Echo Width Research Articles

OBJECT-BASED ANALYSIS OF LIDAR GEOMETRIC FEATURES FOR VEGETATION DETECTION IN SHADED AREAS

Abstract. The extraction of land cover information from remote sensing data is a complex process. Spectral information has been widely utilized in classifying remote sensing images. However, shadows limit the use of multispectral images because they result in loss of spectral radiometric information. In addition, true reflectance may be underestimated in shaded areas. In land cover classification, shaded areas are often left unclassified or simply assigned as a shadow class. Vegetation indices from remote sensing measurement are radiation-based measurements computed through spectral combination. They indicate vegetation properties and play an important role in remote sensing of forests. Airborne light detection and ranging (LiDAR) technology is an active remote sensing technique that produces a true orthophoto at a single wavelength. This study investigated three types of geometric lidar features where NDVI values fail to represent meaningful forest information. The three features include echo width, normalized eigenvalue, and standard deviation of the unit weight observation of the plane adjustment, and they can be derived from waveform data and discrete point clouds. Various feature combinations were carried out to evaluate the compensation of the three lidar features to vegetation detection in shaded areas. Echo width was found to outperform the other two features. Furthermore, surface characteristics estimated by echo width were similar to that by normalized eigenvalues. Compared to the combination of only NDVI and mean height difference, those including one of the three features had a positive effect on the detection of vegetation class.

OBJECT-BASED ANALYSIS OF LIDAR GEOMETRIC FEATURES FOR VEGETATION DETECTION IN SHADED AREAS

The extraction of land cover information from remote sensing data is a complex process. Spectral information has been widely utilized in classifying remote sensing images. However, shadows limit the use of multispectral images because they result in loss of spectral radiometric information. In addition, true reflectance may be underestimated in shaded areas. In land cover classification, shaded areas are often left unclassified or simply assigned as a shadow class. Vegetation indices from remote sensing measurement are radiation-based measurements computed through spectral combination. They indicate vegetation properties and play an important role in remote sensing of forests. Airborne light detection and ranging (LiDAR) technology is an active remote sensing technique that produces a true orthophoto at a single wavelength. This study investigated three types of geometric lidar features where NDVI values fail to represent meaningful forest information. The three features include echo width, normalized eigenvalue, and standard deviation of the unit weight observation of the plane adjustment, and they can be derived from waveform data and discrete point clouds. Various feature combinations were carried out to evaluate the compensation of the three lidar features to vegetation detection in shaded areas. Echo width was found to outperform the other two features. Furthermore, surface characteristics estimated by echo width were similar to that by normalized eigenvalues. Compared to the combination of only NDVI and mean height difference, those including one of the three features had a positive effect on the detection of vegetation class.

Scattering due to twisted PEC cylinder coated with chiral/chiroferrite mediums

Scattering of electromagnetic waves by perfectly electrical conducting (PEC) cylinder, coated with chiroferrite medium, is investigated under the oblique angle of incident. The coated PEC cylinder is wrapped with perfectly conducting sheath helix structure. For this structural configuration, the bi- and the mono-scattering echo widths are computed numerically while assuming the incident wave with parallel polarization. The roles of pitch angle (of sheath helix structure) and the material parameters on the echo width are analyzed. The obtained results for scattering echo widths are compared with those achieved when the PEC cylinder is coated with simply chiral material. It is found that the chiro-ferrite coating causes larger scattering of waves than the situation when the PEC cylinder is coated with simply chiral medium. Furthermore, a parallel orientation of the helix structure results in larger echo width.

Scattering characteristics of a chiral-coated cylindrical reflector embedded in a double-negative metamaterial

The scattering characteristics of a cylindrical reflector coated with a chiral material and embedded in a double-negative metamaterial have been studied using numerical simulation. The effects of double-negative metamaterial background media and chiral admittances of a chiral coating layer upon the co- and cross-polarized echo widths have been investigated. It is shown that a double-negative metamaterial background with relatively larger negative values of the permittivity and the permeability enhances the co-polarized echo width in the forward scattering direction and reduces this echo width in the backward scattering direction as compared to the free space background. It is further shown that by increasing the chiral admittance of a chiral-coated cylindrical reflector embedded in a double-negative metamaterial with fixed background parameters increases the co-polarized echo width in the forward and the backward scattering directions as compared to an achiral-coated cylindrical reflector embedded in the same double-negative metamaterial background.

