Accurate measurements of P/S ratios at local-regional scale are often challenged by near-distance failure and/or sparse monitoring. During June 2014 - Aug. 2016 (iMUSH project), the XD array was deployed around the Mount St. Helens (MSH, hear and after) within ~150 km of the summit. The array contains ~80 three-component broadband stations, forming a nearly uniform monitoring system that recorded 23 active shots and 407 of M>1 earthquake within the 2-year period. The determined local magnitudes for the shots range from 0.9 to 2.3. Most earthquakes are deep (>10 km) and the shots are 10m below the surface. Due to the complexity of near surface structure, waveforms of the shots have both strong P and S energy on the transverse components, leaving them identical to earthquakes. This study takes advantage of this integrate dataset to systematically evaluates potential contributing factors to the P/S ratio measurements, including: source type (i.e., explosive vs. shear), distance, depth, and station location (i.e., site effect, coverage). We also compared between different frequency ranges, window choices, methods and component choices (i.e., RTZ vs. LQT) that differentiate the shots from the earthquakes. We observed no clear dependence for P-to-S ratio over depth, azimuth nor magnitude, while other parameters could be optimized to isolate contributions from the source. For example, the P-to-S ratios increase with frequency from 4Hz to 18 Hz and shots show much larger increasements than the earthquakes. We suggest that the near-source challenges could be relieved by: 1) use narrow windows to capture early phase and avoid overlap between S-coda and surface wave, 2) use higher frequency range to enhance body wave signal-to-noise ratio and allow for enough period within narrow phase windows, 3) rotate from the RTZ system to LQT system to maximize P wave energy and/or 4) include the transverse (T) component in P-phase energy calculations. With these optimizations, our averaged ratios are consistent throughout all distances (6-160 km) and clearly separate the shots from the earthquakes. In addition, regardless of the source type, the P-to-S ratios also vary with station location, which could be attributable to site effect and local structures.

Inspired by the AAHE Assessment Forum’s Principles for good practice for assessing students’ learning, the author has generated Ten Steps (1992) to Promote a Stronger Emphasis on Student Learning in a Hydrology–Fluid Mechanics Course. Student-Learning must not be focused only about making the connections initially. Instead it should concentrate more about maintaining those connections in the long run. Student learning is fundamentally about a strong bond between the academic establishment and the student citizens of the entire community. Student-Learning is enhanced by the environment. It should take place in the context of a compelling situation that balances curiosity, challenge and opportunity. Student-Learning should have an active search for meaning by the learner – constructing knowledge rather than passively delivering it or receiving it. In other words one should create a Concept Mapping Model instead of a Structured Content Model. Student-Learning is developmental. In other words, it is a cumulative process involving the whole person, who is capable of integrating the new with the old. The settings, the surroundings, the influences of others contribute to successful accomplishments. Student-Learning should be viewed as an effort promoted by individuals who are intrinsically tied to others as social beings, actually interacting as collaborators. Student-Learning is strongly influenced by the educational climate in which learning achievements takes place. Student-Learning requires Action, Communication, Ownership, Reflection and Nurture (ACORN) as suggested by Hawkins and Winter (1997). Student-Learning in reality aims at an educational experience that takes place informally and incidentally, beyond explicit teaching in the lecture hall. Student-Learning is grounded in particular contexts and individual experiences, requiring effort to transfer specific knowledge and skills to other citizens. Student-Learning involves the ability of individuals not only to monitor their own learning, but also be able to enhance learning through collaboration and cooperation. References: Hawkins, P., & Winter, J. (1997). Mastering change: Learning the lessons of the enterprise in higher education initiative. London: Department for Education and Employment.

