Reassessing Megalithic Spatial Densities in Southwestern Iberia Through Airborne Laser Scanning‐Based Landscape Analysis

Monitoring gully change: A comparison of airborne and terrestrial laser scanning using a case study from Aratula, Queensland

Enhancing wall-to-wall forest structure mapping through detailed co-registration of airborne and terrestrial laser scanning data in Mediterranean forests

Evaluating airborne, mobile and terrestrial laser scanning for urban tree inventories: A case study in Ghent, Belgium

Multi-temporal airborne laser scanning (ALS) surveys have become a prime consideration for detecting landslide movements and evaluating landslide risk in mountain areas. The minimum elevation change (or detectability) that can be detected by repeated ALS surveys has become a critical threshold for landslide researchers and engineers to decide if ALS is a capable tool for detecting targeted landslides and arranging the minimum time span between two scans if ALS is a choice. The National Center for Airborne Laser Mapping (NCALM) at the University of Houston conducted three repeated ALS surveys at the Slumgullion landslide site in Colorado, U.S. over one week in July of 2015. These repeated ALS surveys provide valuable datasets for evaluating the vertical detectability of multi-temporal ALS surveys in a typical mountain area. According to this study, the difference of digital elevation models (DDEM) derived from ALS has the ability of detecting a minimum elevation change of 5 cm over flatter and moderately rugged terrain areas (slope < 20 degrees) and a minimum of a 10-cm elevation change over rugged terrain areas (20 degrees < slope < 40 degrees). However, the DDEM values over highly rugged terrain areas (slope > 40 degrees), such as cliff and landslide scarps, should be interpolated with caution. Global Navigation Satellite Systems (GNSS) and Terrestrial Laser Scanning (TLS) surveys were also performed at the middle portion of the landslide area for assessing the accuracy of ALS datasets. The accuracy of ALS varies from approximately one decimeter (~10 cm) to one foot (~30 cm) depending on the roughness of terrain surface and vegetation coverage (point density). The detectability and accuracy estimates of ALS measurements obtained from the case study could be used as a reference for estimating the performance of modern ALS in mountain areas with similar topography and vegetation coverage.

Repeated airborne laser scanning (ALS) measurements during leaf-on and leaf-off phenophases were studied. A 15 km × 15 km test site located in northern Estonia was used that included a reference set of stands, and 870 stands with thinning carried out before, between, and after two ALS flights. The decrease in ALS-based canopy cover estimate (CC ALS) caused by thinning was similar for the leaf-off and leaf-on phenophases, and for different height thresholds. The point cloud height percentile (H Px) values increased in almost all thinned stands, and the increase was present for the leaf-off and leaf-on phenophases. ALS point cloud metrics (skewness, kurtosis, mode, and canopy relief ratio) showed no response to thinning (p-value >0.05). Stand-dominating species had no significant influence on H Px increment or CC ALS change using the leaf-on data (p-value >0.05). The minimum height filter for pulse return selection had a substantial influence on H Px increment in stands thinned between the two ALS measurements. Ground points are usually excluded from H Px calculation, but for stand-level analyses, their inclusion can provide additional information.

Remotely sensed data and imagery have revolutionized the way we understand archaeological sites and landscapes. LiDAR / airborne laser scanning (ALS) has been used to capture the often subtle topographic remnants of previously undiscovered sites even in intensely studied landscapes, and is rapidly becoming a key technology in survey projects with large extents and/or difficult terrain. This paper examines the practical application of this technology to archaeological heritage management, with special attention given to how ALS can support the World Heritage List nomination process and management of WHS archaeological sites and landscapes. It presents a number of examples from published ALS studies alongside case studies from projects undertaken by the authors at Cultural Site Research and Management and the Cultural Site Research and Management Foundation, Baltimore, Maryland, USA. The paper opens with a review of how ALS has been used at established World Heritage Sites, focusing on the Archaeological Ensemble of the Bend in the Boyne, Ireland, and the Angkor Archaeological Site in Cambodia. ALS applications for site prospection and demarcation, and viewshed analysis is explored in this section. Following this, we explore how ALS has been used to support two recent applications: the successfully nominated Monumental Earthworks at Poverty Point, USA and the recently nominated Orheiul Vechi Archaeological Landscape in Moldova. We propose that the detail offered by ALS data greatly strengthens nomination dossiers by emphasizing the outstanding universal value of sites, highlighting significant features and providing greater context to wider landscapes, and is particularly efficacious in delineating site boundaries for legal protection and long-term management. Finally, we conclude with a look at some of the practical considerations involved in the use of ALS, including access and training.

