Multi-temporal survey of diaphragm wall with terrestrial laser scanning method

Abstract. In general, poor road conditions, specifically road cracks constitute a public nuisance, causing troublesome to road users, severe damage to vehicles and accidents. Hence, it is essential to detect the road crack earlier as an early-stage preventive for maintenance, but traditional inspection method used in Malaysia to physically collect the road information is extremely time-consuming, hazardous and labour-intensive. Nowadays, new technologies have improved the measuring performance. This leaves a gap in comparing two modern technologies in road cracks mapping. This study aims to explore the quality assessment between the unmanned aerial vehicle (UAV) and terrestrial laser scanning (TLS) methods in road cracks mapping. Two study areas inside the campus of Universiti Teknologi Malaysia (UTM), Johor, were selected. The ground control points (GCPs) and check points (CPs) at the study areas were georeferenced by global navigation satellite system (GNSS) data with MyRTKNet and ISKnet connections. Low altitude aerial imageries were collected using DJI Phantom 4 UAV, while Topcon GLS-2000 was employed to acquire the dense data of the cracked road. GNSS and manual inspection methods were performed to evaluate the results. In terms of mapping and measurement, both TLS and UAV methods produce almost similar results with average RMSE differences ranging from ±0.003 m to ±0.030 m and ±0.042 m to ±0.224 m respectively. This revealed that TLS is more accurate than UAV in mapping and measuring work. Differences in DTM quality across these approaches is below two (2) cm. Based on this study, TLS is more reliable than UAV. However, UAV offers advantages based on several considerations such as cost, time, safety, and accessibility. In summary, findings from this study shed some light to the authorities on the feasibility of UAV and TLS methods in road cracks mapping.

In geodetic measurements of deformations in shell cooling towers, an important factor is to optimize the number of points representing the exterior surface of the shell. The conducted analyses of damage to such structures proved that cooling towers exhibited shell deformation consisting of irregular vertical waves (three concavities and two convexities), as well as seven horizontal waves. On this basis, it is claimed that, in accordance with the Shannon theorem, the correct representation of the generated waves requires the measurement of the cooling tower shell in a minimum of 12 vertical and 14 horizontal sections. Such density of the points may not be sufficient to represent local imperfections of the shell. The article presents the results of test measurements and their analysis, which were conducted to verify the assumptions as to the optimal number of measurement points for the shell of a cooling tower. The evaluation was based on a comparative analysis of the data obtained by the Terrestrial Laser Scanning (TLS) method, creating a very detailed model of geometric imperfections in an actual cooling tower with a height of 100 m. Based on the data obtained by the TLS method, point grids of various density were generated. An additional measurement of the cooling tower shell deformation was performed using a precise electronic total station with reflectorless measurement option. Therefore, it was possible to assess the accuracy of measurements by laser scanning in relation to measurements obtained by reflectorless total stations.

Forests make up 34.1% of the Czech Republic total area and forest roads account for nearly the same length (47,465 km) as all other roads administered by the state and its regions (55,738 km). Forest roads are not as intensively used as other roads. On the other hand, as logging trucks carry the maximum permitted load on roads and forests create a specific microclimate, forest roads are subject to rapid wear. A road wearing course is generally designed for 20 years of service and for a maximum damage level of 25% before they are supposed to be reconstructed. To ensure this life cycle is adhered to, more efficient, faster, and more flexible surface damage detection adaptable for forest environment is needed. As smartphones and their optical devices, i.e., new iPhones with LiDAR sensors, become more advanced, the option arises to perform laser scanning on road surfaces using smartphones applications. This work aimed to test this technology and its precision applicability to assessing damage to a forest wearing course and compare it with another hand-held personal laser scanner (PLShh), represented in this study by GeoSLAM ZEB Horizon scanner, and more precise terrestrial laser scanning (TLS) technology, represented in this study by Faro Focus 3D laser scanner, which have started to replace tacheometric wearing course damage surveying thanks to their greater precision. So, this study involved a comparison of three alternative laser scanning methods focused especially on these, which are implemented in new iPhones for tacheometric surveying. First, a Faro Focus 3D laser scanner was used for the TLS method. Second, the PLShh method was tested on a GeoSLAM ZEB Horizon scanner. Third, another PLShh method using an iPhone 13 Pro with applications 3D Scanner and Polycam was evaluated. If we are comparing positional height accuracy of PLShh to tacheometric surveying on reference cross position height coordinates, ZEB Horizon achieved devXY and devZ RMSE 0.108 m; 0.025 m; iPhone 13 Pro with 3D Scanner app devXY and devZ RMSE 0.185 m; 0.021 m, and with Polycam app devXY and devZ RMSE 0.31 m; 0.045. TLS achieved the best results with devXY RMSE 0.049 and devZ RMSE 0.0077. The results confirm that only the TLS scanner achieves precision values in height differences applicable for an assessment of forest road wearing course damage measurement comparable with tacheometric surveying. Surprisingly, comparing the PLShh scanners to the TLS technology, they achieved interesting results, comparing their transverse profiles and 3D objects as digital surface models (DSM) of the road to TLS in height position. In transverse profiles, ZEB Horizon achieved devZ RMSE 0.032 m; iPhone 13 Pro with 3D Scanner app devZ RMSE 0.017 m, and with Polycam app devZ RMSE 0.041 m compared to the TLS method measured using a Faro Focus 3D static laser scanner. Comparing forest road DSM to Faro Focus 3D, ZEB Horizon achieved devZ RMSE 0.028 m; iPhone 13 Pro with 3D Scanner app devZ RMSE 0.018 m and with Polycam devZ RMSE 0.041 m. These results in height differences show that the height accuracy of PLShh achieves precision, which is applicable to determining the current shape of forest road wearing course compared to the required roof shape gradient. However, further testing provided the insight that such a kind of PLShh measurement is still only possible to use for the identification of a transverse profile shape, as in length measurement the length error increases. All PLShh are able to capture the current shape of forest road cross profile, but still they cannot be used for any design or calculation of material measurement needed for wearing course repair.

