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Attitude fluctuation of helicopter-borne platform is an important factor influencing the quality of point cloud products from airborne LiDAR, especially the roll and pitch parts. Therefore, we proposed a method to compensate the attitude fluctuation for helicopter-borne laser scanning; an attitude compensation prototype was designed, to eliminate the impact of both the roll and pitch fluctuations on point cloud products. The mechanical structure and control system of the prototype were designed. In order to test the dynamic compensation effectiveness of the prototype for airborne LiDAR, we established a semi-physical simulation system. In the experiment setup, the prototype, a laser rangefinder as well as a position and orientation system (POS) were all mounted on the platform of a three-axis turntable. The inner and middle shafts of the three-axis turntable rotated with sinusoidal movements to simulate the roll and pitch fluctuations of helicopter-borne platform. The x-axis and y-axis frameworks of the prototype were controlled to rotate inversely halves of the measured rotation angles of the simulated attitude fluctuations by the POS. Hence, the emitting orientations of the pulsed laser beams reflected by the scanning mirror embedded in the prototype would not be affected by the dynamic changing of the roll and pitch fluctuations. Total 11 groups of experiments were carried out to verify the control performance and dynamic compensation effectiveness of the compensation prototype under 11 sets of sinusoidal attitude fluctuations with different frequencies and amplitudes. Experimental results show that, under the impact of different frequencies and amplitudes sinusoidal attitude fluctuations, the attitude compensation prototype can always significantly decrease the unfavorable influence of the attitude fluctuations and have good dynamic compensation effectiveness. [ABSTRACT FROM AUTHOR]

Unmanned airborne systems (UAS), particularly the class of UAS referred to as small-unmanned airborne systems (S-UAS), have the potential to revolutionize the science, practice, and role of remote sensing. S-UAS-collected remote sensing data differ from that acquired from larger airborne and space-borne platforms in myriad ways. To provide an indication of the novel remote sensing capabilities that S-UAS are poised to enable and identify research priorities for realizing the full potential of remote sensing from these novel platforms, characteristics of S-UAS platforms and their impact on data and information products are analysed in the context of remote sensing model and the remote sensing communication model. Results indicate that S-UAS will not only enable a range of novel remote sensing capabilities but also present clear challenges to the remote sensing community. These challenges, including increased data volume, a paucity of appropriate analysis approaches, and restrictions on autonomous operation (both regulatory and technological), point towards several near-term research priorities. [ABSTRACT FROM AUTHOR]

Estimating individual tree diameters at breast height (DBH) from delineated crowns and tree heights on the basis of airborne light detection and ranging (LiDAR) data provides a good opportunity for large-scale forest inventory. Generally, ground-based measurements are more accurate, but LiDAR data and derived DBH values can be obtained over larger areas for a relatively smaller cost if a right procedure is developed. A nonlinear least squares (NLS) regression is not an appropriate approach to predict the aboveground biomass (AGB) of individual trees from the estimated DBH because both the response variable and the regressor are subject to measurement errors. In this study, a system of compatible individual tree DBH and AGB error-in-variable models was developed using error-in-variable regression techniques based on both airborne LiDAR and field-measured datasets of individual Picea crassifolia Kom. trees, collected in northwestern China. Two parameter estimation algorithms, i.e., the two-stage error-in-variable model (TSEM) and the nonlinear seemingly unrelated regression (NSUR), were proposed for estimating the parameters in the developed system of compatible individual tree DBH and AGB error-in-variable models. Moreover, two model structures were applied to estimate AGB for comparison purposes: NLS with AGB estimation depending on DBH (NLS&DD) and NLS with AGB estimation not depending on DBH (NLS&NDD). The results showed that both TSEM and NSUR led to almost the same parameter estimates for the developed system. Moreover, the developed system effectively accounted for the inherent correlation between DBH and AGB as well as for the effects of measurement errors in the DBH on the predictions of AGB, whereas NLS&DD and NLS&NDD did not. A leave-one-out cross-validation indicated that the prediction accuracy of the developed system of compatible individual tree DBH and AGB error-in-variable models with NSUR was the highest among those estimated by the four methods evaluated, but, statistically, the accuracy improvement was not significantly different from zero. The main reason might be that, except for the measurement errors, other source errors were ignored in the modeling. This study implies that, overall, the proposed method provides the potential to expand the estimations of both DBH and AGB from individual trees to stands by combining the error-in-variable modeling and LiDAR data and improve their estimation accuracies, but its application needs to be further validated by conducting a systematical uncertainty analysis of various source errors in a future study. [ABSTRACT FROM AUTHOR]

Airborne characterization of ice crystals has important applications. The extreme difficulty of realizing in situ tests requires the development of a complete instrumentation in the laboratory. Such an installation should enable design, development, test, and calibration of instruments in conditions as close as possible to real ones. We present a set of numerical and experimental tools that have been developed to realize ice crystal sensors based on interferometric particle imaging. The set of tools covers the development of complementary simulators for crystal growth and interferometric particle imaging predictions, experimental generation of "programmable" ice crystals, and instrumentation of a freezing column where different techniques as in-focus imaging, out-of-focus imaging, and digital in-line holography can be combined simultaneously for test and calibration. [ABSTRACT FROM AUTHOR]

