Lidar Model Research Articles

In-Field Estimation of Orange Number and Size by 3D Laser Scanning

The estimation of fruit load of an orchard prior to harvest is useful for planning harvest logistics and trading decisions. The manual fruit counting and the determination of the harvesting capacity of the field results are expensive and time-consuming. The automatic counting of fruits and their geometry characterization with 3D LiDAR models can be an interesting alternative. Field research has been conducted in the province of Cordoba (Southern Spain) on 24 ‘Salustiana’ variety orange trees—Citrus sinensis (L.) Osbeck—(12 were pruned and 12 unpruned). Harvest size and the number of each fruit were registered. Likewise, the unitary weight of the fruits and their diameter were determined (N = 160). The orange trees were also modelled with 3D LiDAR with colour capture for their subsequent segmentation and fruit detection by using a K-means algorithm. In the case of pruned trees, a significant regression was obtained between the real and modelled fruit number (R2 = 0.63, p = 0.01). The opposite case occurred in the unpruned ones (p = 0.18) due to a leaf occlusion problem. The mean diameters proportioned by the algorithm (72.15 ± 22.62 mm) did not present significant differences (p = 0.35) with the ones measured on fruits (72.68 ± 5.728 mm). Even though the use of 3D LiDAR scans is time-consuming, the harvest size estimation obtained in this research is very accurate.

Calculating macroalgal height and biomass using bathymetric LiDAR and a comparison with surface area derived from satellite data in Nova Scotia, Canada

Abstract The ability to map and monitor the macroalgal coastal resource is important to both the industry and the regulator. This study evaluates topo-bathymetric lidar (light detection and ranging) as a tool for estimating the surface area, height and biomass of Ascophyllum nodosum, an anchored and vertically suspended (floating) macroalga, and compares the surface area derived from lidar and WorldView-2 satellite imagery. Pixel-based Maximum Likelihood classification of low tide satellite data produced 2-dimensional maps of intertidal macroalgae with overall accuracy greater than 80%. Low tide and high tide topo-bathymetric lidar surveys were completed in southwestern Nova Scotia, Canada. Comparison of lidar-derived seabed elevations with ground-truth data collected using a survey grade global navigation satellite system (GNSS) indicated the low tide survey data have a positive bias of 15 cm, likely resulting from the seaweed being draped over the surface. The high tide survey data did not exhibit this bias, although the suspended canopy floating on the water surface reduced the seabed lidar point density. Validation of lidar-derived seaweed heights indicated a mean difference of 30 cm with a root mean square error of 62 cm. The modelled surface area of seaweed was 28% greater in the lidar model than the satellite model. The average lidar-derived biomass estimate was within one standard deviation of the mean biomass measured in the field. The lidar method tends to overestimate the biomass compared to field measurements that were spatially biased to the mid-intertidal level. This study demonstrates an innovative and cost-effective approach that uses a single high tide bathymetric lidar survey to map the height and biomass of dense macroalgae.

Surface rupture and characteristics of a fault associated with the 2011 and 2016 earthquakes in the southern Abukuma Mountains, northeastern Japan, triggered by the Tohoku-Oki earthquake

The 2011 Tohoku-Oki offshore subduction earthquake (Mw 9.0) triggered many normal-type earthquakes inland in northeastern Japan. Among these were two very similar normal-faulting earthquakes in 2011 (Mw 5.8) and 2016 (Mw 5.9), which created surface ruptures along the newly named Mochiyama fault within the southern Abukuma Mountains, northeastern Japan, where no active faults had been previously mapped by interpretation of aerial photographs. We conducted field surveys in this area immediately after both earthquakes, and we performed trench excavations and observations of fault fracture zones after the 2016 event. These activities were complemented by an interferometric synthetic aperture radar analysis that mapped the areas of deformation and locations of surface discontinuities for both events. The combined results document the coseismic behavior of the Mochiyama fault during both events. Subtle tectonic geomorphic features associated with the fault were evident in a lidar digital elevation model of the area, and layered structures of gouge were documented in the field. These lines of evidence indicate repeated activity at shallow crustal levels and the possibility of Quaternary activity. In addition, our trench excavations revealed at least one faulting event before 2011. Our comparison of paleoseismic records on this and two other normal faults in the Abukuma Mountains suggests that great earthquakes in the Japan Trench supercycle of 500–700 years do not consistently trigger ruptures on these faults, and the case of 2011, in which the Tohoku-Oki megathrust earthquake triggered all three faults, is a rare occurrence.