Full-waveform data for building roof step edge localization

Airborne laser scanning data perfectly represent flat or gently sloped areas; to date, however, accurate breakline detection is the main drawback of this technique. This issue becomes particularly important in the case of modeling buildings, where accuracy higher than the footprint size is often required. This article covers several issues related to full-waveform data registered on building step edges. First, the full-waveform data simulator was developed and presented in this paper. Second, this article provides a full description of the changes in echo amplitude, echo width and returned power caused by the presence of edges within the laser footprint. Additionally, two important properties of step edge echoes, peak shift and echo asymmetry, were noted and described. It was shown that these properties lead to incorrect echo positioning along the laser center line and can significantly reduce the edge points’ accuracy. For these reasons and because all points are aligned with the center of the beam, regardless of the actual target position within the beam footprint, we can state that step edge points require geometric corrections. This article presents a novel algorithm for the refinement of step edge points. The main distinguishing advantage of the developed algorithm is the fact that none of the additional data, such as emitted signal parameters, beam divergence, approximate edge geometry or scanning settings, are required. The proposed algorithm works only on georeferenced profiles of reflected laser energy. Another major advantage is the simplicity of the calculation, allowing for very efficient data processing. Additionally, the developed method of point correction allows for the accurate determination of points lying on edges and edge point densification. For this reason, fully automatic localization of building roof step edges based on LiDAR full-waveform data with higher accuracy than the size of the lidar footprint is feasible.

Scattering from silver metal cylinder due to L-nihility coated with conducting sheath helix embedded dielectric medium

In this article, scattering from silver metal cylinder due to L-nihility, coated with dielectric material that encapsulates perfectly electric conducting sheath helix structure, is presented. The orientation of helix can be altered, and the cases of both the parallel (TM) and the perpendicular (TE) polarizations of electromagnetic (EM) waves are analyzed. Co- and cross-polarized fields for different values of pitch angle are formulated under oblique angle of incidence. The bi-static echo width of the scatterer is investigated as a function of at the L-nihility frequency which lies within the optical frequency range. The results are compared with those obtained for perfect electric conductor (PEC) at different values of the angle of incidence. It is observed that the considered guiding structure behaves identically with the simple PEC cylinder under the situation when the helix structure is oriented parallel to the axial direction of the guide. However, for the other forms of the helix orientation, the structure behaves differently – thereby confirming the validity of the analytical approach for the aforementioned complex structured guide presented in the article.

On the frequency response of silver metal with cylindrical geometry

Frequency response of silver metal is illustrated by using circularly cylindrical scatterer as an example. It is observed that silver metal shows the behavior of double-positive, epsilon-negative and the particular case of nihility metamaterials at different ranges of applied frequency. Further, the numerical results demonstrate the dependence of echo width of the cylinder on the wavelength of perpendicular and parallel polarizations of applied field.

POTENTIAL OF FULL WAVEFORM AIRBORNE LASER SCANNING DATA FOR URBAN AREA CLASSIFICATION – TRANSFER OF CLASSIFICATION APPROACHES BETWEEN MISSIONS

Abstract. Full-waveform (FWF) LiDAR (Light Detection and Ranging) systems have their advantage in recording the entire backscattered signal of each emitted laser pulse compared to conventional airborne discrete-return laser scanner systems. The FWF systems can provide point clouds which contain extra attributes like amplitude and echo width, etc. In this study, a FWF data collected in 2010 for Eisenstadt, a city in the eastern part of Austria was used to classify four main classes: buildings, trees, waterbody and ground by employing a decision tree. Point density, echo ratio, echo width, normalised digital surface model and point cloud roughness are the main inputs for classification. The accuracy of the final results, correctness and completeness measures, were assessed by comparison of the classified output to a knowledge-based labelling of the points. Completeness and correctness between 90% and 97% was reached, depending on the class. While such results and methods were presented before, we are investigating additionally the transferability of the classification method (features, thresholds …) to another urban FWF lidar point cloud. Our conclusions are that from the features used, only echo width requires new thresholds. A data-driven adaptation of thresholds is suggested.