Airborne GNSS-R campaigns are crucial to the understanding of signal interactions with the Earth's surface. As a consequence of the specific geometric configurations arising during measurements from aircraft, the reflected signals can be difficult to interpret under certain conditions like over strongly attenuating media such as forests, or when the reflected signal is contaminated by the direct signal. For these reasons, there are many cases where the reflectivity is overestimated, or a portion of the dataset has to be flagged as unusable. In this study we present techniques that have been developed to optimize the processing of airborne GNSS-R data, with the goal of improving its accuracy and robustness under non-optimal conditions. This approach is based on the detailed analysis of data produced by the instrument GLORI, which was recorded during an airborne campaign in the south west of France in June 2015. Our technique relies on the improved determination of reflected waveform peaks in the delay dimension, which is related to the loci of the signals contributed by the zone surrounding the specular point. It is shown that when developing techniques for the correct localization of waveform maxima under conditions of surfaces of low reflectivity, and/or contamination from the direct signal, it is possible to correct and extract values corresponding to the real reflectivity of the zone in the neighborhood of the specular point. This algorithm was applied to a reanalysis of the complete campaign dataset, following which the accuracy and sensitivity improved, and the usability of the dataset was improved by 30%. [ABSTRACT FROM AUTHOR]

The first European Space Agency (ESA) and NASA collaboration in an airborne campaign to support ESA's FLuorescence EXplorer (FLEX) mission was conducted in North Carolina, USA during September-October 2013 (FLEX-US 2013) at the Parker Tract Loblolly Pine (LP) Plantation (Plymouth, NC, USA). This campaign combined two unique airborne instrument packages to obtain simultaneous observations of solar-induced fluorescence (SIF), LiDAR-based canopy structural information, visible through shortwave infrared (VSWIR) reflectance spectra, and surface temperature, to advance vegetation studies of carbon cycle dynamics and ecosystem health. We obtained statistically significant results for fluorescence, canopy temperature, and tower fluxes from data collected at four times of day over two consecutive autumn days across an age class chronosequence. Both the red fluorescence (F685) and far-red fluorescence (F740) radiances had highest values at mid-day, but their fluorescence yields exhibited different diurnal responses across LP age classes. The diurnal trends for F685 varied with forest canopy temperature difference (canopy minus air), having a stronger daily amplitude change for young vs. old canopies. The Photochemical Reflectance Index (PRI) was positively correlated with this temperature variable over the diurnal cycle. Tower measurements from mature loblolly stand showed the red/far-red fluorescence ratio was linearly related to canopy light use efficiency (LUE) over the diurnal cycle, but performed even better for the combined morning/afternoon (without midday) observations. This study demonstrates the importance of diurnal observations for interpretation of fluorescence dynamics, the need for red fluorescence to understand canopy physiological processes, and the benefits of combining fluorescence, reflectance, and structure information to clarify canopy function versus structure characteristics for a coniferous forest. [ABSTRACT FROM AUTHOR]

A standard defining a common acoustic classification scheme for dwellings is under development by ISO TC42/SC2/WG29 based on the outcomes of European project COST Action TU0901. The proposal stands on the assumption that in the long term many countries will establish building acoustic requirements using a harmonized set of descriptors, and the hypothesis of an extended low frequency range for airborne sound insulation evaluation is considered. In this scenario most countries will need to estimate the influence on their current airborne sound insulation requirements due to the new descriptor. This can better be evaluated if translation equations between existing and new proposed descriptors can be used. This paper initially evaluates the adequacy of performing such translations based on the geometrical relation between the sound reduction index R and the standardized level difference D nT . This procedure is shown to be acceptable when both descriptors (original and translated) use the same assessment frequency range. For the cases where a different assessment frequency range is considered, a different approach is studied. The paper investigates a statistical method to obtain translation equations between existing and proposed descriptors, based on the analysis of a significant set of in-situ measurements. Several translation equations are proposed, and the effect of the frequency range extension on such translations is studied for two typical building systems such as heavy and lightweight walls. Results show that, although it is possible to propose a single translation equation for each existent descriptor, in some cases the spread around the proposed translation line is significant. It is also observed that the effect of building system is more noticeable if different frequency range descriptors are involved in the translation. This points out the difficulty of obtaining a unique translation equation independent of the building type when the descriptors’ assessment frequency range is not the same. For some existent descriptors, the obtained translation is compared with the theoretical method proposed within the findings of COST TU0901. When considering only lightweight walls or the full data set, there is no good agreement between both methods, but for heavyweight walls they converge. Existing requirements in thirty-two countries have been translated into the proposed descriptor D nT,50 ≈ D nT,w + C 50 – 3150 using the obtained equations. This provides valuable information and an insight for government and building regulation policy makers when updating their legislation. [ABSTRACT FROM AUTHOR]

A multiresolution wavelet analysis of gravity datasets obtained from satellite, airborne, and terrestrial platforms was conducted to estimate their spectral differences and develop a fused free-air gravity model. In this study, fifth-generation Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite model (DIRR5 and TIMR5), airborne, and terrestrial gravity data were compared to estimate their differences within various spectral bands using wavelet decomposition. The datasets were combined in a two-dimensional approximation while taking into account their strongest spectral content to derive a fused gravity model that shows improved long and medium wavelengths over those of the original terrestrial gravity dataset. The studies were focused on two distinct areas, namely, the relatively smooth gravity field along the coast of the southeastern United States and the northern Gulf of Mexico and the highly variable gravity field of eastern Alaska. Results show that changes brought by satellite and airborne data in areas where the gravity field is smooth (southern United States) were negligible (0.1-0.2 mGal). However, in areas where the gravity field is more variable and the terrestrial data density is lower, the contribution of the airborne gravity and satellite data was increasingly significant on the order of several milligals. Results indicate future possibilities in predicting the necessity and contribution of airborne data based on the presented regional analysis scheme. [ABSTRACT FROM AUTHOR]