Validation of the Analytical Model of Oceanic Lidar Returns: Comparisons with Monte Carlo Simulations and Experimental Results

The analytical model based on the quasi-single small-angle scattering approximation can efficiently simulate oceanic lidar signals with multiple scattering; thus, its accuracy is of particular interest to scientists. In this paper, the model is modified to include refraction at oblique incidence and is then compared with Monte Carlo (MC) simulations and experimental results. Under different conditions, the results calculated by the analytical model demonstrate good agreement with the MC simulation and experimental data. The coefficient of determination R2 considering the logarithm of signals and the root mean square of the relative difference δ are R2 = 0.998 and δ = 10% in comparison with the semi-analytic MC simulation and R2 = 0.952 and δ = 46% for the lidar experiment. Thus, the results demonstrate the validity of the analytical model in the simulation of oceanic lidar signals.

On Bird Species Diversity and Remote Sensing—Utilizing Lidar and Hyperspectral Data to Assess the Role of Vegetation Structure and Foliage Characteristics as Drivers of Avian Diversity

Avian diversity has long been used as a surrogate for overall diversity. In forest ecosystems, it has been assumed that vegetation structure, composition, and condition have a significant impact on avian diversity. Today, these features can be evaluated via remote sensing. This study examined how structure metrics from lidar data and narrowband indices from hyperspectral data relate with avian diversity. This was assessed in four deciduous-dominated woods with differing age and structure set in an agricultural matrix in eastern England. The woods were delineated into cells within which metrics of avian diversity and remote sensing based predictors were calculated. Best subset regression was used to obtain best lidar models, hyperspectral models, and finally, the best models combining variables from both data sets. The aims were not only to examine the drivers of avian diversity, but to assess the capabilities of the two remote sensing techniques for the task. The amount of understorey vegetation was the best single predictor, followed by foliage height diversity, reflectance at 830 nm, anthocyanin reflectance index 1, and Vogelmann red edge index 2. This showed the significance of the full vertical profile of vegetation, the condition of the upper canopy, and potentially tree species composition. The results thus agree with the role that vegetation structure, condition, and floristics are assumed to have for diversity. However, the inclusion of hyperspectral data resulted in such minor improvements to models that its collection for these purposes should be assessed critically.

Lidar model of the formation of a sodium laser star when space objects are being observed and angularly tracked

This paper discusses a lidar model of the formation of a sodium laser star for the measurement and adaptive correction of atmospheric phase distortions in a ground-based optical system when space objects are being observed and angularly tracked. The energy characteristics of the laser star are studied when it occupies various angular positions in the visibility zone of a ground-based optical system. Requirements are formulated on the energy characteristics of a laser for forming a laser star in order to implement adaptive phase-matched correction of atmospheric phase distortions when low-orbit space objects are being observed.

Neolithic Temples of Malta: 3D analysis points to novel roof reconstruction

The Neolithic temples of Malta are among the oldest examples of prehistoric architecture, yet the construction of their roofs remains a mystery. The absence of any roofs or roofing material at the temple sites has resulted in conjecture regarding the original appearance of these megalithic structures. The most valuable indications of prehistoric Maltese roof architecture are found in the Neolithic burial complex, the Hypogeum of Hal Saflieni. Two chambers in the Hypogeum are modelled closely after the above-ground temples, with indications of a roof structural system on the ceilings. This paper uses LiDAR and photogrammetry-derived 3D models to provide a partial temple roof reconstruction that has its design entirely based on contemporaneous archaeology.Photogrammetric reconstruction of the Mnajdra and Tarxien temple complexes allowed for detailed architectural analyses including key structural features and any indications of previous roof construction that would be evident in situ. A LiDAR model of the carved chambers of the Hypogeum of Hal Saflieni was superimposed onto corresponding positions in the temple models. Merging the LiDAR imagery onto the photogrammetry temple models confirmed structural consistency between the two megalithic complexes; supporting the theory that the carved façades were a deliberate reflection of the original architecture of the Maltese temples. This evidence points to an entirely new temple roof reconstruction, founded upon the archaeology of Neolithic Malta.

Estimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling

The geometric structure of tree branches has been hypothesized to relate to the mechanical safety and efficiency of resource transport within a tree. As such, the topology of tree architecture links physical properties within a tree and influences the interaction of the tree with its environment. Prior work suggests the existence of general principles which govern tree architectural patterns across of species and bio-geographical regions. In particular, West, Brown and Enquist (WBE, 1997) and Savage et al. (2010) derive scaling exponents (branch radius scaling ratio α and branch length scaling ratio β) from symmetrical branch parameters and from these, an architecture-based metabolic scaling rate (θ) for the whole tree. With this key scaling exponent, the metabolism (e.g., number of leaves, respiration, etc.) of a whole tree, or potentially a group of trees, can be estimated allometrically. Until now, branch parameter values have been measured manually; either from standing live trees or from harvested trees. Such measurements are time consuming, labour intensive and susceptible to subjective errors. Remote sensing, and specifically terrestrial LiDAR (TLS), is a promising alternative, being objective, scalable, and able to collect large quantities of data without destructive sampling. In this paper, we calculated branch length, branch radius, and architecture-based metabolic rate scaling exponents by first using TLS to scan standing trees and then fitting quantitative structure models (TreeQSM) models to 3D point clouds from nine trees in a tropical forest in Guyana. To validate these TLS-derived scaling exponents, we compared them with exponents calculated from direct field measurements of all branches >10 cm at four scales: branch-level, cumulative branch order, tree-level and plot-level. We found a bias on the estimations of α and β exponents due to a bias on the reconstruction of the branching architecture. Although TreeQSM scaling exponents predicted similar θ as the manually measured exponents, this was due to the combination of α and β scaling exponents which were both biased. Also, the manually measured α and β scaling exponents diverged from the WBE’s theoretical exponents suggesting that trees in tropical environments might not follow the predictions for the symmetrical branching geometry proposed by WBE. Our study provides an alternative method to estimate scaling exponents at both the branch- and tree-level in tropical forest trees without the need for destructive sampling. Although this approach is based on a limited sample of nine trees in Guyana, it can be implemented for large-scale plant scaling assessments. These new data might improve our current understanding of metabolic scaling without harvesting trees.

Lidar model of the formation of a sodium "laser star" during the observation and angular tracking of space objects

Lidar model of the formation of a sodium "laser star" during the observation and angular tracking of space objects

Multi-layer electromagnetic spring with tunable negative stiffness for semi-active vibration isolation

Abstract Semi-active systems have demonstrated excellent performance in vibration isolation, However, the tunable range of conventional variable stiffness elements is limited by the mount stiffness required to support a load. To improve the performance of low-frequency vibration isolation, a novel compact and contactless multi-layer electromagnetic spring (MES) with tunable negative stiffness is proposed in this paper. The negative stiffness is generated by the electromagnetic force between the coils and the magnets and can be tuned online by controlling the current. Based on a stiffness analysis model, a design procedure for configuring the MES is presented to expand the region where the stiffness is negative and to increase its tunable range. As a result, with only one type of magnet and coil, various negative stiffness elements with different stiffness characteristics can be manufactured, thereby reducing costs. To verify the dynamic behavior of the MES, a tunable high-static-low-dynamic stiffness (HSLDS) vibration isolator based on the MES was modeled and evaluated by applying it to a lidar. The experimental results demonstrate the following: the MES tuned the isolator online and broadened the isolation frequency band such that the isolator attenuated the vibration of the lidar, and it significantly improved the lidar modeling performance.