Normalization of Echo Features Derived from Full-Waveform Airborne Laser Scanning Data

Full-waveform airborne laser scanning systems provide fundamental observations for each echo, such as the echo width and amplitude. Geometric and physical information about illuminated surfaces are simultaneously provided by a single scanner. However, there are concerns about whether the physical meaning of observations is consistent among different scanning missions. Prior to the application of waveform features for multi-temporal data classification, such features must be normalized. This study investigates the transferability of normalized waveform features to different surveys. The backscatter coefficient is considered to be a normalized physical feature. A normalization process for the echo width, which is a geometric feature, is proposed. The process is based on the coefficient of variation of the echo widths in a defined neighborhood, for which the Fuzzy Small membership function is applied. The normalized features over various land cover types and flight missions are investigated. The effects of different feature combinations on the classification accuracy are analyzed. The overall accuracy of the combination of normalized features and height-based attributes achieves promising results (>93% overall accuracy for ground, roof, low vegetation, and tree canopy) when different flight missions and classifiers are used. Nevertheless, the combination of all possible features, including raw features, normalized features, and height-based features, performs less well and yields inconsistent results.

Categorizing Grassland Vegetation with Full-Waveform Airborne Laser Scanning: A Feasibility Study for Detecting Natura 2000 Habitat Types

There is increasing demand for reliable, high-resolution vegetation maps covering large areas. Airborne laser scanning data is available for large areas with high resolution and supports automatic processing, therefore, it is well suited for habitat mapping. Lowland hay meadows are widespread habitat types in European grasslands, and also have one of the highest species richness. The objective of this study was to test the applicability of airborne laser scanning for vegetation mapping of different grasslands, including the Natura 2000 habitat type lowland hay meadows. Full waveform leaf-on and leaf-off point clouds were collected from a Natura 2000 site in Sopron, Hungary, covering several grasslands. The LIDAR data were processed to a set of rasters representing point attributes including reflectance, echo width, vegetation height, canopy openness, and surface roughness measures, and these were fused to a multi-band pseudo-image. Random forest machine learning was used for classifying this dataset. Habitat type, dominant plant species and other features of interest were noted in a set of 140 field plots. Two sets of categories were used: five classes focusing on meadow identification and the location of lowland hay meadows, and 10 classes, including eight different grassland vegetation categories. For five classes, an overall accuracy of 75% was reached, for 10 classes, this was 68%. The method delivers unprecedented fine resolution vegetation maps for management and ecological research. We conclude that high-resolution full-waveform LIDAR data can be used to detect grassland vegetation classes relevant for Natura 2000.

Analysis of scattering from cylindrical structures coated by radially inhomogeneous layer using Taylor’s series method

Consider a cylindrical structure with an arbitrary core coated by a radially inhomogeneous layer in a general case. The core of the structure may be PEC, PMC, PEMC, impedance boundary, dielectric, or metamaterial. Contrary to the scattering problems of homogeneous media, scattering problems of inhomogeneous media do not have exact solutions except for special inhomogeneous profiles. In this paper, a general frequency domain method is proposed to analyze scattering from such structures on the basis of Taylor’s series concept for obliquely incident electromagnetic (EM) waves with arbitrary polarizations. The validity of the suggested method is verified by comparison with the exact solutions of some special profiles for the coating layer. Furthermore, a comparison is made between the proposed method and other commonly used methods in the literature, which confirms that the proposed method is general, fast, and has good convergence toward the solution. Moreover, as an application, we employed the method for optimization of the scattering echo width of a PEC cylinder.

Delineation of Tree Crowns and Tree Species Classification From Full-Waveform Airborne Laser Scanning Data Using 3-D Ellipsoidal Clustering

Individual tree crowns can be delineated from dense airborne laser scanning (ALS) data and their species can be classified from the spatial distribution and other variables derived from the ALS data within each tree crown. This study reports a new clustering approach to delineate tree crowns in three dimensions (3-D) based on ellipsoidal tree crown models (i.e., ellipsoidal clustering). An important feature of this approach is the aim to derive information also about the understory vegetation. The tree crowns are delineated from echoes derived from full-waveform (fwf) ALS data as well as discrete return ALS data with first and last returns. The ellipsoidal clustering led to an improvement in the identification of tree crowns. FwfALS data offer the possibility to derive also the echo width and the amplitude in addition to the 3-D coordinates of each echo. In this study, tree species are classified from variables describing the fwf (i.e., the mean and standard deviation of the echo amplitude, echo width, and total number of echoes per pulse) and the spatial distribution of the clusters for pine, spruce, birch, oak, alder, and other species. Supervised classification is done for 68 field plots with leave-one-out cross-validation for one field plot at a time. The total accuracy was 71% when using both fwf and spatial variables, 60% when using only spatial variables, and 53% when using discrete return data. The improvement was greatest for discriminating pine and spruce as well as pine and birch.

