LiDAR is a useful technology for gathering point cloud data from its environment and has been adapted to many applications. We use a cost-efficient LiDAR system attached to a moving object to estimate the location of the moving object using reference...
This paper represents the results of ten years of monitoring using satellite imagery and aerial reconnaissance, followed by in-depth analysis utilizing LiDAR data and geomagnetic prospection techniques of the first two Neolithic rondels detected in C...
The aim of this paper is to highlight how the employment of Light Detection and Ranging (LiDAR) technique can enhance greatly the performance and reliability of many monitoring systems applied to the Earth Observation (EO) and Environmental Monitorin...
Airborne Light Detection and Ranging (LiDAR) topographic data provide highly accurate digital terrain information, which is used widely in applications like creating flood insurance rate maps, forest and tree studies, coastal change mapping, soil and...
Delineating canopy gaps and quantifying gap characteristics (e.g., size, shape, and dynamics) are essential for understanding regeneration dynamics and understory species diversity in structurally complex forests. Both high spatial resolution optical...
LiDAR technology is rapidly evolving as various new systems emerge, providing unprecedented data to characterize forest vertical structure. Data from different LiDAR systems present distinct characteristics owing to a combined effect of sensor specif...
Studies have shown that vehicle trajectory data are effective for calibrating microsimulation models. Light Detection and Ranging (LiDAR) technology offers high-resolution 3D data, allowing for detailed mapping of the surrounding environment, includi...
Most of the cultural sites hidden under dense vegetation in the mountains of China have been destroyed. In this paper, we present a microtopographic feature analysis (MFA)-based Light Detection and Ranging (LiDAR) data processing approach and an arch...
Currently, the worsening impacts of urbanizations have been impelled to the importance of monitoring and management of existing urban trees, securing sustainable use of the available green spaces. Urban tree species identification and evaluation of t...
This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on...
Urban green spaces are known to provide ample benefits to human society and hence play a vital role in safeguarding the quality of life in our cities. In order to optimize the design and management of green spaces with regard to the provisioning of t...
A data-driven method for describing the benthic cover type based on full-waveform bathymetric LiDAR data analysis is presented. The waveform of the bathymetric LiDAR return pulse is first modeled as a sum of three functions: a Gaussian pulse represen...
Due to the increasing scarcity of fossil fuels and the upwards trend in energy costs over time, many countries—especially in Europe—have begun to modify their energy policies aiming to increase that percentage obtained from renewable energies. The EA...
Precise maintenance is vital for ensuring the safety of tunnel structures; however, traditional visual inspections are subjective and hazardous. Digital technologies such as LiDAR and imaging offer promising alternatives, but each has complementary l...
The fusion of the hyperspectral image (HSI) and the light detecting and ranging (LiDAR) data has a wide range of applications. This paper proposes a novel feature fusion method for urban area classification, namely the relative total variation struct...
The shoreline and seabed topography are key components of the coastal zone and are essential for hydrographic surveys, shoreline process modelling, and coastal infrastructure management. The development of unmanned aerial vehicles (UAVs) and optoelec...
Fatalities and serious injuries still represent a significant portion of run-off-the-road (ROR) collisions on highways in North America. In order to address this issue and design safer and more forgiving roadside areas, more empirical evidence is req...
As drone-based Light Detection and Ranging (LiDAR) becomes more accessible, it presents new opportunities for automated, geometry-driven classification. This study investigates the use of LiDAR point cloud data and Machine Learning (ML) to classify r...
Spectral confusion among land cover classes is quite common, let alone in a complex and heterogenous system like the semi-arid Mediterranean environment; thus, employing new developments in remote sensing, such as multispectral imagery (MSI) captured...
Gully erosion is one of the main processes of soil degradation, representing 50%–90% of total erosion at basin scales. Thus, its precise characterization has received growing attention in recent years. Geomatics techniques, mainly photogrammetr...
Estimating forest canopy height from large-footprint satellite LiDAR waveforms is challenging given the complex interaction between LiDAR waveforms, terrain, and vegetation, especially in dense tropical and equatorial forests. In this study, canopy h...
Salt marshes are changing due to natural and anthropogenic stressors such as sea level rise, nutrient enrichment, herbivory, storm surge, and coastal development. This study analyzes salt marsh change at Fire Island National Seashore (FIIS), a nation...
The achievements made in genomic technology in recent decades are yet to be matched by fast and accurate crop phenotyping methods. Such crop phenotyping methods are required for crop improvement efforts to meet expected demand for food and fibre in t...
Machine Learning (ML) techniques are now being used very successfully in predicting and supporting decisions in multiple areas such as environmental issues and land management. These techniques have also provided promising results in the field of nat...
This manuscript focuses on a quality assessment of DJI’s new sensors: the Zenmuse L1 and P1, which are LiDAR and photographic payload sensors, respectively, for UAVs/UASs. In particular, metric and statistical analyses aim to evaluate the data...
