Search Results (513)

In recent years, the growth of digital data has been unimaginable. This also applies to geospatial data. One of the largest data types is LiDAR point clouds. Their large volumes on disk, both at the acquisition and processing stages, and in the final versions translate into a high demand for disk space and therefore electricity. It is therefore obvious that in order to reduce energy consumption, lower the carbon footprint of the activity and sensitize sustainability in the digitization of the industry, lossless compression of the aforementioned datasets is a good solution. In this article, a new format for point clouds—3DL—is presented, the effectiveness of which is compared with 21 available formats that can contain LiDAR data. A total of 404 processes were carried out to validate the 3DL file format. The validation was based on four LiDAR point clouds stored in LAS files: two files derived from ALS (airborne laser scanning), one in the local coordinate system and the other in PL-2000; and two obtained by TLS (terrestrial laser scanning), also with the same georeferencing (local and national PL-2000). During research, each LAS file was saved 101 different ways in 22 different formats, and the results were then compared in several ways (according to the coordinate system, ALS and TLS data, both types of data within a single coordinate system and the time of processing). The validated solution (3DL) achieved CR (compression rate) results of around 32% for ALS data and around 42% for TLS data, while the best solutions reached 15% for ALS and 34% for TLS. On the other hand, the worst method compressed the file up to 424.92% (ALS_PL2000). This significant reduction in file size contributes to a significant reduction in energy consumption during the storage of LiDAR point clouds, their transmission over the internet and/or during copy/transfer. For all solutions, rankings were developed according to CR and CT (compression time) parameters. Full article

In Republic of Korea, the digital transformation of forest data has emerged as a critical priority at the governmental level. To support this effort, numerous case studies have been conducted to collect and analyze forest data. This study evaluated the accuracy of forest resource assessment methods using terrestrial laser scanning (TLS) and backpack personal laser scanning (BPLS) under Leaf-on and Leaf-off conditions in the Gari Mountain Forest Management Complex, Hongcheon, Republic of Korea. The research was conducted across six sample plots representing low, medium, and high stand densities, dominated by Larix kaempferi and Pinus koraiensis. Conventional field survey methods and LiDAR technologies were used to compare key forest attributes such as tree height and volume. The results revealed that Leaf-off LiDAR data exhibited higher accuracy in capturing tree height and canopy structures, particularly in high-density plots. In contrast, during the Leaf-on season, measurements of understory vegetation and lower canopy were hindered by foliage obstruction, reducing precision. Seasonal differences significantly impacted LiDAR measurement accuracy, with Leaf-off data providing a clearer and more reliable representation of forest structures. This study underscores the necessity of considering seasonal conditions to improve the accuracy of LiDAR-derived metrics. It offers valuable insights for enhancing forest inventory practices and advancing the application of remote sensing technologies in forest management. Full article

The accurate estimation of Digital Elevation Models (DEMs) derived from satellite data is critical for numerous environmental applications. This study evaluates the accuracy and reliability of two satellite-derived elevation models, the ALOS World 3D and SRTM DEMs, specifically for their application in hydrological modeling. A comparative analysis with Terrestrial Laser Scanning (TLS) measurements assessed the agreement between these datasets. Multiple linear regression models were utilized to evaluate the relationships between the datasets and provide detailed insights into their accuracy and biases. The results indicate significant correlations between satellite DEMs and TLS measurements, with adjusted R-square values of 0.8478 for ALOS and 0.955 for the SRTM. To quantify the average difference, root mean square error (RMSE) values were calculated as 10.43 m for ALOS and 5.65 m for the SRTM. Additionally, slope and aspect analyses were performed to highlight terrain characteristics across the DEMs. Slope analysis showed a statistically significant negative correlation between SRTM and TLS slopes (R² = 0.16, p < 4.47 × 10⁻¹⁰ indicating a weak relationship, while no significant correlation was observed between ALOS and TLS slopes. Aspect analysis showed significant positive correlations for both ALOS and the SRTM with TLS aspect, capturing 30.21% of the variance. These findings demonstrate the accuracy of satellite-derived elevation models in representing terrain features relative to high-resolution terrestrial data. Full article