The Track Zero Charitable Trust (http://trackzero.nz) was founded in early 2018 with the goal of inspiring action on climate change through engagement with the arts. The main motivation is that artistic expression connects on an emotional level in a way that direct communication of science does not. Also, around 80 percent of New Zealanders engage in some way with the arts, a much larger audience than those who take an active interest in science. This presentation discusses the first major activity of TrackZero, a series of public meetings around New Zealand where scientists partnered with local arts practitioners to interact with audiences on the science, on people’s feelings and concerns, and on ways forward to action on adapting to or mitigating climate change. Different communities had different concerns and the range of conversations was rich and varied. While no formal evaluation has been carried out, we provide some general reflections on impact and engagement, and ideas for future activities.

Iron is the fourth most common element found in the earth crust. Although it may not be as important for soil fertility as, e.g., phosphorus, nitrogen and organic matter, its absence would be detrimental to plant growth. At the same time, iron oxides are highly correlated with phosphorus availability. Iron is thus an indicator for soil fertility and the usability of an area for cultivation of crop. A relatively high spectral resolution is needed for mapping iron oxide contents with spectral reflectance data, and remote sensing is the only suitable tool for surveying large areas at a high temporal and spatial interval. Sentinel-2 MSI (MultiSpectral Instrument) is the Landsat-like spatial resolution (10–60 m) super-spectral instrument of the European Space Agency (ESA), aimed at additional data continuity for global land surface monitoring with Landsat and Satellite Pour l’Observation de la Terre (SPOT) missions. Several studies with simulated and real data have been conducted in the last several years to show the potential of Sentinel-2 MSI, including its use for geological remote sensing, mineral mapping in particular. Sentinel-2 has several bands that cover the 0.9 μm iron absorption feature, while space-borne sensors traditionally used for geologic remote sensing, like ASTER and Landsat, had only one band in this feature. In this paper, we show a comparison of Sentinel-2 and AVIRIS to demonstrate the usability of the VNIR bands for mapping the near-infrared iron absorption feature. Next, we present spectral indices for mapping iron minerals that are important in soil fertility and mineral exploration.

With the recent GIEC report about global warming urging humanity to limit the global temperature increase to 2°C maximum, research on the geological storage of carbon dioxide appears more important than ever. However, the injection in geological formations (such as deep saline aquifers and depleted gas/oil fields) of supercritical CO2, stores it in the porosity of the host rock raising legitimate concern about the safety and long-term behavior of such dynamic multiphase hydrosystems. Additionally, the economic and energetic weight of such storage complicates its development at the world scale without strong political incentives. The storage of CO2 in ultramafic formations in some specific contexts appears, on the contrary, as a very appealing technology since it involves the safe mineralization of the carbon by precipitation of carbonates with the major alkaline earth metals (i.e. Mg, Ca…) leached from the formation itself. Moreover, as these rocks contain high amounts of ferrous iron, its oxidation by the water co-injected with CO2 produces dihydrogen, which can be economically valuable rendering the whole process more viable. Large ophiolite formations (Oman, Papua New Guinea, east coast of Adriatic Sea…) are expected to have a storage capacity of several billion tons of CO2 and could produce similar amounts of clean dihydrogen. We present experimental results on the mineral carbonation of natural cores of serpentinites by the continuous percolation of carbon-saturated water. We show that the dimensionless Péclet (relative importance of diffusion and convection processes), and Damköhler (relative importance of convection and chemical processes) numbers as well as the initial geometry of the porosity and permeability control the localization of the silicate dissolution and the carbonate precipitation in the porous medium. We also show that the chemical behavior is principally controlled by the reactivity of calcium-bearing silicates (wollastonite, diopside) and the precipitation of calcite as well as the initial iron content of the different phases. Such results are particularly interesting for the design and the optimization of pilot sites and the development of this technology at industrial scale.