A key feature for urban digital twins (DTs) is an automatically generated detailed 3D representation of the built and unbuilt environment from aerial imagery, footprints, LiDAR, or a fusion of these. Such 3D models have applications in architecture,...
For identification of forested landslides, most studies focus on knowledge-based and pixel-based analysis (PBA) of LiDar data, while few studies have examined (semi-) automated methods and object-based image analysis (OBIA). Moreover, most of them ar...
Mapping and quantifying forest inventories are critical for the management and development of forests for natural resource conservation and for the evaluation of the aboveground forest biomass (AGFB) technically available for bioenergy production. Th...
The United States Forest Service Forest Inventory and Analysis (FIA) Program provides a diverse selection of data used to assess the status of the nation’s forests using sample locations dispersed throughout the country. Airborne laser scanning (ALS)...
Pavement roughness serves as a crucial indicator for evaluating road performance. However, traditional measurement methods, such as laser detection vehicles, are limited to providing roughness values for a single profile, failing to capture the overa...
Monitoring and modeling of coastal vegetation and wetland systems are considered major challenges, especially when considering environmental response to hazards, disturbances, and management activities. Remote sensing applications can provide alterna...
This study introduces a methodology for the improvement of the visibility of archaeological features using an open-source probabilistic machine learning framework applied to UAV LiDAR data from the Torre Castiglione site in Apulia, Italy. By leveragi...
Urbanization transforms simple two-dimensional natural spaces into complex three-dimensional (3D) artificial spaces through intense land use. Hence, urbanization continuously transforms vertical urban settings and the corresponding sky view area. As...
This study proposes a novel hybrid simulation technique for analyzing structural deformation and stress using light detection and ranging (LiDAR)-scanned point cloud data (PCD) and polynomial regression processing. The method estimates the edge and c...
Occupational Health and Safety (OHS) in agriculture is a critical concern worldwide, with self-propelled machinery accidents, particularly tip/roll-overs, being a leading cause of injuries and fatalities. In such a context, while great attention has...
This paper proposes an automated framework that utilizes Light Detection and Ranging (LiDAR) point cloud data to map and detect road obstacles that impact drivers’ field of view at urban intersections. The framework facilitates the simulation of a dr...
Hyperspectral LiDAR (HSL) is a promising active detection technique for underwater positioning and remote sensing, enabling the simultaneous acquisition of three-dimensional topographic and spectral information of underwater targets. This study prese...
This study aims to segment individual tree structures (stem, crown, and ground) from terrestrial LiDAR-derived point cloud data (PCD) and to compare the segmentation accuracy between two models: XGBoost (machine learning) and PointNet++ (deep learnin...
When classifying objects in 3D LiDAR data, it is important to use efficient collection methods and processing algorithms. This paper considers the resolution needed to classify 3D objects accurately and discusses how this resolution is accomplished f...
Light detection and ranging (LiDAR) sensors are critical for autonomous vehicles that require unparalleled depth sensing. However, traditional LiDAR designs face significant challenges, including high costs and bulky configurations, limiting scalabil...
Building change detection is useful for land management, disaster assessment, illegal building identification, urban growth monitoring, and geographic information database updating. This study proposes an automatic method that applies object-based an...
The optimization of forest management in roadsides is a necessary task in terms of wildfire prevention in order to mitigate their effects. Forest fire risk assessment identifies high-risk locations, while providing a decision-making support about veg...
Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for revolutionizing data analysis and applications in many domains of Earth sciences. This review paper synthesizes the existing literature on AI applicatio...
We combined datasets from multiple research projects and remote sensing technologies to evaluate conservation conditions at La Fortaleza de Kuelap, a pre-Hispanic site in Peru that suffered significant damage under heavy seasonal rains in April 2022....
The combination of LiDAR with other technologies for numerisation is increasingly applied in the field of building, design, and geoscience, as it often brings time and cost advantages in 3D data survey processes. In this paper, the reconstruction of...
Updating the most recent set of point cloud data is critical in autonomous driving environments. However, existing systems for point cloud data management often fail to ensure real-time updates or encounter situations in which data cannot be effectiv...
Mobile robots are equipped with various sensors to perform object detection, localization, and navigation. Among these sensors, LiDAR (light detection and ranging) is the most widely used sensor for environment map creation. However, LiDAR-based loca...
The ability to extract flood hazard settings in highly vulnerable areas like populated floodplains by using new computer algorithms and hydraulic modeling software is an important aspect of any flood mitigation efforts. In this framework, the 1D/2D h...
Cliff coasts are dynamic environments that can retreat very quickly. However, the short-term changes and factors contributing to cliff coast erosion have not received as much attention as dune coasts. In this study, three soft-cliff systems in the so...
Solar maps are becoming a popular resource and are available via the web to help plan investments for the benefits of renewable energy. These maps are especially useful when the results have high accuracy. LiDAR technology currently offers high-resol...
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