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Globally, coral reefs are under threat, with many exhibiting degradation or a shift towards algal-dominated regimes following marine heat waves, and other disturbance events. Marginal coral reefs existing under naturally extreme conditions, such as turbid water reefs, may be more resilient than their clear water counterparts as well as offer some insight into how reefs could look in the future under climate change. Here, we surveyed 27 benthic habitats across an environmental stress gradient in the Exmouth Gulf region of north Western Australia immediately following a marine heatwave event. We used multidecadal remotely sensed turbidity (from an in-situ validated dataset) and temperature, to assess how these environmental drivers influence variability in benthic communities and coral morphology. Long-term turbidity and temperature variability were associated with macroalgal colonisation when exceeding a combined threshold. Coral cover was strongly negatively associated with temperature variability, and positively associated with depth, and wave power, while coral morphology diversity was positively associated with turbidity. While moderate turbidity (long-term average ~ 2 mg/L suspended matter) appeared to raise the threshold for coral bleaching and macroalgal dominance, regions with higher temperature variability (> 3.5 °C) appeared to have already reached this threshold. The region with the least turbidity and temperature variability had the highest amount of coral bleaching from a recent heatwave event and moderate levels of both these variables may confer resilience to coral reefs. [ABSTRACT FROM AUTHOR]

We demonstrate a novel application of green nanosilicas (GN), prepared via an environmentally friendly route, in removing volatile organic compounds (VOCs). Herein, we aim to establish GN as viable alternatives to traditional mesoporous silicas for the removal of monoaromatic hydrocarbons (MAHC). The results show that the GN have high extraction efficiencies comparable to those previously reported for mesoporous silicas. It was demonstrated that bespoke GN can be syntheised readily with the ability to tailor their physical properties and MAHC adsorption. In order to understand the MAHC adsorption by GN, their porosity, morphology and pore structure were characterised. It was observed that the combination of broad pore size distribution and, in particular, the presence of meso- and micro-porosity in GN contributed to high MAHC extraction efficiencies and selectivity. Although from a commercial viewpoint, further optimisation of GN is desirable in order to replace traditional sorbents, this work clearly highlights a new family of "green" sorbents, which can be prepared with a substantial reduction in secondary pollution with potential applications in selective gas separation. [ABSTRACT FROM AUTHOR]

Copyright of Photogrammetric Record is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Photogrammetric Record is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Calcium carbonate (E170) is a common food and pharmaceutical additive/ingredient. In addition to a source of calcium, the carbonate has uses including as a colour, acidity regulator and bulking agent. Globally, a range of regulatory agencies and pharmacopoeia control the analyses and specification of additives in food, supplements, pharmaceutical substances and excipients. Accordingly, a range of specifications and analyses exist for calcium carbonate depending on the application and market of the product. In this contribution, we analyse calcium carbonates from geological, synthetic and biogenic sources, focussing on acid insoluble impurities, a test required by current monographs. Analysis of calcium carbonate from different origins may require modification of existing tests to comply with regulatory bodies, due to the variation of impurities specific to the source of the material. We suggest an analytical approach involving centrifugation that improves analytical efficiency (up to 85% time reduction), especially for calcium carbonate of biological origin. [ABSTRACT FROM AUTHOR]

We have proposed a detailed chemical kinetics mechanism for the addition of C2H2 to a (110) diamond surface, which is the fastest growing face. The model contains no adjustable parameters and is based on the hypothesis that diamond surface chemistry may be understood in analogy with gas-phase hydrocarbon chemistry. We calculated a growth rate of 0.03 μm/h, which gives order-of-magnitude agreement with experiments and suggests we have a feasible mechanism for growth on (110) surfaces. [ABSTRACT FROM AUTHOR]

Focuses on a study which examined the effect of gas phase oxygen on chemical vapor deposition diamond growth on platinum substrates. Use of x-ray photoelectron spectroscopy; Decomposition of surface contaminants; Conversion of graphitic species to stable hydrocarbon species.

Presents a study which made in situ mass spectral measurements and x-ray photoelectron spectroscopy measurements at the surface of a diamond film growing on a platinum substrate. Details on the diamond growth experiments; Result of gas-phase measurements; Measurement of the amount and chemical state of the carbon on the substrate; Characteristics of the gas phase chemical kinetics model.

Presents information on a study which examined the thermochemistry of a number of structures on the hydrogenated diamond surface. Methods; Results; Discussion.