In the subsurface, water content, gas solubility, adsorption on minerals and chemical reactions control gas fluxes between soil and the atmosphere. Because these processes vary in intensity both in time and space, it is very challenging to quantify emissions, specifically when flux measurements are used for detection, identification or monitoring of a subsurface gas source. An experimental setup for gas percolation though soil column experiments under well-controlled conditions was developed and validated at the ECOTRON IleDeFrance research center. Its design included the effect of: i) watering/evaporation cycles, ii) barometric pressure, iii) injection pressure, iv) tracer behaviors and v) plant metabolism. To better understand subsurface processes controlling gas fluxes, we studied transport of multiple tracers across soil columns using long-term and high-resolution monitoring thanks to online low-flow mass-spectrometry. We injected tracer gases into columns containing different porous media, pure sillica sand and zeolite. This set-up allowed us to evaluate the relative contribution of diffusion, solubility and adsorption on various trace gases (SF6, noble gas including Xe). All the experimental data are discussed in conjonction with simulations using the NUFT unsaturated flow and transport code.

Quantification of sulfur dioxide (SO2) emission flux is a fundamental task in volcanology to have insights of the composition and the spatial evolution of volcanic plumes. The ground based InfraRed hyperspectral imager HyperCam, from Telops Company, was deployed during IMAGETNA campaign in 2015 and provided high spatial and spectral resolution images of Mt Etna plume. The spectral range of the hyperspectral imager is [7.7 - 11.8 µm] and the measured images contained 320 x 64 pixels with a spectral resolution of 2 cm-1. To process hyperspectral images in quasi real-time, a fast and reliable radiative transfer retrieval model is required. The LATMOS Atmospheric Retrieval Algorithm (LARA), used to retrieve the slant column densities of SO2, includes an accurate line-by-line radiative transfer model and an efficient minimization algorithm of the Levenberg-Marquardt type. But the calculation time remains too high to infer near real time (NRT) estimation of SO2 fluxes. As first, to reach NRT target, a classification methodology of the brightness temperature spectra was developed and then applied on each measured sequence to significantly decrease the processing time. One image previously took a week of calculation to be retrieved. The classification of the spectra, which takes a couple of hours, allows the retrieval of a complete measurement sequence of the field campaign (~400 images) in only two days. The accuracy of the methodology was confirmed, by comparing the SO2 slant column density images obtained after classification with the one obtained by the accurate and time expensive pixel by pixel retrieval processing. The LARA model, the spectra classification methodology and a comparison of the results will be presented.

The 1755 Lisbon earthquake triggered the largest historical tsunami ever registered in Western Europe. Despite the recent efforts to better understand this event, there are still questions to be answered. Understanding the past tsunami intensity is key to assessing tsunami hazard. Sedimentary imprints are the only evidence in the geological record able to quantify onshore tsunami flow characteristics through inverse modelling. On the other hand, forward numerical modelling is a powerful tool capable of simulating tsunami hydrodynamics and the induced sediment transport. This work presents results from inverse and forward modelling in order to assess tsunami characteristics onshore. The study site is located on the Portuguese southern coast, at Salgados lowland where inverse modelling was performed using TsuSedMod (Jaffe and Gelfenbaum, 2007, Sedimentary Geology) based on four Livingstone sediment cores. Forward modelling including tsunami generation and propagation was performed respectively using the methods of Okada (1985, Bulletin of the Seismological Society of America) and Delft3D-FLOW. Onshore topography was corrected for the 1755 scenario based on extensive deposit thickness data. The tsunami source was chosen based on recent results from the same authors that pointed to a good correlation between modeled and field tsunami data considering Marques de Pombal fault. Results from inverse model show tsunami onshore average speed varying from 7.3 up to 9.3 m/s and shear velocities from 0.52 up to 0.66 m/s. Varying the bottom roughness results in the forward model result in average flow velocities between 7.0 and 8.0 m/s, induced by a 3-meter high tsunami at 50 m depth. The good agreement between forward and inverse model estimates of tsunami velocity highlights the potential of numerical modelling (coupled with geological records) to improve the understanding of historical events. Additional research on correlating modelling and geological data is needed and will likely lead to a better understanding of the effects of similar events and contribute to the ability to assess tsunami hazard and coastal vulnerability. Acknowledgements: Work supported by Instituto Dom Luiz and by project OnOff ‑ PTDC/CTA‑GEO/28941/2017 – financed by FCT