The surface anomaly is a common defect for structures that resist lateral stresses, such as retaining walls. The accurate detection of an anomaly using contactless techniques, such as the Terrestrial Laser Scanner (TLS), is significant for the reliable structural assessment. The influence of the scanning geometry on the accuracy of the TLS point-clouds was investigated in previous studies; however, a deeper analysis is needed to investigate their impact in the context of structural health monitoring. This paper aims to empirically assess the performance of the TLS in detecting surface anomalies, with respect to the scanning distance and angle of incidence in two cases: (i) when both the reference and deformed clouds are taken from the same scanning position, and (ii) the scans are from different positions. Furthermore, the paper examines the accuracy of estimating the depth of the anomaly using three cloud comparison techniques (i.e., C2C, C2M, and M3C2 methods). The results show that the TLS is capable of detecting the surface anomaly for distances between 2 and 30 m and angles of incidence between 90° and 30°, with a tolerance of within a few millimeters. This is achieved even for the case where scans from different locations (i.e., angles and distances) are applied. Full article

This study aims to address the challenges associated with rockfall assessment and monitoring, focusing on the coastal cliffs of “Navagio Shipwreck Beach” in Zakynthos. A complete time-series analysis was conducted using state-of-the-art methodologies including a 2020 survey using unmanned aerial systems (UASs) and two subsequent surveys, incorporating terrestrial laser scanning (TLS) and UAS survey techniques in 2023. Achieving high precision and accuracy in georeferencing involving direct georeferencing, the utilization of pseudo ground control points (pGCPs), and integrating post-processing kinematics (PPK) with global navigation satellite system (GNSS) permanent stations’ RINEX data is necessary for co-registering the multitemporal models effectively. For the change detection analysis, UAS surveys were utilized, employing the multiscale model-to-model cloud comparison (M3C2) algorithm, while TLS data were used in a validation methodology due to their very high-resolution model. The synergy of these advanced technologies and methodologies offers a comprehensive understanding of rockfall dynamics, aiding in effective assessment and monitoring strategies for coastal cliffs prone to rockfall risk. Full article

Terrestrial laser scanning (TLS) provides highly detailed 3D information of forest environments but is limited to small spatial scales, as data collection is time consuming compared to other remote sensing techniques. Furthermore, TLS data collection is heavily dependent on wind conditions, as the movement of trees negatively impacts the acquired data. Hardware advancements resulting in faster data acquisition times have the potential to be valuable in upscaling efforts but might impact overall data quality. In this study, we investigated the impact of the pulse repetition rate (PRR), or pulse frequency, which is the number of laser pulses emitted per second by the scanner. Increasing the PRR reduces the scan time required for a single scan but decreases the power (amplitude) of the emitted laser pulses commensurately. This trade-off could potentially impact the quality of the acquired data. We used a RIEGL VZ400i laser scanner to test the impact of different PRR settings on the point cloud quality and derived tree structural metrics from individual tree point clouds (diameter, tree height, crown projected area) as well as quantitative structure models (total branch length, tree volume). We investigated this impact across five field plots of different forest complexity and canopy density for three different PRR settings (300, 600 and 1200 kHz). The scan time for a single scan was 180, 90 and 45 s for 300, 600 and 1200 kHz, respectively. Differences among the raw acquired scans from different PRR replicates were largely removed by several necessary data processing steps, notably the removal of uncertain points with a low reflectance attribute. We found strong agreement between the individual tree structural metrics derived from each of the PRR replicates, independent of the forest complexity. This was the case for both point cloud-based metrics and those derived from quantitative structural models (QSMs). The results demonstrate that the PRR in high-end TLS instruments can be increased for data collection with negligible impact on a selection of derived structural metrics that are commonly used in the context of aboveground biomass estimation. Full article

The work developed aims to present an innovative methodology to execute the heritage conservation processes in a collaborative and interdisciplinary Building Information Modeling (BIM) project, with an effective management of the deterioration suffered over time, emphasizing the structures and coatings. The research begins with an architectural survey using terrestrial laser scanning (TLS) and terrestrial photogrammetry software, Structure from Motion (SfM), studying study the Duomo of Molfetta (Italy), a unique Romanesque architecture of Puglia (Italy). The methodological process is mainly aided by the precise semantic segmentation of global point clouds, a semi-automatic process assisted by classification algorithms implemented in the Cyclone 3DR post-processing software, which has allowed the classification of the unstructured information provided by the remote sensing equipment when identifying the architectural-structural systems of a building with high historical values. Subsequently, it was possible to develop an efficient Scan-to-HBIM workflow, where the Heritage BIM (HBIM) project has fulfilled the function of a database by incorporating and organizing all the information (graphic and non-graphic) to optimize the tasks of auscultation, identification, classification, and quantification and, in turn, facilitating the parametric modeling of unique structures and architectural elements. The results have shown great effectiveness in the processes of characterization of architectural heritage, focusing on the deformations and deterioration of the masonry in columns and pilasters. To make multidisciplinary conservation work more flexible, specific properties have been created for the identification and analysis of the degradation detected in the structures, with the HBIM project constituting a manager of the control and inspection activities. The restoration technician interacts with the determined 3D element to mark the “type decay”, managing the properties in the element’s own definition window. Interactive schemes have been defined that incorporate the items for the mapping of the elements, as well as particular properties of a conservation process (intervention, control, and maintenance). All listed parametric elements have links to be viewed in 2D and 3D views. Therefore, the procedure has facilitated the auscultation of the scanned element as it is semantically delimited, the parametric modeling of it, the analytical study of its materials and deterioration, and the association of intrinsic parameters so that they can be evaluated by all the intervening agents. But there are still some difficulties for the automatic interpretation of 3D point cloud data, related to specific systems of the historical architecture. In conclusion, human action and interpretation continues to be a fundamental pillar to achieve precise results in a heritage environment. Full article