The majority of published in-situ stress information in the Australian continent is confined to petroleum provinces where industry technologies facilitate the capture of contemporary crustal stress information. In contrast, the stress pattern of non-petroleum regions such as the Flinders and Mount Lofty Ranges in South Australia, where intraplate deformation is localised, has not been investigated comprehensively so far. The ongoing activities of the mining industry in South Australia has enabled us to access recently drilled boreholes for image logging techniques that have typically been under-utilised by the mineral sector. Herein, we conduct stress analysis by analysing borehole image logs from 16 boreholes in the basement rocks of South Australia as well as two geothermal wells and one coal seam gas well in South Australia's northern Flinders Ranges, the Gawler Craton and the Eyre Peninsula. The resulting dataset of stress orientations is further accomplished by including recent seismological observations, which provide crustal stress information derived from focal mechanism solutions. The results of this study suggest a regional E-W orientation of the maximum horizontal compressive stress that is consistent with numerous observed neotectonic structures in this region. The focal mechanism solutions in this study suggest that the majority of events occur in a thrust faulting stress regime, which is consistent with the observed Quaternary fault scarps. However, our data compilation also indicates the presence of strike-slip and normal faulting stress regimes in the region, which has not been suggested extensively before this study. [ABSTRACT FROM AUTHOR]

The least square plane fitting adjustment method has been widely used for registration of the mobile laser scanning (MLS) point clouds. The inputs for this process are the plane parameters and points of the corresponding planar features. These inputs can be manually and/or automatically extracted from the MLS point clouds. A number of papers have been proposed to automatically extract planar features. They use different criteria to extract planar features and their outputs are slightly different. This will lead to differences in plane parameters values and points of the corresponding features. This research studies and compares the results of the least square plane fitting adjustment process with different inputs obtained by using different segmentation methods (e.g. RANSAC, RDPCA, Cabo, RGPL) and the results from the point to plane approach - an ICP variant. The questions for this research are: (1) which is the more suitable method for registration of MLS sparse point clouds and (2) which is the best segmentation method to obtain the inputs for the plane based MLS point clouds registration? Experiments were conducted with two real MLS point clouds captured by the MDL - Dynascan S250 system. The results show that ICP is less accurate than the least square plane fitting adjustment. It also shows that the accuracy of the plane based registration process is highly correlated with the mean errors of the extracted planar features and the plane parameters. The conclusion is that the RGPL method seems to be the best methods for planar surfaces extraction in MLS sparse point clouds for the registration process. [ABSTRACT FROM AUTHOR]

Recording techniques such as laser scanning, photogrammetry and photographic reconstruction are not new to archaeology. However as technology evolves and becomes more readily available such methods are being more regularly employed within a cultural heritage management context, often by people with little experience in using these technologies for heritage applications. For most cultural heritage management practitioners, the awe and lure of technology and the ease with which it can bring archaeology to life can distract from the end game of managing the site on the ground. This paper examines the advantages and disadvantages of laser scanning, photogrammetry and photographic reconstruction in recording, managing and interpreting rock art sites with an emphasis on its practical applications to the field of heritage management. Using a case study from West Angelas in the East Pilbara region of Western Australia, we will examine how these technologies assist in the practical management of heritage sites, and the significant outputs achieved for Aboriginal stakeholder groups in remote access to, and the interpretation of indigenous heritage sites. [ABSTRACT FROM AUTHOR]

In this work, a new filtering approach is proposed for a fully automatic Digital Terrain Model (DTM) extraction from very high resolution airborne images derived Digital Surface Models (DSMs). Our approach represents an enhancement of the existing DTM extraction algorithm Multi-directional and Slope Dependent (MSD) by proposing parameters that are more reliable for the selection of ground pixels and the pixelwise classification. To achieve this, four main steps are implemented: Firstly, 8 well-distributed scanlines are used to search for minima as a ground point within a pre-defined filtering window size. These selected ground points are stored with their positions on a 2D surface to create a network of ground points. Then, an initial DTM is created using an interpolation method to fill the gaps in the 2D surface. Afterwards, a pixel to pixel comparison between the initial DTM and the original DSM is performed utilising pixelwise classification of ground and non-ground pixels by applying a vertical height threshold. Finally, the pixels classified as non-ground are removed and the remaining holes are filled. The approach is evaluated using the Vaihingen benchmark dataset provided by the ISPRS working group III / 4. The evaluation includes the comparison of our approach, denoted as Network of Ground Points (NGPs) algorithm, with the DTM created based on MSD as well as a reference DTM generated from LiDAR data. The results show that our proposed approach over performs the MSD approach. [ABSTRACT FROM AUTHOR]

