THE USE OF DIFFERENT MEASUREMENT TECHNOLOGIES TO CALCULATE THE VOLUME OF A ROCK OBJECT IN THE WIETRZNIA NATURE RESERVE IN KIELCE

Quantifying tropical forest structure through terrestrial and UAV laser scanning fusion in Australian rainforests

SLAM-aided forest plot mapping combining terrestrial and mobile laser scanning

Calibration and validation of aboveground biomass (AGB) (AGB) products retrieved from satellite-borne sensors require accurate AGB estimates across hectare scales (1 to 100ha). Recent studies recommend making use of non-destructive terrestrial laser scanning (TLS) based techniques for individual tree AGB estimation that provide unbiased AGB predictors. However, applying these techniques across large sites and landscapes remains logistically challenging. Unoccupied aerial vehicle laser scanning (UAV-LS) has the potential to address this through the collection of high density point clouds across many hectares, but estimation of individual tree AGB based on these data has been challenging so far, especially in dense tropical canopies. In this study, we investigated how TLS and UAV-LS can be used for this purpose by testing different modelling strategies with data availability and modelling framework requirements. The study included data from four forested sites across three biomes: temperate, wet tropical, and tropical savanna. At each site, coincident TLS and UAV-LS campaigns were conducted. Diameter at breast height (DBH) and tree height were estimated from TLS point clouds. Individual tree AGB was estimated for ≥170 trees per site based on TLS tree point clouds and quantitative structure modelling (QSM), and treated as the best available, non-destructive estimate of AGB in the absence of direct, destructive measurements. Individual trees were automatically segmented from the UAV-LS point clouds using a shortest-path algorithm on the full 3D point cloud. Predictions were evaluated in terms of individual tree root mean square error (RMSE) and population bias, the latter being the absolute difference between total tree sample population TLS QSM estimated AGB and predicted AGB. The application of global allometric scaling models (ASM) at local scale and across data modalities, i.e., field-inventory and light detection and ranging LiDAR metrics, resulted in individual tree prediction errors in the range of reported studies, but relatively high population bias. The use of adjustment factors should be considered to translate between data modalities. When calibrating local models, DBH was confirmed as a strong predictor of AGB, and useful when scaling AGB estimates with field inventories. The combination of UAV-LS derived tree metrics with non-parametric modelling generally produced high individual tree RMSE, but very low population bias of ≤5% across sites starting from 55 training samples. UAV-LS has the potential to scale AGB estimates across hectares with reduced fieldwork time. Overall, this study contributes to the exploitation of TLS and UAV-LS for hectare scale, non-destructive AGB estimation relevant for the calibration and validation of space-borne missions targeting AGB estimation.

This study explores the feasibility of applying single-scan airborne, static terrestrial and mobile laser scanning for improving the accuracy of tree height growth measurement. Specifically, compared to the traditional works on forest growth inventory with airborne laser scanning, two issues are regarded: “Can the new technique characterize the height growth for each individual tree?” and “Can this technique refine the minimum growth-discernable temporal interval further?” To solve these two puzzles, the sampling principles of the three laser scanning modes were first examined, and their error sources against the task of tree-top capturing were also analyzed. Next, the three-year growths of 58 Nordic maple trees (Crimson King) for test were intermittently surveyed with one type of laser scanning each time and then analyzed by statistics. The evaluations show that the height growth of each individual tree still cannot be reliably characterized even by single-scan terrestrial laser scanning, and statistical analysis is necessary in this scenario. After Gaussian regression, it is found that the minimum temporal interval with distinguishable tree height growths can be refined into one month based on terrestrial laser scanning, far better than the two years deduced in the previous works based on airborne laser scanning. The associated mean growth was detected to be about 0.12 m. Moreover, the parameter of tree height generally under-estimated by airborne and even mobile laser scanning can be relatively revised by means of introducing static terrestrial laser scanning data. Overall, the effectiveness of the proposed technique is primarily validated.