Underground caves bear a natural hazard due to their possible evolution into a sink hole. Mapping of all existing caves could be useful for general civil usages as natural deposits or tourism and sports. Natural caves exist globally and are typical in karst areas. We investigate the resolution power of modern gravity campaigns to systematically detect all void caves of a minimum size in a given area. Both aerogravity and terrestrial acquisitions are considered. Positioning of the gravity station is fastest with GNSS methods the performance of which is investigated. The estimates are based on a benchmark cave of which the geometry is known precisely through a laser-scan survey. The cave is the Grotta Gigante cave in NE Italy in the classic karst. The gravity acquisition is discussed, where heights have been acquired with dual-frequency geodetic GNSS receivers and Total Station. Height acquisitions with non-geodetic low-cost receivers are shown to be useful, although the error on the gravity field is larger. The cave produces a signal of −1.5 × 10 m/s, with a clear elliptic geometry. We analyze feasibility of airborne gravity acquisitions for the purpose of systematically mapping void caves. It is found that observations from fixed wing aircraft cannot resolve the caves, but observations from slower and low-flying helicopters or drones do. In order to detect the presence of caves the size of the benchmark cave, systematic terrestrial acquisitions require a density of three stations on square 500 by 500 m tiles. The question has a large impact on civil and environmental purposes, since it will allow planning of urban development at a safe distance from subsurface caves. The survey shows that a systematic coverage of the karst would have the benefit to recover the position of all of the greater existing void caves. [ABSTRACT FROM AUTHOR]

This study concerns wide angular sector (higher order) null synthesis in planar irregular sparse antenna arrays when aperture distributed sub-arrays are used to reduce the computational load. A hybrid optimisation tool has been used to find array element excitations to achieve as low as possible sector nulls for the desired sector width. Performance comparisons have been made for three sub-array configurations based on the obtained numerical results. Various interference jamming scenarios have been considered including single and dual sectors for single-dimensional (θ) (1D) and two-dimensional (θ, ϕ) (2D) nulls. The proposed optimisation scheme has shown to be successful for the synthesis of 1D and 2D sector nulls with depths as low as -100 dB for the given configuration with reduced computational time when compared with the full array. The comparison of achieved null depths for different sub-array sizes and convergence time has also been presented and discussed. [ABSTRACT FROM AUTHOR]

The REFLEX 2012 campaign was initiated as part of a training course on the organization of an airborne campaign to support advancement of the understanding of land-atmosphere interaction processes. This article describes the campaign, its objectives and observations, remote as well as in situ. The observations took place at the experimental Las Tiesas farm in an agricultural area in the south of Spain. During the period of ten days, measurements were made to capture the main processes controlling the local and regional land-atmosphere exchanges. Apart from multi-temporal, multi-directional and multi-spatial space-borne and airborne observations, measurements of the local meteorology, energy fluxes, soil temperature profiles, soil moisture profiles, surface temperature, canopy structure as well as leaf-level measurements were carried out. Additional thermo-dynamical monitoring took place at selected sites. After presenting the different types of measurements, some examples are given to illustrate the potential of the observations made. [ABSTRACT FROM AUTHOR]

The work described in this paper is aimed at validating hyperspectral airborne reflectance data collected during the Regional Experiments For Land-atmosphere EXchanges (REFLEX) campaign. Ground reflectance data measured in a vineyard were compared with airborne reflec-tance data. A sampling strategy and subsequent ground data processing had to be devised so as to capture a representative spectral sample of this complex crop. A linear model between airborne and ground data was tried and statistically tested. Results reveal a sound correspondence between ground and airborne reflectance data (R2 > 0.97), validating the atmospheric correction of the latter. [ABSTRACT FROM AUTHOR]

A two-source model for deriving surface energy fluxes and their soil and canopy components was evaluated using multi-angle airborne observations. In the original formulation (TSEB1), a single temperature observation, Priestley-Taylor parameterization and the vegetation fraction are used to derive the component fluxes. When temperature observations are made from different angles, soil and canopy temperatures can be extracted directly. Two dual angle model versions are compared versus TSEB1: one incorporating the Priestley-Taylor parameterization (TSEB2I) and one using the component temperatures directly (TSEB2D), for which data from airborne campaigns over an agricultural area in Spain are used. Validation of TSEB1 versus ground measurements showed RMSD values of 28 and 10 Wm-2 for sensible and latent heat fluxes, respectively. Reasonable agreement between TSEB1 and TSEB2I was found, but a rather low correlation between TSEB1 and TSEB2D was observed. The TSEB2D estimates appear to be more realistic under the given conditions. [ABSTRACT FROM AUTHOR]

This article presents an account of how a technology being transferred from one area of deployment to another entails that specific discourses travel along. In particular, we show that the development of Unmanned Aircraft Systems (UAS, often referred to as drones) is importantly determined by its military progeny, as the civilian context inherits specific discourses from the military context. Contemporary ideas of privacy and security in drone use can be largely traced back to this original context. We show that concepts and their relative importance primarily depend on the discourses that travel together with the technologies on which the concepts aim to act. There is no technological reason for privacy and security to be implemented the way they are, nor can their implementation be explained merely from socio-political or moral discourses. Instead, material and discursive mechanisms successfully enact and reproduce the dominant military viewpoint. [ABSTRACT FROM AUTHOR]

The paper presents selected results of the work carried out at the Air Force Institute of Technology (AFIT) in the scope of computer diagnostic tests of the SWPL-1 Cyklop helmet mounted flight parameters display system. This system has been designed in such a way that it warns the pilot of dangerous situations occurring on board the helicopter and threatening the flight safety (WARN) or faults (FAIL), which inform about a failure in given on-board equipment. The SWPL-1 system has been awarded the Prize of the President of the Republic of Poland during the 17. International Defense Industry Exhibition in Kielce. [ABSTRACT FROM AUTHOR]