Many different forms of sensor fusion have been proposed each with its own niche. We propose a method of fusing multiple different sensor types. Our approach is built on the discrete belief propagation to fuse photogrammetry with GPS to generate three-dimensional (3D) point clouds. We propose using a non-parametric belief propagation similar to Sudderth et al’s work to fuse different sensors. This technique allows continuous variables to be used, is trivially parallel making it suitable for modern many-core processors, and easily accommodates varying types and combinations of sensors. By defining the relationships between common sensors, a graph containing sensor readings can be automatically generated from sensor data without knowing a priori the availability or reliability of the sensors. This allows the use of unreliable sensors which firstly, may start and stop providing data at any time and secondly, the integration of new sensor types simply by defining their relationship with existing sensors. These features allow a flexible framework to be developed which is suitable for many tasks. Using an abstract algorithm, we can instead focus on the relationships between sensors. Where possible we use the existing relationships between sensors rather than developing new ones. These relationships are used in a belief propagation algorithm to calculate the marginal probabilities of the network. In this paper, we present the initial results from this technique and the intended course for future work. [ABSTRACT FROM AUTHOR]

This paper investigates the problems of outliers and/or noise in surface segmentation and proposes a statistically robust segmentation algorithm for laser scanning 3-D point cloud data. Principal component analysis (PCA)-based local saliency features, e.g., normal and curvature, have been frequently used in many ways for point cloud segmentation. However, PCA is sensitive to outliers; saliency features from PCA are nonrobust and inaccurate in the presence of outliers; consequently, segmentation results can be erroneous and unreliable. As a remedy, robust techniques, e.g., RANdom SAmple Consensus (RANSAC), and/or robust versions of PCA (RPCA) have been proposed. However, RANSAC is influenced by the well-known swamping effect, and RPCA methods are computationally intensive for point cloud processing. We propose a region growing based robust segmentation algorithm that uses a recently introduced maximum consistency with minimum distance based robust diagnostic PCA (RDPCA) approach to get robust saliency features. Experiments using synthetic and laser scanning data sets show that the RDPCA-based method has an intrinsic ability to deal with outlier- and/or noise-contaminated data. Results for a synthetic data set show that RDPCA is 105 times faster than RPCA and gives more accurate and robust results when compared with other segmentation methods. Compared with RANSAC and RPCA based methods, RDPCA takes almost the same time as RANSAC, but RANSAC results are markedly worse than RPCA and RDPCA results. Coupled with a segment merging algorithm, the proposed method is efficient for huge volumes of point cloud data consisting of complex objects surfaces from mobile, terrestrial, and aerial laser scanning systems. [ABSTRACT FROM PUBLISHER]

In recent years, 3D city models are in high demand by many public and private organisations, and the steadily growing capacity in both quality and quantity are increasing demand. The quality evaluation of these 3D models is a relevant issue both from the scientific and practical points of view. In this paper, we present a method for the quality evaluation of 3D building models which are reconstructed automatically from terrestrial laser scanning (TLS) data based on an attributed building grammar. The entire evaluation process has been performed in all the three dimensions in terms of completeness and correctness of the reconstruction. Six quality measures are introduced to apply on four datasets of reconstructed building models in order to describe the quality of the automatic reconstruction, and also are assessed on their validity from the evaluation point of view. [ABSTRACT FROM AUTHOR]

The demand for accurate spatial data has been increasing rapidly in recent years. Mobile laser scanning (MLS) systems have become a mainstream technology for measuring 3D spatial data. In a MLS point cloud, the point clouds densities of captured point clouds of interest features can vary: they can be sparse and heterogeneous or they can be dense. This is caused by several factors such as the speed of the carrier vehicle and the specifications of the laser scanner(s). The MLS point cloud data needs to be processed to get meaningful information e.g. segmentation can be used to find meaningful features (planes, corners etc.) that can be used as the inputs for many processing steps (e.g. registration, modelling) that are more difficult when just using the point cloud. Planar features are dominating in manmade environments and they are widely used in point clouds registration and calibration processes. There are several approaches for segmentation and extraction of planar objects available, however the proposed methods do not focus on properly segment MLS point clouds automatically considering the different point densities. This research presents the extension of the segmentation method based on planarity of the features. This proposed method was verified using both simulated and real MLS point cloud datasets. The results show that planar objects in MLS point clouds can be properly segmented and extracted by the proposed segmentation method. [ABSTRACT FROM AUTHOR]