Comparing TanDEM‐X Data With Frequently Used DEMs for Flood Inundation Modeling

AbstractFlood risk, particularly in Small Island Developing States, is increasing. Although spaceborne Digital Elevation Models (DEMs) have provided a capacity to model flooding at the global scale, their relatively coarse resolution (~90 m) has led to a limited ability to provide fine‐scale flood assessments in smaller catchments such as those in Small Island Developing States. Following the release of the TanDEM‐X DEM at ~12‐m resolution, the aim of this research is to determine whether TanDEM‐X can improve flood estimates in comparison to Shuttle Radar Topography Mission (SRTM) and Multi‐Error‐Removed Improved‐Terrain (MERIT) DEMs. Suitable methods to process TanDEM‐X to a Digital Terrain Model (DTM) are identified through testing of seven DTMs produced through combinations of different vegetation removal approaches. Methods include Progressive Morphological Filtering and Image Classification of two TanDEM‐X auxiliary data sets—a Height Error Map and Amplitude map. The LISFLOOD‐FP hydrodynamic model output flood extent and water surface elevation for the TanDEM‐X DTMs, SRTM, and MERIT are compared against the LiDAR model for a catchment in Fiji. The main findings show that the unprocessed TanDEM‐X has improved predictive capacity over SRTM, but not MERIT. The TanDEM‐X processing method combining Image Classification of the Amplitude map and Progressive Morphological Filtering produces the DTM with the highest flood model skill in comparison to all tested DEMs. This DTM reports a 12–14 percentage point higher flood model skill score than MERIT and a lower water surface elevation root‐mean‐square error of 0.11–0.21 m, indicating the suitability of TanDEM‐X for flood modeling.

Quantum lidar based on a random interleaved optical pulse sequence consisting of wavelength-time quantum states.

Based on a random interleaved optical pulse sequence consisting of wavelength-time quantum states, we have established a quantum lidar model. Multiple quantum states are used as a detection tool for the interception and interference of a target, and multiple wavelengths spanning the ultraviolet to near-infrared waveband are used to avoid interference and improve the detection efficiency. We elaborate upon the working principle of the entire quantum lidar detection system and demonstrate its feasibility through simulations, thereby establishing a foundation for the application of quantum lidar systems aboard satellite platforms at long distances from the high-precision detection of targets.

Mapping canopy defoliation by herbivorous insects at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements

Defoliation by herbivorous insects is a widespread forest disturbance driver, affecting global forest health and ecosystem dynamics. Compared with time- and labor-intensive field surveys, remote sensing provides the only realistic approach to mapping canopy defoliation by herbivorous insects over large spatial and temporal scales. However, the spectral and structural signatures of defoliation by insects at the individual tree level have not been well studied. Additionally, the predictive power of spectral and structural metrics for mapping canopy defoliation has seldom been compared. These critical knowledge gaps prevent us from consistently detecting and mapping canopy defoliation by herbivorous insects across multiple scales. During the peak of a gypsy moth outbreak in Long Island, New York in summer 2016, we leveraged bi-temporal airborne imaging spectroscopy (IS, i.e., hyperspectral imaging) and LiDAR measurements at 1 m spatial resolution to explore the spectral and structural signatures of canopy defoliation in a mixed oak-pine forest. We determined that red edge and near-infrared spectral regions within the IS data were most sensitive to crown-scale defoliation severity. LiDAR measurements including B70 (i.e., 70th bincentile height), intensity skewness, and kurtosis were effectively able to detect structural changes caused by herbivorous insects. In addition to canopy leaf loss, increased exposure of understory and non-photosynthetic materials contributed to the detected spectral and structural signatures. Comparing the ability of individual sensors to map canopy defoliation, the LiDAR-only Ordinary Least-Square (OLS) model performed better than the IS-only model (Adj. R-squared = 0.77, RMSE = 15.37% vs. Adj. R-squared = 0.63, RMSE = 19.11%). The IS + LiDAR model improved on performance of the individual sensors (Adj. R-squared = 0.81, RMSE = 14.46%). Our study improves our understanding of spectral and structural signatures of defoliation by herbivorous insects and presents a novel approach for mapping insect defoliation at the individual tree level. Additionally, with the current and next generation of spaceborne sensors (e.g., WorldView-3, Landsat, Sentinel-2, HyspIRI, and GEDI), higher accuracy and frequent monitoring of insect defoliation may become more feasible across a range of spatial scales, which are critical for ecological research and management of forest resources including the economic consequences of forest insect infestations (e.g., reduced growth and increased mortality), as well as for informing and testing of carbon cycle models.