Light Detection and Ranging (LiDAR) is an active sensor that can effectively acquire a large number of three-dimensional (3-D) points. LiDAR systems can be equipped on different platforms for different applications, but to integrate the data, point cloud registration is needed to improve geometric consistency. The registration of airborne and terrestrial mobile LiDAR is a challenging task because the point densities and scanning directions differ. We proposed a scheme for the registration of airborne and terrestrial mobile LiDAR using the least squares 3-D surface registration technique to minimize the surfaces between two datasets. To analyze the effect of point density in registration, the simulation data simulated different conditions and estimated the theoretical errors. The test data were the point clouds of the airborne LiDAR system (ALS) and the mobile LiDAR system (MLS), which were acquired by Optech ALTM 3070 and Lynx, respectively. The resulting simulation analysis indicated that the accuracy of registration improved as the density increased. For the test dataset, the registration error of mobile LiDAR between different trajectories improved from 40 cm to 4 cm, and the registration error between ALS and MLS improved from 84 cm to 4 cm. These results indicate that the proposed methods can obtain 5 cm accuracy between ALS and MLS. [ABSTRACT FROM AUTHOR]

This paper presents methods for 3D modeling of railway environments from airborne laser scanning (ALS) and mobile laser scanning (MLS). Conventionally, aerial data such as ALS and aerial images were utilized for 3D model reconstruction. However, 3D model reconstruction only from aerial-view datasets can not meet the requirement of advanced visualization (e.g., walk-through visualization). In this paper, objects in a railway environment such as the ground, railroads, buildings, high voltage powerlines, pylons and so on were reconstructed and visualized in real-life experiments in Kokemaki, Finland. Because of the complex terrain and scenes in railway environments, 3D modeling is challenging, especially for high resolution walk-through visualizations. However, MLS has flexible platforms and provides the possibility of acquiring data in a complex environment in high detail by combining with ALS data to produce complete 3D scene modeling. A procedure from point cloud classification to 3D reconstruction and 3D visualization is introduced, and new solutions are proposed for object extraction, 3D reconstruction, model simplification and final model 3D visualization. Image processing technology is used for the classification, 3D randomized Hough transformations (RHT) are used for the planar detection, and a quadtree approach is used for the ground model simplification. The results are visually analyzed by a comparison with an orthophoto at a 20 cm ground resolution. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite System (GNSS) is a widely used technology for high accuracy positioning in support of many applications, including airborne mapping and sensor georeferencing. The integration of GNSS and an Inertial Navigation System (INS) is a critical navigation component in an airborne mapping system, because it can provide high update rate of solutions, platform attitude information and improved performance (e.g. accuracy, availability). However, GNSS signals can be easily blocked or interfered with, and sometimes the satellite geometry may not be good enough for high accuracy and high reliability applications. Therefore the development of alternative, non-GNSS-based navigation solutions has attracted increased interest in situations where GNSS system availability cannot be guaranteed. Locata is a groundbased navigation system which can transmit ranging signals at several frequencies in the 2.4 GHz Industrial, Scientific and Medical radio bands. Tracking of Locata signals allows additional range-like measurements to be made, which can be processed in a manner not unlike GNSS measurements. Hence the integration of GNSS, INS and Locata can address requirements for seamless precise positioning in many situations. This paper describes a flight test of a GPS+INS+Locata triple-integrated system. The test was conducted in October 2011, during a flight from Bankstown Airport, Sydney, to Cooma Snowy Mountains Airport. The Locata pseudorange measurements were collected and postprocessed to evaluate overall navigation performance and to investigate the limitations of such an integrated system. [ABSTRACT FROM AUTHOR]

Autonomous navigation airborne forward-looking synthetic aperture radar (SAR) observes the anterior inferior wide area with a short cross-track dimensional linear array as azimuth aperture. This is an application scenario that is drastically different from that of side-looking space-borne or air-borne SAR systems, which acquires azimuth synthetic aperture with along-track dimension platform movement. High precision imaging with a combination of pseudo-polar formatting and overlapped sub-aperture algorithm for autonomous navigation airborne forward-looking SAR imaging is presented. With the suggested imaging method, range dimensional imaging is operated with wide band signal compression. Then, 2D pseudo-polar formatting is operated. In the following, azimuth synthetic aperture is divided into several overlapped sub-apertures. Intra sub-aperture IFFT (Inverse Fast Fourier Transform), wave front curvature phase error compensation, and inter sub-aperture IFFT are operated sequentially to finish azimuth high precision imaging. The main advantage of the proposed algorithm is its extremely high precision and low memory cost. The effectiveness and performance of the proposed algorithm are demonstrated with outdoor GBSAR (Ground Based Synthetic Aperture Radar) experiments, which possesses the same imaging geometry as the airborne forward-looking SAR (short azimuth aperture, wide azimuth swath). The profile response of the trihedral angle reflectors, placed in the imaging scene, reconstructed with the proposed imaging algorithm and back projection algorithm are compared and analyzed. [ABSTRACT FROM AUTHOR]