This paper introduces robust algorithms for extracting the ground points in laser scanning 3-D point cloud data. Global polynomial functions have been used for filtering algorithms for point cloud data; however, it is not suitable as it may lead to bias for the filtering algorithms and can cause misclassification errors when many different objects are present. In this paper, robust statistical approaches are coupled with locally weighted 2-D regression that fits without any predefined global function for the variables of interest. Algorithms are performed iteratively on 2-D profiles: $x-z$ and $y-z$. The $z$ (elevation) values are robustly down weighted based on the residuals for the fitted points. The new set of down-weighted $z$ values, along with the corresponding $x$ (or $y$) values, is used to get a new fit for the lower surface level. The process of fitting and down weighting continues until the difference between two consecutive fits is insignificant. The final fit is the required ground level, and the ground surface points are those that fall within the ground level and the level after adding some threshold value with the ground level for $z$ values. Experimental results are compared with the recently proposed segmentation method through simulated and real mobile laser scanning point clouds from urban areas that include many objects that appear in road scenes such as short walls, large buildings, electric poles, signposts, and cars. Results show that the proposed robust methods efficiently extract ground surface points with better than 97% accuracy. [ABSTRACT FROM PUBLISHER]

Silica is the second most abundant biomineral being exceeded in nature only by biogenic CaCO. Many land plants (such as rice, cereals, cucumber, etc.) deposit silica in significant amounts to reinforce their tissues and as a systematic response to pathogen attack. One of the most ancient species of living vascular plants, Equisetum arvense is also able to take up and accumulate silica in all parts of the plant. Numerous methods have been developed for elimination of the organic material and/or metal ions present in plant material to isolate biogenic silica. However, depending on the chemical and/or physical treatment applied to branch or stem from Equisetum arvense; other mineral forms such glass-type materials (i.e. CaSiO), salts (i.e. KCl) or luminescent materials can also be isolated from the plant material. In the current contribution, we show the chemical and/or thermal routes that lead to the formation of a number of different mineral types in addition to biogenic silica. [ABSTRACT FROM AUTHOR]

High spatial resolution satellite imaging has the advantages of both fine scale and large coverage that indicate the potential for measuring forest morphologies. However, because of the aerial view, imaging has limited capacity of explicitly deriving the under-crown structural parameters. A possible solution is to explore the relationships between this kind of variables such as crown height (CH) and the feature parameters readily derived from the satellite images. However, field sampling of the training data is not a trivial task. To handle this issue, this study attempted the state-of-the-art remote sensing technology of vehicle-based mobile laser scanning (MLS) for collecting the sample data. Evaluation for the case of the Scots pine (Pinus sylvestris) trees has preliminarily validated the plan. That is, MLS mapping enabled the parameter of CH to be estimated from WorldView-2 panchromatic images. [ABSTRACT FROM PUBLISHER]

The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account. [ABSTRACT FROM AUTHOR]

Pyrite framboid in sedimentary rocks could be concerned with arsenic contamination in groundwater of acidic environment and has been studied for the formation process of its unique morphology. However, not much has been discussed about the formation process based on the heavy-metal distribution in pyrite framboids and their aggregates. To reveal the formation process of pyrite framboids and their aggregates, mudstone from the Late Cretaceous Hakobuchi Group, central Hokkaido, Japan, are investigated for mode, petrographical, mineralogical, and micro-PIXE (particle-induced X-ray emission) analysis in this study. Spherical and sub-spherical pyrite framboids observed in polyframboids can be divided into two types based on the diameter of framboids ( D) and the average diameter of microcrystals ( d) within framboids: type 1, ranging from 2 to 9 μm and from 0.4 to 0.9 μm, respectively, and type 2, ranging from 8 to 50 μm and from 0.5 to 1.8 μm, respectively. Based on the quantitative traverse analyses and 2-D elemental mapping results by micro-PIXE, heterogeneities in the concentrations of heavy metals within the analyzed aggregations of pyrite are exhibited. On the basis of the As and Pb zoning patterns, the time range and chronological stages of pyrite-aggregation growth are revealed. [ABSTRACT FROM AUTHOR]