Soil roughness represents fine-scale surface geometry which figures in many geophysical models. While static photogrammetric techniques (terrestrial images and laser scanning) have been recently proposed as a new source for deriving roughness heights, there is still need to overcome acquisition scale and viewing geometry issues. By contrast to the static techniques, images taken from unmanned aerial vehicles (UAV) can maintain near-nadir looking geometry over scales of several agricultural fields. This paper presents a pilot study on high-resolution, soil roughness reconstruction and assessment from UAV images over an agricultural plot. As a reference method, terrestrial laser scanning (TLS) was applied on a 10 m x 1.5 m subplot. The UAV images were self-calibrated and oriented within a bundle adjustment, and processed further up to a dense-matched digital surface model (DSM). The analysis of the UAV- and TLS-DSMs were performed in the spatial domain based on the surface autocorrelation function and the correlation length, and in the frequency domain based on the roughness spectrum and the surface fractal dimension (spectral slope). The TLS- and UAV-DSM differences were found to be under ±1 cm, while the UAV DSM showed a systematic pattern below this scale, which was explained by weakly tied sub-blocks of the bundle block. The results also confirmed that the existing TLS methods leads to roughness assessment up to 5 mm resolution. However, for our UAV data, this was not possible to achieve, though it was shown that for spatial scales of 12 cm and larger, both methods appear to be usable. Additionally, this paper suggests a method to propagate measurement errors to the correlation length.

Calculating the volume for various types of surfaces and materials is important for many branches of engineering sciences. Correct volume calculation often has a significant impact on the cost and time of a given project. These type of calculations are already applied at the design level. Measurement of cubature is crucial, for example, in construction and mining. The paper presents an analysis of and calculation results for measuring the volume of soil masses using different measurement techniques, which include: LIDAR (in this case of terrestrial and airborne laser scanning), photos taken with the use of UAV and measurements in the GNSS method. The object of the study was an earth mound located in the Park Dębnicki in Kraków. Relative volume error has been calculated in relation to the terrestrial laser scanning (TLS) method. For each of the tested methods, the error remained within the limits allowed by the standards and amounted to 0.2% for airborne laser scanning (ALS), 2.3% for photos obtained from UAVs and 3.4% for the GNNS-RTK method. The results of tests are presented in graphic and tabular forms. The obtained results were compared and the most advantageous measurement techniques to be used in determining the cubic capacity of this particular research object was indicated.

Accurate estimates of vegetation structure are important for a large number of applications including ecological modeling and carbon budgets. Light detection and ranging (LiDAR) measures the three-dimensional structure of vegetation using laser beams. Most LiDAR applications today rely on airborne platforms for data acquisitions, which typically record between 1 and 5 “discrete” returns for each outgoing laser pulse. Although airborne LiDAR allows sampling of canopy characteristics at stand and landscape level scales, this method is largely insensitive to below canopy biomass, such as understorey and trunk volumes, as these elements are often occluded by the upper parts of the crown, especially in denser canopies. As a supplement to airborne laser scanning (ALS), a number of recent studies used terrestrial laser scanning (TLS) for the biomass estimation in spatially confined areas. One such instrument is the Echidna® Validation Instrument (EVI), which is configured to fully digitize the returned energy of an emitted laser pulse to establish a complete profile of the observed vegetation elements. In this study we assess and compare a number of canopy metrics derived from airborne and TLS. Three different experiments were conducted using discrete return ALS data and discrete and full waveform observations derived from the EVI. Although considerable differences were found in the return distribution of both systems, ALS and TLS were both able to accurately determine canopy height (Δ height r2 > 0.90, p < 0.01). When using more spatially explicit approaches for modeling the biomass and volume throughout the stands, the differences between ALS and TLS observations were more distinct; however, predictable patterns exist based on sensor position and configuration.