Remote detection of non-native invasive plant species using geospatial imagery may significantly improve monitoring, planning and management practices by eliminating shortfalls, such as observer bias and accessibility involved in ground-based surveys. The use of remote sensing for accurate mapping invasion extent and pattern offers several advantages, including repeatability, large area coverage, complete instead of sub-sampled assessments and greater cost-effectiveness over ground-based methods. It is critical for locating, early mapping and controlling small infestations before they reach economically prohibitive or ecologically significant levels over larger land areas. This study was designed to explore the ability of hyperspectral imagery for mapping infestation of musk thistle (Carduus nutans) on a native grassland during the preflowering stage in mid-April and during the peak flowering stage in mid-June using the support vector machine classifier and to assess and compare the resulting mapping accuracy for these two distinctive phenological stages. Accuracy assessment revealed that the overall accuracies were 79% and 91% for the classified images at preflowering and peak flowering stages, respectively. These results indicate that repeated detection of the infestation extent, as well as infestation severity or intensity, of this noxious weed in a spatial and temporal context is possible using hyperspectral remote sensing imagery [ABSTRACT FROM AUTHOR]

Abstract: The objectives of this study were to estimate above ground forest biomass and identify areas disturbed by selective logging in a 1000ha Brazilian tropical forest in the Antimary State Forest (FEA) using airborne lidar data. The study area consisted of three management units, two of which were unlogged, while the third unit was selectively logged at a low intensity (approximately 10–15m3 ha−1 or 5–8% of total volume). A systematic random sample of fifty 0.25-ha ground plots were measured and used to construct lidar-based regression models for above ground biomass (AGB). A lidar model-assisted approach was used to estimate AGB for the logged and unlogged units (using both synthetic and model-assisted estimators). Two lidar explanatory variables, computed at a spatial resolution of 50m×50m, were used in these predictions: 1) the first quartile height of all above ground returns (P25); and, 2) variance of the height above ground of all returns (VAR). The model-assisted AGB estimator (total 231,589Mg±5,477 SE; mean 231.6Mg ha−1 ±5.5 SE; ±2.4%) was more precise than plot-only simple random sample estimator (total 230,872Mg±10,477 SE; mean 230.9Mg ha−1 ±10.5 SE; ±4.5%). The total and mean AGB estimates obtained using the synthetic estimator (total 231,694Mg; mean 231.7Mg ha−1) were nearly equal those obtained using the model-assisted estimator. In a second component of the analysis lidar metrics were also computed at 1m×1m resolution to identify areas impacted by logging activities within the selectively harvested management unit. A high-resolution canopy relative density model (RDM) was used in GIS to identify and delineate roads, skidtrails, landings and harvested tree gaps. The area impacted by selective logging determined from the RDM was 58.4ha or 15.4% of the total management unit. Using these two spatial resolutions of lidar analyses it was possible to identify differences in AGB in selectively logged areas that had relatively high levels of residual overstory canopy cover. The mean AGB obtained from the synthetic estimator was significantly lower in impacted areas than in undisturbed areas of the selectively logged management unit (p =0.01). [Copyright &y& Elsevier]

The article presents a study which evaluates the performance of a device based on Incoherent Broadband Cavity Enhanced Absorption Spectroscopy (IBB-CEAS), used for sensitive and rapid monitoring of ambient ozone. The study uses direct absorption measurements in a single-pass measurement cell. Results show that improved sensitivity and time response for mapping ozone aboard airborne methods.

Abstract: Two digital Canopy Height Models (CHMs) were generated using the novel Terrestrial Laser Scanning (TLS) technique combined with Airborne Laser Scanning (ALS) data, acquired over a conifer forest. The CHMs were used to extract cross-sections in order to derive surface geometric parameters. Different morphometric models were applied to estimate aerodynamic roughness parameters: the roughness length (z 0) and the displacement height (d 0). The CHMs were also used to derive the area–height relationship of the canopy surface. In order to estimate roughness parameters the observed canopy area–height relationship was modelled by uniform roughness elements of paraboloid or conical shape. The estimated average obstacle density varies between 0.14 and 0.24 for both CHMs. The canopy height distribution is approximately Gaussian, with average heights of about 26m and 21m for CHMs generated with data from TLS and ALS respectively. The estimated values of z 0 and d 0 depend very much on the selected model. It was observed that the Raupach models with parameters tuned to resemble the forest structure of the study area can be applied to a wide range of roughness densities. The cumulative area–height modelling approach also yielded results which are compatible with other models. The results confirm that, to model the upper canopy surface of the conifer forest, both the cone and the paraboloid shapes are fairly appropriate. [Copyright &y& Elsevier]

Airborne Hyperspectral Scanner System (HSS) images of 2.7 m spatial resolution and laboratory/field spectroradiometric data were used for reflectance characterization of synthetic and mineral building materials in southeastern Brazil. An impervious surface image was generated from a five-endmember mixture model with the 37 reflective HSS bands to select sampling sites for creation of a spectral library. Principal component analysis was applied to this library and to the pixels identified as impervious surfaces in the HSS image to identify patterns of spectral response and potential discrimination of urban materials. For both aerial and laboratory/field data sets, PC1 showed high within-class brightness variation due to surface aging, degradation and painting as well as illumination-viewing effects. PC2 indicated an important spectral shape contrast between the near-infrared and the shortwave infrared, which has the potential for discriminating urban materials. When tested with the spectral angle mapper, which reduced the brightness influence on classification and allowed spectral shape comparison, near-infrared and shortwave infrared bands differentiated most of the impervious surfaces studied. Synthetic materials with spectra that declined in magnitude at longer wavelengths (e.g. polyvinyl chloride and painted surfaces) were discriminated from mineral materials with spectra that were flat (e.g. asphalt) or ascending (red tile). Despite having brightness that is distinct from steel and red tile roofs, aluminium was misclassified by spectral angle mapper into the two classes with ascending slope curves. The overall classification accuracy was 74%. [ABSTRACT FROM AUTHOR]

