High-resolution Laser Scanning Data Research Articles

Orthorectification of WorldView-3 Satellite Image Using Airborne Laser Scanning Data

Satellite images have been widely used to produce land use and land cover maps and to generate other thematic layers through image processing. However, images acquired by sensors onboard various satellite platforms are affected by a systematic sensor and platform-induced geometry errors, which introduce terrain distortions, especially when the sensor does not point directly at the nadir location of the sensor. To this extent, an automated processing chain of WorldView-3 image orthorectification is presented using rational polynomial coefficient (RPC) model and laser scanning data. The research is aimed at analyzing the effects of varying resolution of the digital surface model (DSM) derived from high-resolution laser scanning data, with a novel orthorectification model. The proposed method is validated on actual data in an urban environment with complex structures. This research suggests that a DSM of 0.31 m spatial resolution is optimum to achieve practical results (root-mean-square error = 0.69 m ) and decreasing the spatial resolution to 20 m leads to poor results (root-mean-square error = 7.17 ). Moreover, orthorectifying WorldView-3 images with freely available digital elevation models from Shuttle Radar Topography Mission (SRTM) (30 m) can result in an RMSE of 7.94 m without correcting the distortions in the building. This research can improve the understanding of appropriate image processing and improve the classification for feature extraction in urban areas.

Modelling of three-dimensional, diurnal light extinction in two contrasting forests

The three-dimensional (3D) distribution of light within forest ecosystems is a major driver for species competition, coexistence, forest ecosystem functioning, productivity, and diversity. However, accurate knowledge about the 3D distribution of light within the canopy is difficult to obtain. Recent advances in 3D forest reconstruction as well as the use of radiative transfer modelling provide new insights into spatio-temporal variations of light distribution within a forest canopy.We used high resolution laser scanning data coupled with in-situ leaf optical properties (LOP) measurements to parameterize the DART radiative transfer model for a temperate deciduous forest on the Laegern mountain, Switzerland, and for a tropical rain forest located in the Lambir Hills national park, Borneo, Malaysia. Combining terrestrial and unmanned aerial vehicle (UAV) laser scanning acquisitions allowed a high detailed, 3D reconstruction of forest canopies.We analyse the impact of the two contrasting forest canopies, both in terms of structure as well as optical properties, on the 3D extinction of photosynthetic active radiation (PAR, 400 nm - 700 nm) for a whole diurnal cycle. We show that PAR extinction is mainly driven by the canopy structure, resulting in an exponential light extinction profile for the temperate and a more linear extinction profile in the tropical site. The larger 3D heterogeneity in canopy structure for the tropical site also resulted in larger variability in light extinction throughout the whole canopy. We found that contrasting LOPs between the two forests had a minor influence on light extinction. However, approximating light extinction profiles with layered Beer-Lambert or Big-Leaf models only poorly represented the 3D heterogeneity of light extinction within the canopy, illustrating the need for more detailed 3D modelling of light distribution within forest ecosystems. This can give us important insights into light-related mechanisms driving species coexistence, competition and diversity in complex forest ecosystems.

Rockfall Source Identification Using a Hybrid Gaussian Mixture-Ensemble Machine Learning Model and LiDAR Data

The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms (ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

A novel rockfall hazard assessment using laser scanning data and 3D modelling in GIS

Rockfall hazards occur widely in regions with steep terrain such as Kinta Valley, Malaysia. Rockfalls threaten urban areas and the transportation corridors that pass through such areas. This paper proposes a comprehensive rockfall hazard assessment strategy based on high-resolution laser scanning data (LiDAR), both airborne and terrestrial. It provides (1) rockfall source identification by developing a hybrid model based on a bagging neural network (BBNN), which is compared with various machine learning algorithms and ensemble models (bagging, boosting, voting) and a Gaussian mixture model; (2) 3D modelling of rockfall kinematic processes (trajectory distribution, frequency, velocity, kinetic energy, bounce height, impact location); and (3) hazard zonation based on spatial modelling in combination with an analytical hierarchy process (AHP) in a geographic information system (GIS). In addition, mitigation measures are suggested based on the modelling results. The proposed methodology was validated in three study areas to test the applicability and generalisability of the methods. The results show that the proposed hybrid model can accurately identify rockfall source areas at the regional scale. It achieved a 97% training accuracy and 5-fold cross-validation area under curve (AUC) value of 0.96. The mechanical parameters of the developed 3D model were calibrated with an accuracy of 97%, 93% and 95% for Gunung Lang, Gua Tambun and Gunung Rapat areas, respectively. In addition, the proposed spatial model effectively delineates areas at risk of rockfalls. This method provides a comprehensive understanding of rockfall hazards that can assist authorities to develop proper management and protection of urban areas and transportation corridors.