BackgroundPlant growth is a good indicator of crop performance and can be measured by different methods and on different spatial and temporal scales. In this study, we measured the canopy height growth of maize (Zea mays), soybean (Glycine max) and wheat (Triticum aestivum) under field conditions by terrestrial laser scanning (TLS). We tested the hypotheses whether such measurements are capable to elucidate (1) differences in architecture that exist between genotypes; (2) genotypic differences between canopy height growth during the season and (3) short-term growth fluctuations (within 24 h), which could e.g. indicate responses to rapidly fluctuating environmental conditions. The canopies were scanned with a commercially available 3D laser scanner and canopy height growth over time was analyzed with a novel and simple approach using spherical targets with fixed positions during the whole season. This way, a high precision of the measurement was obtained allowing for comparison of canopy parameters (e.g. canopy height growth) at subsequent time points.ResultsThree filtering approaches for canopy height calculation from TLS were evaluated and the most suitable approach was used for the subsequent analyses. For wheat, high coefficients of determination (R2) of the linear regression between manually measured and TLS-derived canopy height were achieved. The temporal resolution that can be achieved with our approach depends on the scanned crop. For maize, a temporal resolution of several hours can be achieved, whereas soybean is ideally scanned only once per day, after leaves have reached their most horizontal orientation. Additionally, we could show for maize that plant architectural traits are potentially detectable with our method.ConclusionsThe TLS approach presented here allows for measuring canopy height growth of different crops under field conditions with a high temporal resolution, depending on crop species. This method will enable advances in automated phenotyping for breeding and precision agriculture applications. In future studies, the TLS method can be readily applied to detect the effects of plant stresses such as drought, limited nutrient availability or compacted soil on different genotypes or on spatial variance in fields.

Abstract. Soil roughness represents fine-scale surface geometry which figures in many geophysical models. While static photogrammetric techniques (terrestrial images and laser scanning) have been recently proposed as a new source for deriving roughness heights, there is still need to overcome acquisition scale and viewing geometry issues. By contrast to the static techniques, images taken from unmanned aerial vehicles (UAV) can maintain near-nadir looking geometry over scales of several agricultural fields. This paper presents a pilot study on high-resolution, soil roughness reconstruction and assessment from UAV images over an agricultural plot. As a reference method, terrestrial laser scanning (TLS) was applied on a 10 m x 1.5 m subplot. The UAV images were self-calibrated and oriented within a bundle adjustment, and processed further up to a dense-matched digital surface model (DSM). The analysis of the UAV- and TLS-DSMs were performed in the spatial domain based on the surface autocorrelation function and the correlation length, and in the frequency domain based on the roughness spectrum and the surface fractal dimension (spectral slope). The TLS- and UAV-DSM differences were found to be under ±1 cm, while the UAV DSM showed a systematic pattern below this scale, which was explained by weakly tied sub-blocks of the bundle block. The results also confirmed that the existing TLS methods leads to roughness assessment up to 5 mm resolution. However, for our UAV data, this was not possible to achieve, though it was shown that for spatial scales of 12 cm and larger, both methods appear to be usable. Additionally, this paper suggests a method to propagate measurement errors to the correlation length.

This study presents a comparison between the use of wearable laser scanning (WLS) and terrestrial laser scanning (TLS) devices for automatic tree detection with an estimation of two dendrometric variables: diameter at breast height (DBH) and total tree height (TH). Operative processes for data collection and automatic forest inventory are described in detail. The approach used is based on the clustering of points belonging to each individual tree, the isolation of the trunks, the iterative fitting of circles for the DBH calculation and the computation of the TH of each tree. TLS and WLS point clouds were compared by the statistical analysis of both estimated forest dendrometric parameters and the possible presence of bias. Results show that the apparent differences in point density and relative precision between both 3D forest models do not affect tree detection and DBH estimation. Nevertheless, tree height estimation using WLS appears to be affected by the limited scanning range of the WLS used in this study. TH estimations for trees below a certain height are equivalent using WLS or TLS, whereas TH of taller trees is clearly underestimated using WLS.