The accuracy of 3D indoor reconstructed models is critical in various applications such as indoor navigation, virtual reality (VR), and building information modelling (BIM). This research study aims to evaluate the accuracy of Unmanned Aerial Vehicles (UAV) and Terrestrial Laser Scanning (TLS) for 3D indoor modelling in large-scale building environments. To achieve this, several evaluations were made towards the number of point clouds, estimated costs and accuracy of the 3D indoor reconstructed model generated from dense point clouds acquired by Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanner (TLS). A small indoor classroom was selected for this study approximately 100m2. In UAV data acquisition, three (3) flight missions were set up at the front, left and right views. Meanwhile, five (5) scanning stations were placed on-site for the TLS method. Due to various different flight mission views in the UAV dataset, the number of point clouds was quite higher compared to the TLS method. However, a better-quality visualization of the TLS model has been obtained as opposed to the UAV 3D model. For the required time to generate a 3D model, it showed that UAV processing time was more consuming lots of time than the TLS method, especially when georeferencing the overlapping photographs. In terms of accuracy, the RMSE value from TLS was better than UAV at 0.003m compared to UAV at 0.021m. Overall, this study provides insights into the accuracy and suitability of UAV and TLS for 3D indoor modelling in large-scale building environments. The results can inform decision-making processes in various industries such as architecture, engineering, and construction, where accurate and reliable 3D models are crucial for design, planning, and management purposes.

In continuous cover forestry, plenter silviculture is regarded as an elaborated system for optimizing the sustainable production of high-quality timber maintaining a constant but heterogeneous canopy. Its complexity necessitates high silvicultural expertise and a detailed assessment of forest stand structural variables. Terrestrial laser scanning (TLS) can offer reliable techniques for long-term tree mapping, volume calculation, and stand variables assessment in complex forest structures. We conducted surveys using both automated TLS and conventional manual methods (CMM) on two plots with contrasting silvicultural regimes within the Black Forest, Germany. Variations in automated tree detection and stand variables were greater between different TLS surveys than with CMM. TLS detected an average of 523 tree stems per hectare, while CMM counted 516. Approximately 9.6% of trees identified with TLS were commission errors, with 6.5% of CMM trees being omitted using TLS. Basal area per hectare was slightly higher in TLS (38.9 m3) than in CMM (38.2 m3). However, CMM recorded a greater standing volume (492.7 m3) than TLS (440.5 m3). The discrepancy in stand volume between methods was primarily due to TLS underestimating tree height, especially for taller trees. DBH bias was minor at 1 cm between methods. Repeated TLS inventories successfully matched an average of 424 tree positions per hectare. While TLS adequately characterizes complex plenter forest structures, we propose enhancing this methodology with personal laser scanning to optimize crown coverage and efficiency and direct volume measurements for increased accuracy of wood volume estimations. Additionally, utilizing 3D point cloud data-derived metrics, such as structural complexity indices, can further enhance plenter forest management.