This study uses gravity data to investigate crustal structure in the region of the Galapagos triple junction where the westward propagating Cocos-Nazca rift (CNR) approaches the East Pacific Rise (EPR) and forms the northern boundary of the Galapagos micro plate. Shipboard and global gravity data are analyzed from 104˚W to 96˚W and 0˚ to 4˚N. In May 2018, the high-resolution gravity data were collected along ship tracks that run across the entire width of the Galapagos gore from the tip of the CNR at ~101.7˚W to 98.5˚W. Residual mantle Bouguer anomaly (RMBA) was calculated by removing the effects of water-crust, crust-mantle, and lithospheric cooling from the free-air anomaly (FAA). We also calculated a model of gravity-derived crustal thickness by downward continuation of the RMBA, as well as a model of non-isostatic topography by removing the topographic effects of thermal subsidence and crustal thickness variations. The results reveal several distinctive features in gravity and crustal structure: (1) The eastern flank of the EPR has systematic shallower topography and more negative RMBA than the conjugate western flank, reflecting regional density variations. (2) On the eastern flank of the EPR, the region south of the Galapagos gore is associated with more negative RMBA than the conjugate region to the north, possibly reflecting closer proximity to the Galapagos hotspot in the southern region. (3) The first ~100 km behind the propagating CNR tip (~101.7˚W to 100.8˚W) is associated with more positive RMBA (up to ~35 mGal) than the CNR rift between ~100.8˚W and 98.5˚W, suggesting locally thinner crust (up to ~1.5 – 2 km). East of 98.5˚W along the CNR, RMBA decreases gradually towards the Galapagos hotspot. (4) A region of local high topography on the southern boundary of the Galapagos microplate, where fresh basalts were sampled, is associated with negative RMBA centered at ~101.6˚W and 1.3˚N, indicating local relatively thick crust. (5) Within our study area, the CNR crust shows shallower average off-axis topography and more negative average RMBA than the EPR crust of corresponding age, which is consistent with a model of isostatic compensation of average thicker CNR crust than the surrounding EPR crust, possibly reflecting Galapagos hotspot effects.

Subtropical cyclones (STCs) are characterized by a hybrid structure sharing tropical and extratropical features. The impacts of this kind of cyclones are similar to the generated by tropical storms or even hurricanes, leading to widespread social damage and great economic losses. Carrying out accurate simulations becomes key for a forecast improvement of these extreme events. In this study, several STCs that hit the northeastern Atlantic coasts and experimented a transition into tropical storms (Delta 2005) or even hurricanes (Vince 2005 and Ophelia 2017) are assessed by means of simulations using the high-resolution HARMONIE-AROME model. This model is developed and operated at 2.5 km resolution through the collaboration of the 10 European National Meteorological Services (NMS) that are part of the international research program HIRLAM together with the 16 countries that comprise the ALADIN consortium. The HARMONIE-AROME model has a convection-permitting configuration and uses a non-hydrostatic spectral dynamical core with a semi-Lagrangian and semi-implicit discretization of the equations. In this way, more realistic results are obtained, which allows providing an added value to the study of tropical transitions.