Concept for maritime near-surface surveillance using water Raman scattering.

We discuss a maritime surveillance and detection concept based on Raman scattering of water molecules. Using a range-gated scanning lidar that detects Raman scattered photons from water, the absence or change of signal indicates the presence of a non-water object. With sufficient spatial resolution, a two-dimensional outline of the object can be generated by the scanning lidar. Because Raman scattering is an inelastic process with a relatively large wavelength shift for water, this concept avoids the often problematic elastic scattering for objects at or very close to the water surface or from the bottom surface for shallow waters. The maximum detection depth for this concept is limited by the attenuation of the excitation and return Raman light in water. If excitation in the UV is used, fluorescence can be used for discrimination between organic and non-organic objects. In this paper, we present a lidar model for this concept and discuss results of proof-of-concept measurements. Using published cross section values, the model and measurements are in reasonable agreement and show that a sufficient number of Raman photons can be generated for modest lidar parameters to make this concept useful for near-surface detection.

Lidar-based closed-loop wake redirection in high-fidelity simulation

This work presents the next step in realizing lidar-based closed-loop wake redirection control. Lidar-based closed-loop wake redirection aims at repositioning the wake at a desired position by yawing the wind turbine. The actual wake deflection is derived from lidar measurements and used in a closed-loop control scheme. Compared to an open-loop setting in which temporal changes are not taken into account, lidar-based closed-loop wake redirection can react on temporal disturbances. This yields a more robust control solution due to the employed closed-loop control framework. In this work, for the first time, the concept is implemented in an LES environment namely the PArallelized Large-eddy simulation Model (PALM) code. In PALM lidar measurements are simulated using a lidar model which are processed to estimate the wake position. A controller is synthesized by the usage of a the reduced order wind farm model WindFarmSimulator (WFSim). High-fidelity simulation results illustrate the controller’s ability to adapt to a temporal changing crosswind disturbance in a turbulent simulation scenario. Consequently, it increases the power output of the two-turbine scenario compared to the open-loop approach.

Investigation into the shape of a wake of a yawed full-scale turbine

In this paper, data from a lidar-based field campaign are used to examine the effect of yaw misalignment on the shape of a wind turbine wake. Prior investigation in wind tunnel research and high-fidelity computer simulation show that the shape assumes an increasingly curled shape as the wake propagates downstream, because of the presence of two counter-rotating vortices. The shape of the wake observed in the field data diverges from predictions of wake shape, and a lidar model is simulated within a large-eddy simulation of the wind turbine in the atmospheric boundary layer to understand the discrepancy.

Quantifying branch architecture of tropical trees using terrestrial LiDAR and 3D modelling

Key message A method using terrestrial laser scanning and 3D quantitative structure models opens up new possibilities to reconstruct tree architecture from tropical rainforest trees.Tree architecture is the three-dimensional arrangement of above ground parts of a tree. Ecologists hypothesize that the topology of tree branches represents optimized adaptations to tree’s environment. Thus, an accurate description of tree architecture leads to a better understanding of how form is driven by function. Terrestrial laser scanning (TLS) has demonstrated its potential to characterize woody tree structure. However, most current TLS methods do not describe tree architecture. Here, we examined nine trees from a Guyanese tropical rainforest to evaluate the utility of TLS for measuring tree architecture. First, we scanned the trees and extracted individual tree point clouds. TreeQSM was used to reconstruct woody structure through 3D quantitative structure models (QSMs). From these QSMs, we calculated: (1) length and diameter of branches > 10 cm diameter, (2) branching order and (3) tree volume. To validate our method, we destructively harvested the trees and manually measured all branches over 10 cm (279). TreeQSM found and reconstructed 95% of the branches thicker than 30 cm. Comparing field and QSM data, QSM overestimated branch lengths thicker than 50 cm by 1% and underestimated diameter of branches between 20 and 60 cm by 8%. TreeQSM assigned the correct branching order in 99% of all cases and reconstructed 87% of branch lengths and 97% of tree volume. Although these results are based on nine trees, they validate a method that is an important step forward towards using tree architectural traits based on TLS and open up new possibilities to use QSMs for tree architecture.