DEFECT DETECTION AND QUALITY ASSESSMENT OF HARDWOOD LOGS:PART 2—COMBINED ACOUSTIC AND LASER SCANNING SYSTEM

The objective of this study was to determine the technical feasibility of combining acoustic wave data with high-resolution laser scanning data to improve the accuracy of defect detection and quality assessment in hardwood logs. Using acoustic impact testing and high-resolution laser scanning techniques, 21 yellow-poplar logs ( Liriodendron tulipifera ) obtained from the central Appalachian region were evaluated for internal and external defects. These logs were then sawn into boards and the boards were visually graded based on the National Hardwood Lumber Association grading rules. The response signals of the logs from acoustic impact testing were analyzed to extract time-domain and frequency-domain parameters. The laser scan data of each log was processed by a defect detection system. The results indicated that acoustic velocity, time centroid, damping ratio, and the combined time- and frequency-domain parameters are all effective quality predictors of the hardwood logs in terms of internal soundness. High-resolution laser scanning is complementary to acoustic impact testing. Acoustic parameters combined with laser scanning results provide a more complete data picture of the log: size, shape, surface defects, and degree of soundness. Indications of soundness in a particular log allow the internal prediction system to flag suspicious defects as potentially unsound. Thus, a combined system would be able to discriminate much more precisely with respect to log quality and potential board grade yields than would either method independently.

DEFECT DETECTION AND QUALITY ASSESSMENT OF HARDWOOD LOGS: PART 1—ACOUSTIC IMPACT TEST AND WAVELET ANALYSIS

The objective of this study was to determine the technical feasibility of combining acoustic wave data with high-resolution laser scanning data to improve the accuracy of defect detection and quality assessment in hardwood logs. This article (Part 1) focused on exploring the potential of an acoustic impact testing method coupled with advanced waveform analysis to detect internal decay of hardwood logs and classify logs in terms of log quality and potential board grade yields. Twenty-one yellow-poplar (Liriodendron tulipifera) logs obtained from the Central Appalachian region were evaluated for internal soundness using an acoustic impact testing technique. These logs were then sawn into boards, and the boards were visually graded based on National Hardwood Lumber Association grading rules. The response signals of the logs from acoustic impact tests were analyzed through moment analysis and continuous wavelet transform to extract time-domain and frequency-domain parameters. The results indicated that the acoustic impact test coupled with wavelet analysis is a viablemethod to evaluate the internal soundness of hardwood logs. Log acoustic velocity alone was able to identify the very low-end logs that have the most severe internal rot or other unsound defects but failed to identify the logs with poor geometry that resulted in very low recovery. Time centroid, damping ratio, and combined time- and frequency-domain parameters were found effective in predicting log quality in terms of board grade yields. Log segregation based on time-domain (time centroid and ρ/Tc**2) and frequency-domain (damping ratio and Ed/ζ**2) parameters showed a positive correlation with the board grade yields.

Assessment of the effects of expressway geometric design features on the frequency of accident crash rates using high-resolution laser scanning data and GIS

ABSTRACTAccurate information on accidents and on the relevant factors that affect them is critical for establishing the relationship between accident frequency and explanatory factors. In this study, we present a simplified method to extract road geometric features accurately from very high-resolution laser scanning data to analyze accident frequency on the North-South Expressway in Malaysia. Using expressway geometric features (i.e. horizontal and vertical alignments) extracted from laser scanning data and accident histories, this research first developed an APM based on geometric regression and a geographic information system (GIS). Then, an elasticity analysis was conducted to investigate the relationship between accident occurrence and road geometric design features. Results of the case study showed that the length of the road segments (mean = 0.014, elasticity = 0.122), the number of vertical curves in a road section (mean = 4.797, elasticity = 0.999), and the presence of a horizontal curve in a road segment (mean = 2.746, elasticity = 0.877), the average distance to the nearest access point (mean = -0.001, elasticity = −0.035), and AADT (mean = 3.01, elasticity = 0.881) determined accident occurrence, all at a significance level of 5%. This study shows that laser scanning systems can provide an easy and efficient method to collect transportation data, particularly those for accident analysis.

Historical analysis and visualization of the retreat of Findelengletscher, Switzerland, 1859–2010

Since the end of the Little Ice Age around 1850, glaciers in Europe have strongly retreated. Thanks to early topographic surveys in Switzerland, accurate maps are available, which enable us to trace glacier changes back in time. The earliest map for all of Switzerland that is usable for a detailed analysis is the Dufour map from around 1850 with subsequent topographic maps on a ~20year interval. Despite the large public and scientific interest in glacier changes through time, this historic dataset has not yet been fully utilized for topographic change assessment or visualization of historic glacier extents. In this study, we use eleven historical topographic maps and more recent digital datasets for the region of Zermatt to analyze geometric changes (length, area and volume) of Findelengletscher as well as for creating animations of glacier evolution through time for use in public communication. All maps were georeferenced, the contour lines digitized, and digital elevation models (DEMs) created and co-registered. Additional digital data like the SRTM X-band DEM and high resolution laser scanning data were used to extend the analysis until 2010. Moreover, one independent DEM from aerial photogrammetry was used for comparison. During the period 1859–2010, Findelengletscher lost 3.5km of its length (6.9km in 2010), 4.42±0.13km2 of its area (15.05±0.45km2 in 2010) and 1.32±0.52km3 of its volume. The average rate of thickness loss is 0.45±0.042myr−1 for the 151years period. Four periods with high thickness change from −0.56m±0.28yr−1 (1859–1881), −0.40±0.08myr−1 (1937–1965), −0.90±0.31myr−1 (1995–2000) and −1.18±0.02myr−1 (2000–2005) have been identified. Small positive thickness changes were found for the periods 1890–1909 (+0.09±0.46myr−1) and 1988–1995 (+0.05±0.24myr−1). During its retreat with intermittent periods of advance, the glacier separated into three parts. The above changes are demonstrated through an animation (available from the supplementary material), which has been created to inform the general public.