Currently, many digital elevation models (DEMs) are derived from airborne LiDAR data acquisition flights. The vertical accuracy of both products has typically been evaluated using methods based on randomly sampled control points. However, due to the superficial nature of the DEM, logic suggests that it is more appropriate to use a superficial object as an evaluation and control element, that is, a “control surface” or “control patch”. Our approach proposes a method for obtaining each patch from a georeferenced point cloud (PC) measured with a terrestrial laser scanner (TLS). In order to reduce the dilution of precision due to very acute angles of incidence that occur between the terrain and the scanner′s rays when it is stationed on a conventional tripod, a system has been created that allows the scanner to be placed face down at a height of up to 7 m. Stationing the scanner at that height also has the advantage of reducing shadow areas in the presence of possible obstacles. In our experiment, the final result is an 18 m × 18 m PC patch which, after resampling, can be transformed into a high-density (10,000 points/m²) and high-quality (absolute positional uncertainty < 0.05 m) DEM patch, that is, with a regular mesh format. This DEM patch can be used as the ground truth to assess the surface accuracy of DEMs (DEM format) or airborne LiDAR data acquisition flights (PC format). Full article

Multi-platform geospatial data synergy is critical for complete and reliable surveys. This study investigates various methods for combining data from terrestrial laser scanning (TLS), orthophotos, databases of topographic objects, utility databases, tacheometry, and GNSS to assess and improve positioning accuracy and consistency of data in spatial databases. The study highlights the challenges and solutions regarding integrating various datasets to yield a complete and reliable geospatial database for building surveys and the construction and keeping of spatial databases. Input from diversified surveying technologies, such as TLS, GNSS, and orthophotos, offers detailed and precise data necessary to create and update accurate base maps and databases of topographic objects. A complete survey of a structure and its surroundings demonstrates how the synergistic application of diverse data sources helps improve the positioning accuracy and consistency of spatial databases. The results indicate the importance of multi-platform collaboration for high data quality standards in surveying, which is critical for effective planning and implementation of surveying projects. Full article

The automatic classification of tree species using terrestrial laser scanning (TLS) point clouds is key in forestry research. This study aims to develop a robust framework for tree species classification by integrating advanced feature extraction and machine learning techniques. Such a framework is of great significance for investigating and monitoring forest resources, sustainable forest management, and biodiversity research. To achieve this, point cloud data from 360 trees of four species were collected at the Northeastern Forestry University in Harbin City, Heilongjiang Province. Three types of tree point cloud features were extracted: tree structure, bark texture, and bark color. In addition, to repair and optimize the bark point cloud data, improved bark texture features were generated using the kriging interpolation method. These four features were combined into seven classification schemes and input into a random forest classifier, which was used to accurately classify the tree species. The results showed that the classification scheme combining tree structure features, improved bark texture features, and bark color features performed the best, with an overall classification accuracy of 94.17% and a kappa coefficient of 0.92. This study highlights the effectiveness of integrating point cloud data with machine learning algorithms for tree species classification and proposes a feature extraction and classification framework that significantly enhances classification accuracy. Full article

This paper reviews the measurement challenges associated with 3D scanning techniques in civil engineering, exploring the practical aspects of scanning buildings and complex surfaces through various case studies. The paper details the conventional use of Terrestrial Laser Scanning (TLS) for reconstructing the technical documentation of a hall. Then it describes an unconventional application of this technique for measuring an External Thermal Insulation Composite System (ETICS) wall, aimed at detecting microdeformations caused by environmental factors controlled within a climatic chamber. Subsequently, the measurements of the insulated wall were repeated using a metrological grade laser scanner. The numerical data were analysed with inspection engineering methods. The deformation maps and displacements of selected reference points were compared. This approach yielded qualitative and quantitative results. The qualitative results, i.e., the distribution of deformations in the form of a map, turned out to be consistent. However, quantitative results show a significant discrepancy in extreme cases of up to 70%. Full article