Analysis of In-Service Traffic Sign Visual Condition: Tree-Based Model for Mobile LiDAR and Digital Photolog Data

AbstractBecause the important task of traffic signs is to provide drivers with valuable information, the replacement of ineffective signs leads to a safer and more efficient environment for road us...

Relative humidity vertical profiling using lidar-based synergistic methods in the framework of the Hygra-CD campaign

Abstract. Accurate continuous measurements of relative humidity (RH) vertical profiles in the lower troposphere have become a significant scientific challenge. In recent years a synergy of various ground-based remote sensing instruments have been successfully used for RH vertical profiling, which has resulted in the improvement of spatial resolution and, in some cases, of the accuracy of the measurement. Some studies have also suggested the use of high-resolution model simulations as input datasets into RH vertical profiling techniques. In this paper we apply two synergetic methods for RH profiling, including the synergy of lidar with a microwave radiometer and high-resolution atmospheric modeling. The two methods are employed for RH retrieval between 100 and 6000 m with increased spatial resolution, based on datasets from the HygrA-CD (Hygroscopic Aerosols to Cloud Droplets) campaign conducted in Athens, Greece from May to June 2014. RH profiles from synergetic methods are then compared with those retrieved using single instruments or as simulated by high-resolution models. Our proposed technique for RH profiling provides improved statistical agreement with reference to radiosoundings by 27 % when the lidar–radiometer (in comparison with radiometer measurements) approach is used and by 15 % when a lidar model is used (in comparison with WRF-model simulations). Mean uncertainty of RH due to temperature bias in RH profiling was ∼ 4.34 % for the lidar–radiometer and ∼ 1.22 % for the lidar–model methods. However, maximum uncertainty in RH retrievals due to temperature bias showed that lidar-model method is more reliable at heights greater than 2000 m. Overall, our results have demonstrated the capability of both combined methods for daytime measurements in heights between 100 and 6000 m when lidar–radiometer or lidar–WRF combined datasets are available.

Delineation of the riparian zone in data-scarce regions using fuzzy membership functions: An evaluation based on the case of the Naryn River in Kyrgyzstan

Riparian zones contain important ecosystems with a high biodiversity and relevant ecosystem services. From a process point of view, riparian zones are characterized by the interaction of hydrological, geomorphological and ecological processes. Consequently, their boundary is dynamic and blurred as it depends on not only the local valley morphology but also the hydrological regime. This makes a delineation of riparian zones from digital elevation data a challenging task as it should represent this blurred nature of riparian zone boundaries. While the application of high resolution topography from LIDAR and hydraulic models have become standard in many developed countries, studies and applications in remote areas still commonly rely on the freely available coarse resolution digital elevation models. In this article, we present the delineation of riparian zones from the SRTM-1 elevation model and fuzzy membership functions for the Naryn River in Kyrgyzstan having a length of approximately 700 km. We evaluate the extraction of the underlying channel network as well as the different indicator variables. The maximum user's accuracy for the delineation of riparian zones along the entire Naryn River is 82.14% reflecting the uncertainty arising from the heterogeneity of the riverscape as well as from the quality of the underlying elevation data. Despite the uncertainty, the fuzzy membership approach is considered as an appropriate method for riparian zone delineation as it reflects their dynamic, transitional character and can be used as indicator of connectivity within a riverscape.