Electromagnetic scattering from anisotropic plasma-coated perfect electromagnetic conductor cylinders

The scattering of electromagnetic waves by a perfect electromagnetic conductor (PEMC) cylinder coated with a homogeneous plasma anisotropic material is studied in this paper. Both of the transverse electric and the transverse magnetic polarizations of the incident waves have been analyzed and formulated. The presented analysis and formulations are general for any perfect conductor cylinder (PEC, PMC, or PEMC) with general isotropic/anisotropic material coatings that include plasma and metamaterials. The co-polarized and the cross-polarized components of the scattered fields are computed for different cases of the anisotropic plasma coated PEMC cylinders and for an anisotropic plasma column. Bistatic echo widths for the cases of PEMC, PEC (perfect electric conductor) and PMC (perfect magnetic conductor) cores have been computed and compared. The behavior of the monostatic echo width with the variation of the admittance parameter for the co-polarized and the cross polarized fields is also investigated. The comparisons of the computed results of the presented formulations with the published results of some special cases confirm the accuracy of the presented analysis.

Airborne Dual-Wavelength LiDAR Data for Classifying Land Cover

This study demonstrated the potential of using dual-wavelength airborne light detection and ranging (LiDAR) data to classify land cover. Dual-wavelength LiDAR data were acquired from two airborne LiDAR systems that emitted pulses of light in near-infrared (NIR) and middle-infrared (MIR) lasers. The major features of the LiDAR data, such as surface height, echo width, and dual-wavelength amplitude, were used to represent the characteristics of land cover. Based on the major features of land cover, a support vector machine was used to classify six types of suburban land cover: road and gravel, bare soil, low vegetation, high vegetation, roofs, and water bodies. Results show that using dual-wavelength LiDAR-derived information (e.g., amplitudes at NIR and MIR wavelengths) could compensate for the limitations of using single-wavelength LiDAR information (i.e., poor discrimination of low vegetation) when classifying land cover.

Comparison of discrete and full-waveform ALS for dead wood detection

Abstract. The amount of dead wood is a significant parameter for the description and assessment of forest habitat quality under the terms of the Habitats directive and Natura 2000 guidelines. EU member states are obliged by the Natura 2000 regulations to report on habitat quality in a regular interval of six years. To fulfil this task, the areas should be surveyed in the field, which requires an enormous amount of workload if done only by conventional field work. In this study the applicability of airborne laser scanning data as the single data source for the detection of downed trees in forest habitats is investigated. A focus is laid on the comparison of point clouds with only discrete (XYZ) and full-waveform (including echo width) information as input data. In our paper we present an automatic workflow which is able to detect downed trees with high completeness for both data sets (77.8% for discrete and 75.6% for full-waveform data). Due to large amount of false positives, the correctness using discrete ALS data is poorer (63.1%) than for full-waveform data (89.9%). It was found that the quality of the result is also influenced by factors such as dimension, state of decay, vegetation density and penetration of the foliage by the laser.

Detection of fallen trees in forested areas using small footprint airborne laser scanning data

Deadwood was identified as an important indicator for habitat condition and biodiversity in forests. The assessment of downed trees is therefore part of sustainable forest management and ecological monitoring. However, manual quantification of deadwood in forests is challenging, time consuming, and considered cost-inefficient. Full-waveform airborne laser scanning (FWF-ALS) can be used to support the assessment process. The amplitude and width of the backscattered pulses contain information on the properties of the surface. We used these observations for the identification of downed trees in a Natura2000 forest site. A high density FWF-ALS data set was acquired under leaf-off conditions. Echo width and type (i.e., first, intermediate, and last) information as well as normalized echo heights were used to filter the point cloud and derive a digital height model (DHM). This DHM depicts downed stems as line-like features. Image processing was applied to derive and refine regions representing fallen trees. Terrestrial reference data consisting of locations and dimensions of downed trees, as well as state of decay were used for evaluation. Direct identification of downed trees in FWF-ALS point clouds was possible (completeness 75%, correctness 90%), but it was influenced by factors such as dimension, state of decay, vegetation density, and penetration of the laser.

CONDITIONAL RANDOM FIELDS FOR THE CLASSIFICATION OF LIDAR POINT CLOUDS

Abstract. In this paper we propose a probabilistic supervised classification algorithm for LiDAR (Light Detection And Ranging) point clouds. Several object classes (i.e. ground, building and vegetation) can be separated reliably by considering each point's neighbourhood. Based on Conditional Random Fields (CRF) this contextual information can be incorporated into classification process in order to improve results. Since we want to perform a point-wise classification, no primarily segmentation is needed. Therefore, each 3D point is regarded as a graph's node, whereas edges represent links to the nearest neighbours. Both nodes and edges are associated with features and have effect on the classification. We use some features available from full waveform technology such as amplitude, echo width and number of echoes as well as some extracted geometrical features. The aim of the paper is to describe the CRF model set-up for irregular point clouds, present the features used for classification, and to discuss some results. The resulting overall accuracy is about 94 %.