Biomineral formation is widespread in nature, and occurs in bacteria, single-celled protists, plants, invertebrates, and vertebrates. Minerals formed in the biological environment often show unusual physical properties (e.g. strength, degree of hydration) and often have structures that exhibit order on many length scales. Biosilica, found in single-celled organisms through to higher plants and primitive animals (sponges), is formed from an environment that is undersaturated with respect to silicon, and under conditions of approximately neutral pH and relatively low temperatures of 4−40 °C compared to those used industrially. Formation of the mineral may occur intracellularly or extracellularly, and specific biochemical locations for mineral deposition that include lipids, proteins and carbohydrates are known. In most cases, the formation of the mineral phase is linked to cellular processes, an understanding of which could lead to the design of new materials for biomedical, optical and other applications. In this contribution, we describe the aqueous chemistry of silica, from uncondensed monomers through to colloidal particles and 3D structures, that is relevant to the environment from which the biomineral forms. We then describe the chemistry of silica formation from alkoxides such as tetraethoxysilane, as this and other silanes have been used to study the chemistry of silica formation using silicatein, and such precursors are often used in the preparation of silicas for technological applications. The focus of this article is on the methods, experimental and computational, by which the process of silica formation can be studied, with an emphasis on speciation. [ABSTRACT FROM AUTHOR]

We present a novel closed-form expression of positional uncertainty measured by a near-monostatic and time-of-flight laser range finder with consideration of its measurement uncertainties. An explicit form of the angular variance of the estimated surface normal vector is also derived. This expression is useful for the precise estimation of the surface normal vector and the outlier detection for finding correspondence in order to register multiple 3D point clouds. Two practical algorithms using these expressions are presented: a method for finding optimal local neighborhood size which minimizes the variance of the estimated normal vector and a resampling method of point clouds. [ABSTRACT FROM AUTHOR]

Considerable research has been directed toward identifying the mechanisms involved in biosilicification to understand and possibly mimic the process for the production of superior silica-based materials while simultaneously minimizing pollution and energy costs. Molecules isolated from diatoms and, most recently sponges, thought to be key to this process contain polyamines with a propylamine backbone and variable levels of methylation. In a chemical approach to understanding the role of amine (especially propylamine) structures in silicification we have explored three key structural features: (i) the degree of polymerization, (ii) the level of amine methylation, and (iii) the size of the amine chain spacers. In this article, we show that there are two factors critical to their function: the ability of the amines to produce microemulsions and the presence of charged and uncharged amine groups within a molecule, with the latter feature helping to catalyze silicic acid condensation by a proton donor/acceptor mechanism. The understanding of amine-silicate interactions obtained from this study has enabled the controlled preparation of hollow and nonporous siliceous materials under mild conditions (circumneutral pH, room temperature, and in all aqueous systems) possibly compatible with the conditions used by biosystems. The "rules" identified from our study were further used predictively to modulate the activity of a given amine. We believe that the outcomes of the present contribution will form the basis for an approach to controlling the growth of inorganic materials by using tailor-made organic molecules. [ABSTRACT FROM AUTHOR]

Silica skeletal architectures in diatoms are characterized by remarkable morphological and nanostructural details. Silk proteins from spiders and silkworms form strong and intricate self-assembling fibrous biomaterials in nature. We combined the features of silk with biosilica through the design, synthesis, and characterization of a novel family of chimeric proteins for subsequent use in model materials forming reactions. The domains from the major ampullate spidroin 1 (MaSp1) protein of Nephila clavipes spider dragline silk provide control over structural and morphological details because it can be self-assembled through diverse processing methods including film casting and fiber electrospinning. Biosilica nanostructures in diatoms are formed in aqueous ambient conditions at neutral pH and low temperatures. The R5 peptide derived from the silaff in protein of Cylindrotheca fusiformis induces and regulates silica precipitation in the chimeric protein designs under similar ambient conditions. Whereas mineralization reactions performed in the presence of R5 peptide alone form silica particles with a size distribution of 0.5-10 μm in diameter, reactions performed in the presence of the new fusion proteins generate nanocomposite materials containing silica particles with a narrower size distribution of 0.5-2 μm in diameter. Furthermore, we demonstrate that composite morphology and structure could be regulated by controlling processing conditions to produce films and fibers. These results suggest that the chimeric protein provides new options for processing and control over silica particle sizes, important benefits for biomedical and specialty materials, particularly in light of the all aqueous processing and the nanocomposite features of these new materials. [ABSTRACT FROM AUTHOR]