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

Complex Geodetic and Photogrammetric Monitoring of the Kral’ovany Rock Slide

The availability of high-resolution Digital Surface Models of coastal environments is of increasing interest for scientists involved in the study of the coastal system processes. Among the range of terrestrial and aerial methods available to produce such a dataset, this study tests the utility of the Structure from Motion (SfM) approach to low-altitude aerial imageries collected by Unmanned Aerial Vehicle (UAV). The SfM image-based approach was selected whilst searching for a rapid, inexpensive, and highly automated method, able to produce 3D information from unstructured aerial images. In particular, it was used to generate a dense point cloud and successively a high-resolution Digital Surface Models (DSM) of a beach dune system in Marina di Ravenna (Italy). The quality of the elevation dataset produced by the UAV-SfM was initially evaluated by comparison with point cloud generated by a Terrestrial Laser Scanning (TLS) surveys. Such a comparison served to highlight an average difference in the vertical values of 0.05 m (RMS = 0.19 m). However, although the points cloud comparison is the best approach to investigate the absolute or relative correspondence between UAV and TLS methods, the assessment of geomorphic features is usually based on multi-temporal surfaces analysis, where an interpolation process is required. DSMs were therefore generated from UAV and TLS points clouds and vertical absolute accuracies assessed by comparison with a Global Navigation Satellite System (GNSS) survey. The vertical comparison of UAV and TLS DSMs with respect to GNSS measurements pointed out an average distance at cm-level (RMS = 0.011 m). The successive point by point direct comparison between UAV and TLS elevations show a very small average distance, 0.015 m, with RMS = 0.220 m. Larger values are encountered in areas where sudden changes in topography are present. The UAV-based approach was demonstrated to be a straightforward one and accuracy of the vertical dataset was comparable with results obtained by TLS technology.

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.

Vegetation structure is a crucial component of habitat suitability for wildlife, but methods traditionally used to quantify it can be costly, subjective, or difficult to replicate. There have been substantial advancements, and growing interest, in the use of terrestrial laser scanning (TLS) methods to measure fine-scale vegetation attributes in ecological research, but limited opportunities for ecologists and practitioners to learn how to incorporate these into applied research. Here, we provide a starting point for those who want to incorporate TLS methods into ecological research and monitoring, using a case study from a temperate forest in South-Eastern Australia. We scanned 24 sites at different stages of post-fire recovery as part of a larger project measuring the impact of fire on forest dwelling bats, using a FARO Focus 3DS. Using the data from these scans, we present an example workflow with accompanying R code to demonstrate how to process the point clouds and extract a range of vegetation structure metrics relevant to habitat structure for wildlife, including vegetation height, cover, density, and heterogeneity. We discuss how three-dimensional data obtained through TLS can be valuable to wildlife studies and opens up the potential to explore advanced ecological and conservation questions around how vegetation structure influences wildlife behaviours, distribution patterns, and responses to disturbance.

3차원 실내공간정보에 구축 시 경제성, 효율성 및 정확도 향상을 위한 지상레이저스캐너의 활용이 주목을 받고 있다. 그러나 실내공간정보 구축에 있어 지상레이저스캐너 관측방식과 기존 측량방식 방식에 대한 비교 연구는 미비한 실정이다. 본 연구에서는 설계도면 갱신 및 3차원 실내 모델링에 AMCW 방식 및 direct TOF 방식의 지상레이저스캐너와 토탈스테이션의 작업시간 및 위치정확도를 비교하여 지상레이저스캐너의 효율성과 경제성을 제시하였다. 비교결과, AMCW 방식은 direct TOF 방식에 비해 시간효율성이 뛰어났으며 두 관측값 사이의 RMSE는 <TEX>${\pm}1mm$</TEX> 수준으로 나타났다. 또한 지상레이저스캐닝 방식은 토탈스테이션 관측방식에 비해 2배 이상의 시간효율성을 보였으며 두 관측값 사이의 RMSE는 <TEX>${\pm}3.4cm$</TEX>로 나타났다. 제시된 지상레이저스캐너를 이용한 3차원 실내모델링의 경제성과 효율성을 바탕으로 향후 3차원 실내공간 정보 구축에 지상레이저스캐닝 방식이 효과적으로 활용될 수 있을 것으로 기대된다. According to the increasing demand for 3D indoor spatial information, the utilization of a terrestrial laser scanner comes to the fore. However, the research for the comparison between a terrestrial laser scanning method and a traditional surveying method is insufficient. The paper evaluated the time-efficiency and the locational accuracy of an AMCW type and a direct TOF type of terrestrial laser scanning methods in comparison with the observation using a total station. As a result, an AMCW type showed higher time-efficiency than a direct TOF type and the RMSE between the two types of data was <TEX>${\pm}1mm$</TEX>. Moreover, the terrestrial laser scanning method showed twice higher time-efficiency than the observation using a total station and the RMSE between the two data was <TEX>${\pm}3.4cm$</TEX>. The results indicate that the terrestrial laser scanning method has better profitability and performance for 3D indoor modeling than the traditional survey using a total station. In the future, a terrestrial laser scanner can be efficiently utilized in the construction of 3D indoor spatial information.

