practical and more expensive, our comparison suggests that ALS measurements are still reasonable for many applications, and its usefulness is justified. This novel tree-level analysis and its respective results contribute to lidar-based planning of forest structure and fuel management.

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.

Assessing Structural Complexity of Individual Scots Pine Trees by Comparing Terrestrial Laser Scanning and Photogrammetric Point Clouds

Structural complexity of trees is related to various ecological processes and ecosystem services. To support management for complexity, there is a need to assess the level of structural complexity objectively. The fractal-based box dimension (Db) provides a holistic measure of the structural complexity of individual trees. This study aimed to compare the structural complexity of Scots pine (Pinus sylvestris L.) trees assessed with Db that was generated with point cloud data from terrestrial laser scanning (TLS) and aerial imagery acquired with an unmanned aerial vehicle (UAV). UAV imagery was converted into point clouds with structure from motion (SfM) and dense matching techniques. TLS and UAV measured Db-values were found to differ from each other significantly (TLS: 1.51 ± 0.11, UAV: 1.59 ± 0.15). UAV measured Db-values were 5% higher, and the range was wider (TLS: 0.81–1.81, UAV: 0.23–1.88). The divergence between TLS and UAV measurements was found to be explained by the differences in the number and distribution of the points and the differences in the estimated tree heights and number of boxes in the Db-method. The average point density was 15 times higher with TLS than with UAV (TLS: 494,000, UAV 32,000 points/tree), and TLS received more points below the midpoint of tree heights (65% below, 35% above), while UAV did the opposite (22% below, 78% above). Compared to the field measurements, UAV underestimated tree heights more than TLS (TLS: 34 cm, UAV: 54 cm), resulting in more boxes of Db-method being needed (4–64%, depending on the box size). Forest structure (two thinning intensities, three thinning types, and a control group) significantly affected the variation of both TLS and UAV measured Db-values. Still, the divergence between the two approaches remained in all treatments. However, TLS and UAV measured Db-values were consistent, and the correlation between them was 75%.