Parametric and nonparametric modeling methods have been widely used for the estimation of forest attributes from airborne laser-scanning data and aerial photographs. However, the methods adopted suffered from complex remote-sensed data structures involving high dimensions, nonlinear relationships, different statistical distributions, and outliers. In this context, artificial neural networks (ANNs) are of interest as they have many clear benefits over conventional modeling methods and could then enhance the accuracy of current forest-inventory methods. This paper examines the ability of common ANN modeling techniques for the prediction of species-specific forest attributes, as exemplified here with the prediction stem volumes (cubic meters per hectare) at the field plot and forest stand levels. Three modeling methods were evaluated, namely, the multilayer perceptron (MLP), support vector regression (SVR), and self-organizing map, and intercompared with the corresponding nonparametric k most similar neighbor method using cross-validated statistical performance indexes. To decrease the number of model-input variables, a multiobjective input-selection method based on genetic algorithm is adopted. The numerical results obtained in the study suggest that ANNs are appropriate and accurate methods for the assessment of species-specific forest attributes, which can be used as alternatives to multivariate linear regression and nonparametric nearest neighbor models. Among the ANN models, SVR and MLP provide the best choices for prediction purposes as they yielded high prediction accuracies for species-specific tree volumes throughout. [ABSTRACT FROM AUTHOR]

Ashe juniper (Juniperus ashei Buchholz) in excessive coverage reduces forage production, interferes with livestock management, and degrades watersheds and wildlife habitat on infested rangelands. The objective of this study was to apply minimum noise fraction (MNF) transformation and different classification techniques to airborne hyperspectral imagery for mapping Ashe juniper infestations. Hyperspectral imagery with 98 usable bands covering a spectral range of 475-845 nm was acquired from two Ashe juniper infested sites in central Texas. MNF transformation was applied to the hyperspectral imagery and the transformed imagery with the first 10 and 20 MNF bands was classified using four hard classifiers: minimum distance, Mahalanobis distance, maximum likelihood and spectral angle mapper (SAM). For comparison, the 10- and 20-band MNF imagery was inversely transformed to noise-reduced 98-band imagery in the original data space, which was also classified using the four classifiers. Accuracy assessment showed that the first 10 MNF bands were sufficient for distinguishing Ashe juniper from associated plant species (mixed woody species and mixed herbaceous species) and other cover types (bare soil and water). Although the 20-band MNF imagery provided better results for some classifications, the increase in overall accuracy was not statistically significant. Overall accuracy on the 10-band MNF imagery varied from 88% for SAM to 93% for minimum distance for site 1 and from 84% for SAM to 94% for maximum likelihood for site 2. The 98-band imagery derived from the 10-band MNF imagery resulted in overall accuracy ranging from 91% for both SAM and Mahalanobis distance to 97% for maximum likelihood for site 1 and from 87% for SAM to 93% for minimum distance for site 2. Although both approaches produced comparable classification results, the MNF imagery required smaller storage space and less computing time. These results indicate that airborne hyperspectral imagery incorporated with image transformation and classification techniques can be a useful tool for mapping Ashe juniper infestations. [ABSTRACT FROM AUTHOR]

The use of an enhanced vision (EV) system in civil aircraft is projected to increase rapidly as the Federal Aviation Administration recently changed the aircraft operating rules under Part 91, revising the flight visibility requirements for conducting operations to civil airports. Operators conducting straight-in instrument approach procedures may now operate below the published approach minimums when using an approval EV system that shows the required visual references on the pilot's Head-Up Display (HUD). An experiment was conducted to evaluate the complementary use of synthetic vision (SV) and EV technologies, focusing on new techniques for integration and/or fusion of synthetic and enhanced vision technologies under the newly adopted FAA rules. The current paper describes a fixed-based simulation experiment that evaluated several display concepts located on the pilot-flying HUD and pilot-not-flying auxiliary display. Results specific to flight crew response, during non-normal events and below minimum visibility, using the fused synthetic/enhanced vision system are discussed here. The results demonstrated that the integrated SV/EV display did not adversely impact detection of lateral navigational solution errors on runway incursions. Additionally, flight crews were able to effectively use existing EV system procedures in their decision-making but found the visual transition from an excellent EV image to natural vision by 100 ft height above touchdown to be awkward. Finally, the addition of scene-linked symbology significantly enhanced flight crew go-around decision-making and reduced the number of illegal landings during approaches in which the required visual references to continue the landing were unavailable. [ABSTRACT FROM AUTHOR]

Synthetic vision systems provide an in-cockpit view of terrain and other hazards via a computer-generated display representation. Two simulator-based experiments examined several display concepts for synthetic vision and evaluated how such displays modulate pilot performance. Experiment 1 (24 general aviation pilots) compared 3 navigational display (ND) concepts: 2D coplanar, 3D, and dual-perspective. Experiment 2 (12 commercial airline pilots) evaluated baseline “blue sky-brown ground” or synthetic-vision-enabled primary flight displays (PFDs) and 3 ND concepts: 2D coplanar with and without synthetic vision and a dynamic multimode rotatable exocentric format. In general, the results pointed to an overall advantage for a dual-perspective format, whether it be stand-alone (Experiment 1) or available via rotatable viewpoints (Experiment 2). Furthermore, Experiment 2 revealed benefits associated with utilizing synthetic vision in both the PFD and ND representations and the value of combined ego- and exocentric presentations. [ABSTRACT FROM AUTHOR]