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.

Ground-based LiDAR also known as Terrestrial Laser Scanning (TLS) technology is an active remote sensing imaging method said to be one of the latest advances and innovations for plant phenotyping. Basal Stem Rot (BSR) is the most destructive disease of oil palm in Malaysia that is caused by white-rot fungus Ganoderma boninense, the symptoms of which include flattening and hanging-down of the canopy, shorter leaves, wilting green fronds and smaller crown size. Therefore, until now there is no critical investigation on the characterisation of canopy architecture related to this disease using TLS method was carried out. This study proposed a novel technique of BSR classification at the oil palm canopy analysis using the point clouds data taken from the TLS. A total of 40 samples of oil palm trees at the age of nine-years-old were selected and 10 trees for each health level were randomly taken from the same plot. The trees were categorised into four health levels - T0, T1, T2 and T3, which represents the healthy, mildly infected, moderately infected and severely infected, respectively. The TLS scanner was mounted at a height of 1 m and each palm was scanned at four scan positions around the tree to get a full 3D image. Five parameters were analysed: S200 (canopy strata at 200 cm from the top), S850 (canopy strata at 850 cm from the top), crown pixel (number of pixels inside the crown), frond angle (degree of angle between fronds) and frond number. The results taken from statistical analysis revealed that frond number was the best single parameter to detect BSR disease as early as T1. In classification models, a linear model with a combination of parameters, ABD – A (frond number), B (frond angle) and D (S200), delivered the highest average accuracy for classification of healthy-unhealthy trees with an accuracy of 86.67 per cent. It also can classify the four severity levels of infection with an accuracy of 80 per cent. This model performed better when compared to the severity classification using frond number. The novelty of this research is therefore on the development of new approach to detect and classify BSR using point clouds data of TLS.

A forest inventory is often carried out using airborne laser data combined with ground measured reference data. Traditionally, the ground reference data have been collected manually with a caliper combined with land surveying equipment. During recent years, studies have shown that the caliper can be replaced by equipment and methods that capture the ground reference data more efficiently. In this study, we compare three different ground based laser measurement methods: terrestrial laser scanner, handheld laser scanner and a backpack laser scanner. All methods are compared with traditional measurements. The study area is located in southeastern Norway and divided into seven different locations with different terrain morphological characteristics and tree density. The main tree species are boreal, dominated by Norway spruce and Scots pine. To compare the different methods, we analyze the estimated tree stem diameter, tree position and data capture efficiency. The backpack laser scanning method captures the data in one operation. For this method, the estimated diameter at breast height has the smallest mean differences of 0.1 cm, the smallest root mean square error of 2.2 cm and the highest number of detected trees with 87.5%, compared to the handheld laser scanner method and the terrestrial laser scanning method. We conclude that the backpack laser scanner method has the most efficient data capture and can detect the largest number of trees.

Sediment Barriers (SBs) are crucial for effective erosion control, and understanding their capacities and limitations is essential for environmental protection. This study compares the accuracy and effectiveness of Terrestrial Laser Scanning (TLS) and Robotic Total Station (RTS) techniques for quantifying sediment retention in SBs. To achieve this, erosion tests were conducted in a full-scale testing apparatus with TLS and RTS methods to collect morphological data of sediment retention surfaces before and after each experiment. The acquired datasets were processed and integrated into a Building Information Modeling (BIM) platform to create Digital Elevation Models (DEMs). These were then used to calculate the volume of accumulated sediment upstream of the SB system. The results indicated that TLS and RTS techniques could effectively measure sediment retention in a full-scale testing environment. However, TLS proved to be more accurate, exhibiting a standard deviation of 0.41 ft3 in contrast to 1.94 ft3 for RTS and more efficient, requiring approximately 15% to 50% less time per test than RTS. The main conclusions of this study highlight the benefits of using TLS over RTS for sediment retention measurement and provide valuable insights for improving erosion control strategies and sediment barrier design.