Terrestrial Laser Scanner (TLS) has become a familiar instrument to be used in wide range of engineering application. It can be used for the rapid capture of accurate and highly detailed 3D point cloud datasets. The advantage of laser scanner is that it can record huge number of points in a short period of time. The main idea in this contribution assesses the accuracy of TLS relative to other traditional surveying instruments. This is done throughout four different case studies. In all case studies the 3D coordinates, obtained using total station (TS) are assumed the reference coordinates. First, a control point network, that consists of nine points, is measured using TS, TLS, and real time kinematic global navigation satellite system (RTK-GPS). The precision of each instrument is investigated considering the standard deviation (SD) of measurements. In addition, the accuracy of TLS and RTK-GPS is investigated considering the measurements RMS. Secondly, a grid levelling for a 30,000m2 ground terrain was performed using TS and TLS. After words, the RMS of TLS measurements is computed and a grid of 5mx5m is generated from both surfaces; formed using TS and TLS measurements. Thirdly, the effect of incidence angle on TLS measurements is assessed by measuring fifty-six points fixed on a building facade using different incident angles. Those points were measured using both TS and TLS, and then the absolute height differences between TS and TLS measurements were calculated to figure out the effect of decreasing the incidence angle on measurements. In the fourth case study, the accuracy of TLS on steep-vertical cut measurements is investigated by surveying a downhill area of 500m2 by both TS and TLS, the RMS of TLS measurements was calculated. Finally, based on the obtained results, it was found that TLS produces a higher vertical accuracy than RTK-GPS in measuring control point networks. The RMS of TLS measurements was about 5cm. Moreover, TLS incidence angle is not preferable to be less than 45 degrees as the accuracy degrades significantly after this value. In steep-vertical cut measurements, TLS obtained RMS almost of 6mm discrepancies with a lower measurement period. Eventually, despite the fact that TLS is more expensive than traditional surveying techniques, it is more beneficial in terms of time and effort saving. In addition, it can figure out acceptable accuracy ranges with more detailed surveyed data.

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%.

In the publication, the authors demonstrated the possibility of using terrestrial and airborne laser scanning technology for both inventory and modeling of architectural objects. First of all, they presented the use of laser scanning technology, for creation of 3D models of sacral objects, both the large ones, as well as the smaller ones constituting small architecture objects. For the airborne laser scanning, the subject of the study was the Sanctuary of the Divine Mercy in Krakow along with the surrounding complex of sacral buildings. Modelling and visualization of the Sanctuary were made in the TerraSolid and MicroStation programs on the basis of a point cloud with a density of 12 points/m2. Data from terrestrial laser scanning were obtained on the basis of measurement with the use of terrestrial laser scanner Leica ScanStation P40 and included the Chapel of Our Lady of Czestochowa located in the Lasek Mogilski in Krakow.

There are several different methods in laser scanning technology including terrestrial laser scanner (TLS), airborne laser scanner (ALS), and mobile laser scanner (MLS). In addition to these scanners, there are personal laser scanners (PLS). PLS are examined under two main categories as handheld personal laser scanner (HPLS) and backpack personal laser scanner (BPLS) which are the latest additions to these laser scanning technologies. Today, the use of personal laser scanner technology is a popular research and application topics. The primary advantage of PLS lies in its high mobility in different topography conditions and rapid data acquisition. Unlike TLS and MLS, the operator carries the PLS device in the work area at standard walking speed, which is sufficient to collect data. Also, PLS technology eliminates the limitations of moving TLS equipment from one station point to another station point during the data collection process and installing instruments on a tripod again. In this paper, a case study was conducted using the LiBackpack DGC50 Mobile Scanner, which is the PLS technique, for the cadastral updating surveying in the Karaağaç District of Edirne province. It has been concluded that backpack laser scanners provide sufficient accuracy for cadastral studies in the study area.

Three dimensional terrestrial laser scanners have the potential to provide new insights into multidisciplinary coastal studies due to the extremely high spatial data resolution, speed of surveys and availability of additional parameters, namely return signal intensity and RGB color information. Not only can high resolution morphological maps be produced, but quantities such as sediment type, surface roughness, surface moisture and vegetation cover can be inferred from the point density and additional parameters. This chapter firstly provides a review of the state of the art of use of terrestrial laser scanners in coastal environments, paying particular attention to the use of data abundance to derive additional information beyond morphology. Terrestrial laser scanners have been used more extensively in other fields of study and hence relevant studies from these sectors are also described. Secondly a case study will be presented of terrestrial laser scanner usage: a terrestrial laser scanner has been used to study barrier and cusp evolution on a composite sand-gravel beach. This will demonstrate the scanners ability to measure fine scale morphological features, surface roughness and will demonstrate techniques to define sand and gravel regions via RGB color properties. Finally some discussion into the future potential and caveats to the use of terrestrial laser scanners are presented. These caveats are primarily the short range of many instruments and the data surplus for some more uniform coastlines. These mean that the appropriateness of a terrestrial laser scanner survey will depend upon both the site and the scales of the physical processes being investigated.