Analysis of full-waveform LiDAR data for classification of an orange orchard scene

Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data capture from the National Airborne Field Experiment in November 2006 using a custom peak-detection procedure and a trust-region-reflective algorithm for fitting Gauss functions. Calibration was carried out using waveforms returned from a road surface, and the backscattering coefficient c was derived for every waveform peak. The processed data were then analysed according to the number of returns detected within each waveform and classified into three classes based on pulse width and c. For single-peak waveforms the scatterplot of c versus pulse width was used to distinguish between ground, grass and orange trees. In the case of multiple returns, the relationship between first (or first plus middle) and last return c values was used to separate ground from other targets. Refinement of this classification, and further sub-classification into grass and orange trees was performed using the c versus pulse width scatterplots of last returns. In all cases the separation was carried out using a decision tree with empirical relationships between the waveform parameters. Ground points were successfully separated from orange tree points. The most difficult class to separate and verify was grass, but those points in general corresponded well with the grass areas identified in the aerial photography. The overall accuracy reached 91%, using photography and relative elevation as ground truth. The overall accuracy for two classes, orange tree and combined class of grass and ground, yielded 95%. Finally, the backscattering coefficient c of single-peak waveforms was also used to derive reflectance values of the three classes. The reflectance of the orange tree class (0.31) and ground class (0.60) are consistent with published values at the wavelength of the Riegl scanner (1550 nm). The grass class reflectance (0.46) falls in between the other two classes as might be expected, as this class has a mixture of the contributions of both vegetation and ground reflectance properties.

Transport timescales and tracer properties in the extratropical UTLS

A comprehensive evaluation of seasonal backward trajectories initialized in the northern hemisphere lowermost stratosphere (LMS) has been performed to investigate the factors that determine the temporal and spatial structure of troposphere-to-stratosphere-transport (TST) and it's impact on the LMS. In particular we explain the fundamental role of the transit time since last TST (tTST) for the chemical composition of the LMS. According to our results the structure of the LMS can be characterized by a layer with tTST<40 days forming a narrow band around the local tropopause. This layer extends about 30 K above the local dynamical tropopause, corresponding to the extratropical tropopause transition layer (ExTL) as identified by CO. The LMS beyond this layer shows a relatively well defined separation as marked by an aprupt transition to longer tTST indicating less frequent mixing and a smaller fraction of tropospheric air. Thus the LMS constitutes a region of two well defined regimes of tropospheric influence. These can be characterized mainly by different transport times from the troposphere and different fractions of tropospheric air. Carbon monoxide (CO) mirrors this structure of tTST due to it's finite lifetime on the order of three months. Water vapour isopleths, on the other hand, do not uniquely indicate TST and are independent of tTST, but are determined by the Lagrangian Cold Point (LCP) of air parcels. Most of the backward trajectories from the LMS experienced their LCP in the tropics and sub-tropics, and TST often occurs 20 days after trajectories have encountered their LCP. Therefore, ExTL properties deduced from CO and H2O provide totally different informations on transport and particular TST for the LMS.

Measurements of NO, NOy, N2O, and O3 during SPURT: implications for transport and chemistry in the lowermost stratosphere

We present measurements of NO, NOy, O3, and N2O within the lowermost stratosphere (LMS) over Europe obtained during the SPURT project. The measurements cover all seasons between November 2001 and July 2003. They span a broad band of latitudes from 30° N to 75° N and a potential temperature range from 290 to 380 K. The measurements represent a comprehensive data set of these tracers and reveal atmospheric transport processes that influence tracer distributions in the LMS. Median mixing ratios of stratospheric tracers in equivalent latitude-potential temperature coordinates show a clear seasonal cycle related to the Brewer-Dobson circulation, with highest values in spring and lowest values in autumn. Vertical tracer profiles show strong gradients at the extratropical tropopause, suggesting that vertical (cross-isentropic) mixing is reduced above the tropopause. Pronounced meridional gradients in the tracer mixing ratios are found on potential temperature surfaces in the LMS. This suggests strongly reduced mixing along isentropes. Concurrent large gradients in static stability in the vertical direction, and of PV in the meridional direction, suggest the presence of a mixing barrier. Seasonal cycles were found in the correlation slopes ΔO3/ΔN2O and ΔNOy/ΔN2O well above the tropopause. Absolute slope values are smallest in spring indicating chemically aged stratospheric air originating from high altitudes and latitudes. Larger values were measured in summer and autumn suggesting that a substantial fraction of air takes a "short-cut" from the tropical tropopause region into the extratropical LMS. The seasonal change in the composition of the LMS has direct implications for the ozone chemistry in this region. Comparisons of measured NO with the critical NO value at which net ozone production changes from negative to positive, imply ozone production up to 20 K above the local tropopause in spring, up to 30 K in summer, and up to 40 K in autumn. Above these heights, and in winter, net ozone production is negative.

Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the SPURT project: an overview

During SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) we performed measurements of a wide range of trace gases with different lifetimes and sink/source characteristics in the northern hemispheric upper troposphere (UT) and lowermost stratosphere (LMS). A large number of in-situ instruments were deployed on board a Learjet 35A, flying at altitudes up to 13.7 km, at times reaching to nearly 380 K potential temperature. Eight measurement campaigns (consisting of a total of 36 flights), distributed over all seasons and typically covering latitudes between 35° N and 75° N in the European longitude sector (10° W–20° E), were performed. Here we present an overview of the project, describing the instrumentation, the encountered meteorological situations during the campaigns and the data set available from SPURT. Measurements were obtained for N2O, CH4, CO, CO2, CFC12, H2, SF6, NO, NOy, O3 and H2O. We illustrate the strength of this new data set by showing mean distributions of the mixing ratios of selected trace gases, using a potential temperature-equivalent latitude coordinate system. The observations reveal that the LMS is most stratospheric in character during spring, with the highest mixing ratios of O3 and NOy and the lowest mixing ratios of N2O and SF6. The lowest mixing ratios of NOy and O3 are observed during autumn, together with the highest mixing ratios of N2O and SF6 indicating a strong tropospheric influence. For H2O, however, the maximum concentrations in the LMS are found during summer, suggesting unique (temperature- and convection-controlled) conditions for this molecule during transport across the tropopause. The SPURT data set is presently the most accurate and complete data set for many trace species in the LMS, and its main value is the simultaneous measurement of a suite of trace gases having different lifetimes and physical-chemical histories. It is thus very well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the UT/LMS, as demonstrated in accompanying and elsewhere published studies.

Determination of eddy-diffusivity in the lowermost stratosphere

We present a 2D-advection-diffusion model that simulates the main transport pathways influencing tracer distributions in the lowermost stratosphere (LMS). The model describes slow diabatic descent of aged stratospheric air, vertical (cross-isentropic) and horizontal (along isentropes) diffusion within the LMS and across the tropopause using equivalent latitude and potential temperature coordinates. Eddy diffusion coefficients parameterize the integral effect of dynamical processes leading to small scale turbulence and mixing. They were specified by matching model simulations to observed CO distributions. Interestingly, the model suggests mixing across isentropes to be more important than horizontal mixing across surfaces of constant equivalent latitude, shining new light on the interplay between various transport mechanisms in the LMS. The model achieves a good description of the small scale tracer features at the tropopause with squared correlation coefficients R2 = 0.72…0.94.

Molecular recognition between functionalized gold nanoparticles and healable, supramolecular polymer blends – a route to property enhancement

A new, healable, supramolecular nanocomposite material has been developed and evaluated. The material comprises a blend of three components: a pyrene-functionalized polyamide, a polydiimide and pyrenefunctionalized gold nanoparticles (P-AuNPs). The polymeric components interact by forming well-defined p–p stacked complexes between p-electron rich pyrenyl residues and p-electron deficient polydiimide residues. Solution studies in the mixed solvent chloroform–hexafluoroisopropanol (6 : 1, v/v) show that mixing the three components (each of which is soluble in isolation), results in the precipitation of a supramolecular, polymer nanocomposite network. The precipitate thus formed can be re-dissolved on heating, with the thermoreversible dissolution/precipitation procedure repeatable over at least 5 cycles. Robust, self-supporting composite films containing up to 15 wt% P-AuNPs could be cast from 2,2,2- trichloroethanol. Addition of as little as 1.25 wt% P-AuNPs resulted in significantly enhanced mechanical properties compared to the supramolecular blend without nanoparticles. The nanocomposites showed a linear increase in both tensile moduli and ultimate tensile strength with increasing P-AuNP content. All compositions up to 10 wt% P-AuNPs exhibited essentially quantitative healing efficiencies. Control experiments on an analogous nanocomposite material containing dodecylamine-functionalized AuNPs (5 wt%) exhibited a tensile modulus approximately half that of the corresponding nanocomposite that incorporated 5 wt% pyrene functionalized-AuNPs, clearly demonstrating the importance of the designed interactions between the gold filler and the supramolecular polymer matrix.

Review of monitoring tools for e-learning platforms

The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The Learning Management System (LMS) is the core of the entire e-learning process along with technology, content, and services. This paper investigates the role of model-driven personalisation support modalities in providing enhanced levels of learning and trusted assimilation in an e-learning delivery context. We present an analysis of the impact of an integrated learning path that an e-learning system may employ to track activities and evaluate the performance of learners.

Beneath a learning management system: understanding the human information interaction in information systems

Studies on learning management systems have largely been technical in nature with an emphasis on the evaluation of the human computer interaction (HCI) processes in using the LMS. This paper reports a study that evaluates the information interaction processes on an eLearning course used in teaching an applied Statistics course. The eLearning course is used as a synonym for information systems. The study explores issues of missing context in stored information in information systems. Using the semiotic framework as a guide, the researchers evaluated an existing eLearning course with the view to proposing a model for designing improved eLearning courses for future eLearning programmes. In this exploratory study, a survey questionnaire is used to collect data from 160 participants on an eLearning course in Statistics in Applied Climatology. The views of the participants are analysed with a focus on only the human information interaction issues. Using the semiotic framework as a guide, syntactic, semantic, pragmatic and social context gaps or problems were identified. The information interactions problems identified include ambiguous instructions, inadequate information, lack of sound, interface design problems among others. These problems affected the quality of new knowledge created by the participants. The researchers thus highlighted the challenges of missing information context when data is stored in an information system. The study concludes by proposing a human information interaction model for improving the information interaction quality issues in the design of eLearning course on learning management platforms and those other information systems.