Sparse logistic regression and polynomial modelling for detection of artificial drainage networks

Mire ditching changes dramatically mire biodiversity. Thus, drainage network detection is an important factor when analysing the natural state of a mire. In this article, we propose a method for automated drainage network detection from raster digital terrain model created from high-resolution laser scanning data. Sparse logistic regression classifier with a large generic feature set and automated feature selection is used for classification. Broken segments are connected with polynomial modelling. The results showed that our method can accurately detect artificial drainage networks.

Measuring blast fragmentation at Esperanza mine using high-resolution 3D laser scanning

Image analysis as a technique for fragmentation measurement of rock piles has been the subject of research since the 1980s, and to date, run of mine (ROM) fragmentation optimisation studies have primarily relied on particle size measurement using photographic-based 2D imaging systems. Disadvantages of 2D imaging systems include particle delineation errors because of variable lighting and material colour and texture variation; no direct measure of scale and perspective distortion; and inability to distinguish overlapped particles, non-overlapped particles, and areas of fines. With the development of 3D imaging technologies, there is an opportunity to develop techniques that could improve data collection and overcome the limitations of existing 2D image-based systems. This paper describes the first attempt to use 3D high-resolution laser scanning techniques to quantify ‘whole of muckpile’ fragmentation from full-scale production blasting. During two monitoring campaigns in 2013, high-resolution laser scanning data were collected from production blasts at Esperanza mine (Antofagasta Minerals Group). Fully automated analysis of the 3D data was possible in all cases where the data were of sufficiently high resolution. Manual pre-processing was required when the data were of low resolution to specify the region of fines. Overall results indicated that ROM fragmentation requirements were meeting specified targets, despite the marked differences in powder factors. This was particularly the case for those blasts conducted in similar geological domains. This work has demonstrated that high-resolution laser scanning can be used as an alternative technique to measure ‘whole of muckpile’ fragmentation in production blasting.

Persistence in intra‐annual snow depth distribution: 2. Fractal analysis of snow depth development

We present an analysis of high resolution laser scanning data of snow depths of three different slopes in the Wannengrat catchment (introduced in part 1) using omnidirectional and directional variograms for three specific terrain features; cross‐loaded slopes, lee slopes, and windward slopes. A break in scaling behavior was observed in all subareas, which can be seen as the roughness scale of bare earth terrain which is modified by the snow cover. In the wind‐protected lee slope a different scaling behavior was observed, compared to the two wind‐exposed areas. The wind‐exposed areas have a smaller ordinal intercept , a smaller short range fractal dimension D, and a larger scale break distance L than the wind‐protected lee slope. Snow depth structure inherits characteristics of dominant NW storms, which results, e.g., in a trend toward larger break distances in the course of the accumulation season. This can be interpreted as a result of surface smoothing at increasing scales. Similar scaling characteristics were obtained for two different years at the end of the accumulation season. Since snow depth structure is altered strongly by NW storms, this inter‐annual consistency may strongly depend on their frequency in an accumulation period. With the analysis of directional variograms anisotropies of fractal parameters were detected, which were related to dominant wind directions.

Semi-automatic extraction of rock mass structural data from high resolution LIDAR point clouds

In this paper a Matlab tool called DiAna (Discontinuity Analysis), for the 2D and 3D geo-structural analysis of rock mass discontinuities on high resolution laser scanning data is presented. The proposed approach is able to semi-automatically retrieve some relevant rock mass parameters, namely orientation, number of sets, spacing/frequency (and derived RQD), persistence, block size and scale dependent roughness, by analyzing high resolution point clouds acquired from terrestrial or aerial laser scanners. In addition, with a specific DiAna option called filterveg, we are able to remove vegetation or other disturbing objects from the point cloud, which is one of the main problems in LIDAR data processing. Some examples of the proposed method have demonstrated its ability to investigate rock masses characterized by irregular block shapes, and suggest applications in the field of engineering geology and emergency management, when it is often advisable to minimize survey time in dangerous environments and, in the same time, it is necessary to gather all the required information as fast as possible.