Detailed three-dimensional (3D) radiative transfer models (RTMs) enable a clear understanding of the interactions between light, biochemistry, and canopy structure, but they are rarely explicitly evaluated due to the availability of 3D canopy structure data, leading to a lack of knowledge on how canopy structure/leaf characteristics affect radiative transfer processes within forest ecosystems. In this study, the newly released 3D RTM Eradiate was extensively evaluated based on both virtual scenes reconstructed using the quantitative structure model (QSM) by adding leaves to point clouds generated from terrestrial laser scanning (TLS) data, and real scenes monitored by Sentinel-2 in a typical temperate deciduous forest. The effects of structural parameters on reflectance were investigated through sensitivity analysis, and the performance of the 3D model was compared with the 5-Scale and PROSAIL radiative transfer models. The results showed that the Eradiate-simulated reflectance achieved good agreement with the Sentinel-2 reflectance, especially in the visible and near-infrared spectral regions. Furthermore, the simulated reflectance, particularly in the blue and shortwave infrared spectral bands, was clearly shown to be influenced by canopy structure using the Eradiate model. This study demonstrated that the Eradiate RTM, based on the 3D explicit representation, is capable of providing accurate radiative transfer simulations in the temperate deciduous forest and hence provides a basis for understanding tree interactions and their effects on ecosystem structure and functions. Full article

Spatially referenced and geometrically accurate laser scanning is essential for the safety monitoring of an underground mine. However, the spatial inconsistency of point clouds collected by heterogeneous platforms presents challenges in achieving seamless fusion. In our study, the terrestrial and handheld laser scanning (TLS and HLS) point cloud registration method based on the coarse-to-fine strategy is proposed. Firstly, the point features (e.g., target spheres) are extracted from TLS and HLS point clouds to provide the coarse transform parameters. Then, the fine registration algorithm based on identical area extraction and improved 3D normal distribution transform (3D-NDT) is adopted, which achieves the datum unification of the TLS and HLS point cloud. Finally, the roughness is calculated to downsample the fusion point cloud. The proposed method has been successfully tested on two cases (simulated and real coal mine point cloud). Experimental results showed that the registration accuracy of the TLS and HLS point cloud is 4.3 cm for the simulated mine, which demonstrates the method can capture accurate and complete spatial information about underground mines. Full article

Terrestrial laser scanning (TLS) has become a vital tool in forestry for accurately measuring tree parameters, such as diameter at breast height (DBH). However, its application in Mexican forests remains underexplored. This study evaluates the performance of five two-dimensional DBH estimation algorithms (Nelder–Mead, least squares, Hough transform, RANSAC, and convex hull) within a temperate Mexican forest and explores their broader applicability across diverse ecosystems, using published point cloud data from various scanning devices. Results indicate that algorithm accuracy is influenced by local factors like point cloud density, occlusion, vegetation, and tree structure. In the Mexican study area, the Nelder–Mead algorithm achieved the highest accuracy (R² = 0.98, RMSE = 1.59 cm, MAPE = 6.12%), closely followed by least squares (R² = 0.98, RMSE = 1.67 cm, MAPE = 6.42%), with different outcomes in other sites. These findings advance DBH estimation methods by highlighting the importance of tailored algorithm selection and environmental considerations, thereby contributing to more accurate and efficient forest management across various landscapes. Full article

This article examines the potential of low-cost LiDAR technology for 3D modeling and assessment of the degradation of historic buildings, using a section of the Koszalin city walls in Poland as a case study. Traditional terrestrial laser scanning (TLS) offers high accuracy but is expensive. The study assessed whether more accessible LiDAR options, such as those integrated with mobile devices such as the Apple iPad Pro, can serve as viable alternatives. This study was conducted in two phases—first assessing measurement accuracy and then assessing degradation detection—using tools such as the FreeScan Combo scanner and the Z+F 5016 IMAGER TLS. The results show that, while low-cost LiDAR is suitable for small-scale documentation, its accuracy decreases for larger, complex structures compared to TLS. Despite these limitations, this study suggests that low-cost LiDAR can reduce costs and improve access to heritage conservation, although further development of mobile applications is recommended. Full article