Resolution of satellite altimetry derived sea surface heights (SSH) is relatively low, whereas near coastal areas the data have poor accuracy. For monitoring SSH regionally, Airborne Laser Scanning (ALS) in conjunction with kinematic GPS-positioning can be a more accurate and high-resolution alternative. A case study was carried out at the southern shores of Gulf of Finland, the Baltic Sea. An ALS profile flown at an altitude of ~400 m was used for SSH determination. Two different algorithms for ALS trajectory calculations were compared and clear systematic discrepancies between the two were determined. Also, significant variations in backscattering of ALS pulses yield large data gaps even with near ideal flight conditions. The causes for this phenomena were analyzed and a possible explanation given. The accuracy of the sea level corrected SSH results was validated with a regional geoid and sea surface models. The ALS derived SSH values agree within 2 cm (in terms of standard deviation) with the geoid model.

This study investigates the potential of unmanned aerial vehicles (UAVs) to measure and monitor structural properties of forests. Two remote sensing techniques, airborne laser scanning (ALS) and structure from motion (SfM) were tested to capture three-dimensional structural information from a small multi-rotor UAV platform. A case study is presented through the analysis of data collected from a 30 × 50 m plot in a dry sclerophyll eucalypt forest with a spatially varying canopy cover. The study provides an insight into the capabilities of both technologies for assessing absolute terrain height, the horizontal and vertical distribution of forest canopy elements, and information related to individual trees. Results indicate that both techniques are capable of providing information that can be used to describe the terrain surface and canopy properties in areas of relatively low canopy closure. However, the SfM photogrammetric technique underperformed ALS in capturing the terrain surface under increasingly denser canopy cover, resulting in point density of less than 1 ground point per m2 and mean difference from ALS terrain surface of 0.12 m. This shortcoming caused errors that were propagated into the estimation of canopy properties, including the individual tree height (root mean square error of 0.92 m for ALS and 1.30 m for SfM). Differences were also seen in the estimates of canopy cover derived from the SfM (50%) and ALS (63%) pointclouds. Although ALS is capable of providing more accurate estimates of the vertical structure of forests across the larger range of canopy densities found in this study, SfM was still found to be an adequate low-cost alternative for surveying of forest stands.

We review the research related to the application of inventory techniques utilizing airborne laser scanning (ALS) in intensively managed forest plantations. The single tree detection and area based methods originally developed in more complex forest types were found to be no less effective in plantation forests for the estimation of important stand parameters such as stocking, height, basal area, volume and leaf area. Further accuracy gains have been achieved by leveraging ancillary information commonly available in plantation databases, such as plantation age, planting distance and genetics of planting stock. A case study is presented describing a site productivity inventory system implemented in South Australian Pinus radiata plantations. It demonstrates that ALS based solutions can be effectively introduced in existing resource information systems without disrupting information continuity and consistency, while achieving accuracy and cost efficiencies. It is concluded that airborne (and terrestrial) laser scanning based inventories are an effective option for forest plantations. The spatially explicit nature of ALS based information can support intensive site specific management and can assist in optimizing recovery of the value inherent in trees and stands.KeywordsPlantation ForestSite QualityEucalyptus PlantationTerrestrial Laser ScanningAirborne Laser ScanningThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Ground-dwelling macrolichens dominate the forest floor of mature upland pine stands in the boreal forest. Understanding patterns of lichen abundance, as well as environmental characteristics associated with lichen growth, is key to managing lichens as a forage resource for threatened woodland caribou (Rangifer tarandus caribou). The spectral signature of light-coloured lichen distinguishes it from green vegetation, potentially allowing for mapping of lichen abundance using multi-spectral imagery, while canopy structure measured from airborne laser scanning (ALS) of forest openings can indirectly map lichen habitat. Here, we test the use of high-resolution KOMPSAT (Korea Multi-Purpose Satellite-3) imagery (280 cm resolution) and forest structural characteristics derived from ALS to predict lichen biomass in an upland jack pine forest in Northeastern Alberta, Canada. We quantified in the field lichen abundance (cover and biomass) in mature jack pine stands across low, moderate, and high canopy cover. We then used generalized linear models to relate lichen abundance to spectral data from KOMPSAT and structural metrics from ALS. Model selection suggested that lichen abundance was best predicted by canopy cover (ALS points > 1.37 m) and to a lesser extent blue spectral data from KOMPSAT. Lichen biomass was low at plots with high canopy cover (98.96 g/m2), while almost doubling for plots with low canopy cover (186.30 g/m2). Overall the model fit predicting lichen biomass was good (R2 c = 0.35), with maps predicting lichen biomass from spectral and structural data illustrating strong spatial variations. High-resolution mapping of ground lichen can provide information on lichen abundance that can be of value for management of forage resources for woodland caribou. We suggest that this approach could be used to map lichen biomass for other regions.