Examines the thermochemistry on a fluorinated diamond (111) surface. Evaluation of performed calculations of mechanisms for growth of diamond on fluorinated diamond surfaces; Presentation of steric repulsion between neighboring fluoride atoms on a fluorinated surface; Implications of the absence of hydrogen for the growth of diamond on a fluorinated surface.

The last decade has seen an exponential increase in the application of unmanned aerial vehicles (UAVs) to ecological monitoring research, though with little standardisation or comparability in methodological approaches and research aims. We reviewed the international peer-reviewed literature in order to explore the potential limitations on the feasibility of UAV-use in the monitoring of ecological restoration, and examined how they might be mitigated to maximise the quality, reliability and comparability of UAV-generated data. We found little evidence of translational research applying UAV-based approaches to ecological restoration, with less than 7% of 2133 published UAV monitoring studies centred around ecological restoration. Of the 48 studies, > 65% had been published in the three years preceding this study. Where studies utilised UAVs for rehabilitation or restoration applications, there was a strong propensity for single-sensor monitoring using commercially available RPAs fitted with the modest-resolution RGB sensors available. There was a strong positive correlation between the use of complex and expensive sensors (e.g., LiDAR, thermal cameras, hyperspectral sensors) and the complexity of chosen image classification techniques (e.g., machine learning), suggesting that cost remains a primary constraint to the wide application of multiple or complex sensors in UAV-based research. We propose that if UAV-acquired data are to represent the future of ecological monitoring, research requires a) consistency in the proven application of different platforms and sensors to the monitoring of target landforms, organisms and ecosystems, underpinned by clearly articulated monitoring goals and outcomes; b) optimization of data analysis techniques and the manner in which data are reported, undertaken in cross-disciplinary partnership with fields such as bioinformatics and machine learning; and c) the development of sound, reasonable and multi-laterally homogenous regulatory and policy framework supporting the application of UAVs to the large-scale and potentially trans-disciplinary ecological applications of the future. [ABSTRACT FROM AUTHOR]

The article presents the development and application of spaceborne Synthetic Aperture Radar (SAR) sensors to monitor Arctic ice coverage. It indicates that sea ice information provided by SAR imagery and incorporated into ice reports and forecasts offers various operational users with mission critical situational awareness. It notes that additional ice characteristics extracted from multi-polarization data can refine the risk assessed against an identified ice hazard.

Registration is an essential procedure for merging point clouds defined in different coordinate systems associated to different scanner positions and orientations. It is usually the first step before the point clouds are further processed to provide spatial information of a scene to support engineering applications. In this paper, a new automatic registration method based on a novel geometric model of a polygonal object is presented. Since the cross section of the shaft of many lamp poles is octagonal, registration based on an octagonal pyramid model is proposed. The presented method only requires a single, common octagonal lamp pole observed in both point clouds, though actual overlap of the point clouds is not strictly required. It can be performed as long as the model parameters can be estimated by fitting the point observations to the model. Moreover, no user interaction is needed to derive approximate values, so the proposed registration can be completely automated. Three independent datasets captured by two scanners were used to verify the method. The registration accuracies in the horizontal and vertical directions were up to 11.7 mm and 4.4 mm at approximately 62 m and 17 m away from the scanner, respectively. With such high accuracies, the estimated registration parameters can serve as a set of initial parameters for fine registration using algorithm such as the iterative closest point (ICP). [ABSTRACT FROM AUTHOR]

Filament-assisted chemical vapor deposition (CVD) diamond film growth on Si(100) was studied using x-ray photoelectron spectroscopy (XPS) to examine the sample at selected intervals during the nucleation and growth processes. The sample was transferred under vacuum from the growth chamber to the attached XPS analysis chamber without exposure to air. Before growth XPS showed that the Si sample is covered by a layer of SiO2 and carbonaceous residue; however, after 15 min of growth both of these substances are removed and replaced by a distinct SiC layer [Si(2p)=100.3 eV and C(1s)=282.7 eV]. [ABSTRACT FROM AUTHOR]