Characterization of mobile LiDAR data collected with multiple echoes per pulse from crowns during foliation

As a state-of-the-art technology for fine-scale forest investigation, mobile terrestrial light detection and ranging (LiDAR), also referred to as mobile laser scanning (MLS), recently has been increasingly exploited to improve its performance on this task. One potential solution is to apply special MLS systems with the capability of collecting multiple echoes per pulse (multi-echoes, for short) from canopies. The methodologies of this rationale turned out to perform better but still insufficiently for canopy properties retrieval, owing to their common defective premise. That is, the knowledge of the characteristics of MLS scan data comprising multi-echoes, so far, is in shortage, especially when regarding the dynamic process of tree foliation. As a pioneering work for this challenge, this study attempted to comprehensively analyze the characteristics of MLS multi-echoes collected from tree crowns during foliation. Specifically, new stable multi-echoes-related features were deduced under the schematic frame of relative quantification, in both spatial and temporal sense. “Relative” here briefly means the division operation deployed on the attributes of multi-echoes, individually in terms of the number of echoes, echo width and crown volume integrity, between their different return orders. Then, the “relative” schematic was primarily validated for more stably representing crown properties during foliation, based on the real data that was collected by the Sensei MLS system with a maximum of three echoes per pulse. Further, a case of tree species classification was examined using a linear discriminant classifier, and it was testified that the resultant temporal statistical rules of multi-echoes as the reverse clues can enhance the performance of MLS in applications.

Dynamics of radiationless transitions in large molecules: 2. Recurrence cycles in population evolution of the initial state

Evolution of the population of the initial state S is due to radiationless transitions into a dense discrete spectrum of intramolecular vibrations {Rn} (reservoir R) and spontaneous decay of S and Rn by virtue of coupling with a continuous spectrum of intermolecular vibrations (reservoir Q). An exact solution to the dynamic problem has been found, which indicates that in contrast to the Fermi approximation, which reproduces only the exponential decay of S, the evolution consists of recurrence cycles such that Loschmidt echo (partial recovery of the population of S via back transitions from Rn) appears in each cycle. The width and number of echo components depend upon average characteristics of the spectrum of R. With an equidistant spectrum and the same coupling constants of S with all R states, the decay of S is exponential in the initial cycle and the number of echo components and echo width increase proportionally to the cycle number in subsequent cycles. The increase in the width causes mixing of the echo components and the transition from regular to quasi-stochastic dynamics. Deformation of the equidistant spectrum leads to nonexponential decay in the initial cycle, an increase in the number of components, and a reduction in the number of cycles with regular dynamics.

A Novel Approach to Mitigation of Radar Beam Weighting Effect on Coherent Radar Imaging Using VHF Atmospheric Radar

Multiple-receiver coherent radar imaging using very high frequency atmospheric radars is capable of imaging angular power distribution (termed brightness distribution) of the backscattered radar echoes with some inversion algorithms such as Capon's method. The brightness distribution, however, is weighted by the radar beam weighting pattern. Modification of the brightness distribution with a simulated radar beam weighting pattern usually incurs spurious peaks around the edge of the distribution map. In view of this, an approach to mitigation of the radar beam weighting effect on brightness distribution is proposed, thereby giving more reliable estimates of echo center and brightness width. The proposed approach employs several pairs of symmetrically tilted radar beams to determine an effective weighting pattern of the radar beam that is adaptive to the signal-to-noise ratio (SNR) of the data, as well as the transmitting-receiving array configuration. Four radar experiments were carried out with the Middle and Upper atmosphere radar in Japan (34.85°N , 136.11°E) to demonstrate the proposed approach. One of the experiments was exhibited in more detail, and it showed the following: 1) Approximately 14% of the single-center cases turned into double-center situations; 2) the zenith angles of the corrected echo centers were larger than the original ones by ~0.75° on average; and 3) the brightness widths could be larger than the original ones by several degrees, depending on the SNR of the data. Based on these investigations, suitable corrections of the echo center and brightness width are expected to result in different estimates of some atmospheric parameters like scatterer anisotropy and tilt angle of the layer structure.