This article discusses attentional tunneling as one cause of breakdowns in task management. The phenomenon is defined, and it is shown how it can be induced by head-up display location, and compelling 3-dimensional perspective displays. The results of 6 experiments using a synthetic vision display, with or without a highway in the sky (HITS) display are then summarized, as these reveal the attention tunneling phenomenon manifest in the failure to detect unexpected air hazards. Two factors that enhance this phenomenon are identified: location away from the center of visual scan and the presence of the HITS. [ABSTRACT FROM AUTHOR]

This study investigates the use of polarimetric AirSAR (TopSAR) data for estimating biomass and carbon storage of Eucalyptus miniata (Darwin Woolly Butt) and E. tetrodonta (Stringybark) dominated open-forest savannah in the Northern Territory, Australia. Radar backscatter intensity was correlated with basal area for 30 plots within the Wildman River Reserve, Northern Territory. Published allometric relationships were used to convert tree basal area to estimates of above-ground biomass for each of the measured plots. Below-ground biomass was also estimated for these plots, using additional published allometric relationships between below-ground and above-ground biomass. Backscatter of the L-HV channel had the highest regression co-efficient (r2 = 0.92) with ground-based tree basal area measurements. Using a linear regression equation of backscatter intensity for the L-HV channel versus above-ground biomass gave a mean above-ground biomass of 94 t DM (dry mass) ha-1 for the eucalypt dominated vegetation in the Wildman River Reserve, equivalent to 47 t C ha-1 stored in this biomass pool. Estimated below-ground biomass was 28 t C ha-1, giving a total carbon biomass storage for this savannah ecosystem of 75 t C ha-1. The results of this study indicate that the L-HV channel of polarimetric SAR is best suited to model biomass of the tropical savannahs of northern Australia. Given the vast spatial extent of savannah woodlands across north Australia, SAR has the potential to be a major tool in carbon stock assessment, critical for carbon accounting, as well as to contribute to gaining a better understanding of the role the tropical savannahs of northern Australia play in the biochemical cycles of Australia. [ABSTRACT FROM AUTHOR]

Twenty-two participants (12 with prior flying experience and 12 without), performed a series of trials in a low fidelity flight simulator in which they attempted to recover from a series of unusual attitudes. Two display variables were examined: (1) the attitude display was either a traditional head-up display (HUD) with an inside-out motion and pitch ladder, or an Arc-Segmented Attitude Reference (ASAR) display; and (2) a command icon that pointed to the appropriate airplane rotation for recovery direction in pitch and roll was either present or absent. The results revealed that the icon speeded the initial correction and reduced the number of roll reversal errors, while the traditional HUD decreased the total time to recovery. Experienced pilots were more disrupted by the ASAR display than were novices. [ABSTRACT FROM AUTHOR]

Interest in implementing 3D pictorial displays for traffic information in aircraft has been prevalent for decades without any obvious implementation in the cockpit. Our research is focused on design issues for these displays. The purpose of the experiments discussed here was to investigate where and when additional spatial cues, e.g., drop-lines, could contribute to better performance and whether such additions could replace shifts between 2D and 3D presentation for different tasks. Our results show that drop-lines are beneficial in focused attention tasks but are not necessarily beneficial in more integrated tasks. This speaks to the need for an adaptive approach to the presentation of flight situation displays. [ABSTRACT FROM AUTHOR]

Two remarkable supercell storms developed on 22 June 2003 in eastern Nebraska. One of the thunderstorms, located near the town of Aurora, Nebraska, produced the largest known hailstone on record. Receiving far less attention was an adjacent supercell that was equally impressive and is referred to as the Superior, Nebraska, supercell. The two supercells formed during the Bow Echo and Mesoscale Convective Vortex (MCV) Experiment (BAMEX), operated in the spring and summer of 2003. One of the main platforms used during BAMEX was the airborne Electra Doppler Radar (ELDORA). ELDORA was deployed on the Superior supercell several hours after it initiated. Striking in one of the flybys past the storm was the characteristics of the parent circulation. The Superior supercell was associated with a mesocyclone that was the largest (∼9 km in diameter) and the most intense (118 m s-1 velocity differential) ever documented. Ground-based observations from a nearby Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Hastings, Nebraska (UEX), could not resolve the Doppler velocities correctly owing to the intensity of the mesocyclone. The environmental conditions, satellite imagery, and Doppler radar observations of this supercell are presented. [ABSTRACT FROM AUTHOR]

Canopy height distributions were created from small-footprint airborne laser scanner data collected over 133 georeferenced field sample plots and 56 forest stands located in young and mature forest. The plot size was 300–400 m2 and the average stand size was 1.7 ha. Spruce and pine were the dominant tree species. Canopy height distributions were created from both first and last pulse data. The laser data were acquired from two different flying altitudes, i.e., 530–540 and 840–850 m above ground. Height percentiles, mean and maximum height values, coefficients of variation of the heights, and canopy density at different height intervals above the ground were computed from the laser-derived canopy height distributions. Corresponding metrics derived from the two different flying altitudes were compared. Only 1 of 54 metrics derived from the first pulse data differed significantly between flying altitudes. For the last pulse data, the mean values of the height percentiles were up to 50 cm higher than the corresponding values of the low-altitude data. The high-altitude data yielded significantly higher values for most of the canopy density measures. The standard deviation for the differences between high and low flying altitude for each of the metrics was estimated. The standard deviations for the height percentiles ranged from 0.07 to 0.30 cm in the forest stands, indicating a large degree of stability between repeated flight overpasses.The effect of variable flying altitude on mean tree height (hL), stand basal area (G), and stand volume (V) estimated from the laser-derived height and density measures using a two-stage inventory procedure was assessed by randomly combining laser data from the two flying altitudes for each individual sample plot and forest stand. The sample plots were used as training data to calibrate the models. The random assignment was repeated 10,000 times. The results of the 10,000 trials indicated that the precision of the estimated values of hL, G, and V was robust against alterations in flying altitude. [Copyright &y& Elsevier]