Abstract. Digital terrain models form the basis for distributed hydrologic models as well as for two-dimensional hydraulic river flood models. The technique used for generating high accuracy digital terrain models has shifted from stereoscopic aerial-photography to airborne laser scanning during the last years. Since the disastrous floods 2002 in Austria, large airborne laser-scanning flight campaigns have been carried out for several river basins. Additionally to the topographic information, laser scanner data offer also the possibility to estimate object heights (vegetation, buildings). Detailed land cover maps can be derived in conjunction with the complementary information provided by high-resolution colour-infrared orthophotos. As already shown in several studies, the potential of airborne laser scanning to provide data for hydrologic/hydraulic applications is high. These studies were mostly constraint to small test sites. To overcome this spatial limitation, the current paper summarises the experiences to process airborne laser scanner data for large mountainous regions, thereby demonstrating the applicability of this technique in real-world hydrological applications.

<jats:p>Within the last years terrestrial and airborne laser scanning has become a powerful technique for fast and efficient three-dimensional data acquisition of different kinds of objects. Airborne laser system (LiDAR) collects accurate georeferenced data of extremely large areas very quickly while the terrestrial laser scanner produces dense and geometrically accurate data. The combination of these two segments of laser scanning provides different areas of application. One of the applications is in the process of reconstruction of objects. Objects recorded with laser scanning technology and transferred into the final model represent the basis for building an object as it was original. In this paper, there will be shown two case studies based on usage of airborne and terrestrial laser scanning and processing of the data collected by them.</jats:p>

The paper presents the results from the study concerning the application of airborne laser scanning (ALS) data and derived raster products like the digital surface model (DSM) and the digital terrain model (DTM) for the assessment of the degree of change of the land use based on the forest succession example. Simultaneously, an automated method of ALS data processing was developed based on the normalized (nDSM) and cadastral GIS information. Besides delivering precise information on forest succession, ALS technology is an excellent tool for time-changes spatial analyses. Usage of the ALS data can support the image interpretation process decreasing the subjectivity of the operator. In parallel, a manual vectorization and object classification (object-based image analysis—OBIA) were performed; both based on aerial orthophoto and ALS data. By using integrated ALS point clouds and digital aerial images, one can obtain fast OBIA processing and the determination of areas where the land cover has changed. The Milicz District (central west part of Poland) was chosen as the test site where ALS was to be performed in 2007, together with the digital aerial photos (Vexcel camera; pixel 0.15 m; CIR). The aerial photos were then processed to a CIR orthophoto. The area of study consisted of 68 private parcels (some of them were abandoned; 68.57 ha; scanned cadastral maps from the local survey office; land use information) in the direct neighbourhood of the State Forest, on which a forest succession could often be observed. The operator vectorized forest (trees and shrubs) succession areas on the 2D CIR orthophoto. They were then compared with the results from the OBIA and GIS analysis, based on the normalized digital surface model. The results showed that areas with high vegetation cover were three times larger than the official land cover database (cadastral maps).

The effects of field plot size on model-assisted estimation of aboveground biomass change using multitemporal interferometric SAR and airborne laser scanning data

Abstract. Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean diameter and stem volume. When stratification was performed based on ALS acquisition settings and geographical criteria, satisfactory prediction models were obtained for volume (R2 = 0.61 with a root mean square error of 47 %) and basal area (respectively 0.51 and 45 %) while height variables had an error lower than 19%. This case study shows that the use of nationwide ALS and field datasets for forest resources mapping is cost efficient, but additional investigations are required to handle the limitations of the input data and optimize the accuracy.