Synthetic vision information systems (SVIS) are the next generation of cockpit display systems that will become an integral part of the commercial flight deck in the future. The goal of this study was to evaluate SVIS against conventional glass cockpit displays to assess whether or not SVIS can improve pilot performance, situation awareness (SA), and workload. The evaluation was conducted in a fixed-based laboratory flight simulator located in the Operator Performance Laboratory at the University of Iowa. A total of 12 pilot evaluators hand-flew fairly difficult approaches into the Eagle County, Colorado, airport. Specially designed questionnaires were used in various phases of the flights to estimate workload. S.A. and user preference. Information relating to SA was collected using the Situation Awareness Global Assessment Technique and workload estimates were obtained using the NASA Task Loading Index technique. Eye movement data were collected using a modified IScan ETL 500 system, and analyzed to find a link analysis (an analysis of eye movement transitions between areas of duration of fixations. Flight technical error performance was derived. Analysis results indicate that the SVIS is superior to the conventional displays for the majority of the measures that were obtained in the experiments. [ABSTRACT FROM AUTHOR]

Presents a study which described approaches to detect airborne obstacles on collision course and crossing trajectories in video images captured from an airborne aircraft. Flight maneuvers for collision course and crossing scenarios; Discrimination of hazard from clutters; Detection of collision course object.

Compares the performance of two visually coupled system (VCS) installations in helicopter flight and simulator trials. Benefits of VCS to helicopter effectiveness and pilot workload; Levels of control augmentation of maneuvers performed by pilots; VCS factors that affect the performance of helicopters.

Examines the effects of pictorial detail on the timing of the landing flare in a visual simulation experiment. Consideration of applying artificial outside-world displays to aircraft cockpits; Importance of identifying the needed elements of the pictorial detail; Details of the two elements of the pictorial detail; Visual perception in aircraft approach and landing.

Describes an approach to multisensory display development in fighter plane cockpits. Use of human performance evaluations as a design tool; Progression of the lethality and complexity of aerial weapons systems; Problems with the single sensor-single indicator philosophy display design; Effects of the proliferation of visual displays.

Three prototype displays are contrasted for aircraft navigation and tactical hazard awareness: a conventional 2-D coplanar display, an exocentric (God's eye) 3-D display, and an immersed (pilot's eye) 3-D display coupled with a small scale global display. Strengths and weaknesses of each display type are discussed, related particularly to the ambiguity of perspective displays and to attention allocation problems with dual-display suites. In Experiment 1, 8 pilots flew with each of the displays around an airspace populated by waypoints, hazards, and traffic. Performance measures revealed the anticipated costs and benefits of each display type. In Experiment 2, cognitive engineering techniques of performance and cognitive task analysis were applied to remediate the weaknesses of each display type. Emphasis was placed on display enhancements to resolve 3-D ambiguity and visual momentum and cueing techniques to facilitate attention allocation and switching. Analysis of performance of 27 additional participants in flight path tracking and hazard awareness measures revealed success in application of the cognitive engineering principles, greatly attenuating the weaknesses of each display. [ABSTRACT FROM AUTHOR]

Explores issues involving the integration of multisensory display with automated cockpit display systems. Need for effective human-automation communication and coordination; Introduction of modem automation technology to the flight deck; Efforts to address existing problems on human to machine communication and coordination.

An airborne video system was used to investigate the visible and near-infrared (NIR) spectral properties of soil and vegetation features across a range of common arid landscape types. The four-camera system was equipped with filters of 25mm bandwidth centred on 450nm ('blue'), 550nm ('green'), 650nm ('red') and 770nm ('NIR'). The aim was to determine what vegetation properties could be detected by combining data from the blue part of the spectrum with the green, red and NIR range, thereby utilizing information contained in the first channel of Landsat Thematic Mapper (TM) (450-520nm). Adding information from the blue end of the spectrum did not assist in discriminating between green vegetation and dry vegetation or green vegetation and bare soil. This separation is best done with a red/NIR ratio. Neither was the blue band an improvement over the PD54 red-green perpendicular distance index in distinguishing between soil and vegetation, irrespective of phenological condition. The blue band can help separate soil from dry vegetation when combined with the sum of brightness values in the red and green bands in a perpendicular distance index. These properties of the spectral dataspace lead to a sequential classification procedure by which airborne videography data can be used to measure vegetation components which are much slower to assess with conventional ground-based methods. Videography has great potential for rapidly verifying or calibrating vegetation cover indices derivedfrom satellite data. Vegetation cover derived from classifying high resolution video data acquired from a heterogeneous floodplain area correlated well with vegetation indices computed from contemporary and co-registered TM data. The most effective indices for measuring vegetation cover with TM data are the PD54 index, brightness in the red band and a perpendicular index based on the sum of the red-green bands and the blue band. However, multiple regression indicates that the addition of a red/NIR ratio as an additional predictor of cover does not greatly improve the performance of these indices. [ABSTRACT FROM AUTHOR]

Airborne multispectral videography has become a useful tool for classifying and mapping riparian vegetation because its spectral and digital format has high spatial resolution. This paper explains the processing steps and procedures required to use this type of spectral imagery for riparian vegetation classification and mapping. A description of the Utah State University airborne system is given, along with the image processing steps used for developing finalized products, because these are used in other articles in this volume. Examples of riparian applications using high-resolution imagery are included. [ABSTRACT FROM AUTHOR]