The carbonate dissolution plays a major role in the atmospheric CO2 sink and in the riverine transfer of dissolved inorganic carbon from the atmosphere to the critical zone and to the oceans. In this context, the Baget watershed (13.25 km2, altitude 950 m), essentially forested and weakly exposed to local anthropogenic pollution, drains a karst area in the Pyrenees mountains. It has been monitored for more than 40 years to better understand the impact of global changes on carbonate dissolution and hydro-chemistry of streamwaters. The mean annual precipitation exceeds 1500 mm and the air temperature average is 12°C. Calcareous dominates the lithology (around 2/3 of the area), with some flysh and schists. This experimental catchment belongs to the French Karst Network, to the French (OZCAR) and European (LTER) Research Infrastructures. Based on the hydrochemistry survey since 1978, the results focus on carbonate dissolution, stream water chemistry (mainly Ca, Mg and alkalinity) and calcite saturation index (SI) in relation with pCO2, temperature (T) and river discharge (Q). We analysed the long term trends of the instantaneous values but also of the inter-annual fluctuations of the mean monthly values. The long-term hydrochemical survey allows to evidence a net increasing trend in [Ca2++Mg2+] and [HCO3-] that could be related to an increase in air temperature and a decrease in pCO2 and discharge. Indeed, changes in vegetation cover over the period might have been another controlling factor that is currently investigated. Furthermore, mean monthly values based on the long-term trends allow to understand the dynamic of carbonate dissolution and to identify the main key controlling factors such as the water amount (discharge) and the air temperature, which influences pCO2 production. Lastly, the influence of the drainage relative to minor lithology could be evidenced particularly during low water period by an increased proportion of [SO42-] to [HCO3- ] in stream water, due to the relative substitution of [H2CO3] by [H2SO4] from pyrite oxydation.

Continental flood basalts (CFB) in the Karoo large igneous province have been divided into the North and South Karoo groups. Picrites from the Luenha river, Mozambique, have been shown to represent the primitive mantle-like end-member required to explain the geochemical characteristics of the North Karoo CFBs, which have elevated ΔNb compared to the South Karoo CFBs. These picrites exhibit a narrow range of bulk-rock Nd isotope compositions (εNd180Ma -2.0 to +1.4) but a wide range of bulk-rock, plagioclase and groundmass Sr isotope compositions (full range 87Sr/86Sr180Ma 0.704096-0.71061), extending to high values suggestive of crustal contamination in the origin of these rocks. Despite this, preliminary O isotope data for olivine from one sample with elevated 87Sr/86Sr show uniform, mantle-like δ18O values (4.68±0.38‰ to 5.53±0.37‰). New O isotope data to be acquired in November 2019 on the NordSIM Cameca IMS 1280 ion microprobe will determine the O isotope composition of a sample inferred to most closely represent the parental magma as well as test the intra- and inter-sample O-isotopic variability of these picrites. Combined with the available bulk-rock and plagioclase phenocryst compositions, these data allow us to constrain the progress of crustal contamination and evaluate the homogeneity of the parental magmas. Most importantly, we aim to distinguish between the effects upon the samples of crustal contamination versus mantle source heterogeneity.

Turbulence and icing represent a danger for the aircrafts. In fact, turbulence is the leading cause of aircraft accidents related to meteorology. Both turbulence and icing weather hazards can occur in mountain waves simultaneously. For this reason, it is important to study these weather phenomena. Here, the HARMONIE-AROME model is used in order to analyze mountain wave events in the Guadarrama and the Cantabrian Mountain Ranges (Spain). This short-range mesoscale numerical weather prediction model is used for operational weather forecasts in many European meteorological organizations with a horizontal resolution of 2.5 km. In this study, a spatial resolution of 1 x 1 km is selected. In the analyzed areas, mountain waves are formed on the leeward side when strong winds, perpendicular to the mountains (usually north or northwest winds), are forced to ascend. Simulated total cloud cover and z-wind component have been analyzed and compared with satellite images. The validation of these mountain wave episodes between the HARMONIE-AROME simulations and satellite observations were satisfactory. The most notable differences were observed in the hours of the mountain wave formation/dissipation.

Deciduous larch is a weak competitor when growing in mixed stands with evergreen taxa but is dominant in many boreal forest areas of Eastern Siberia. However, it is hypothesized that certain factors such as a shallow active layer thickness and high fire frequency favor larch dominance. Our aim is to understand how thermohydrological interactions between vegetation, permafrost, and atmosphere stabilize the larch forests and the underlying permafrost in Eastern Siberia. A tailored version of a one-dimensional land surface model (CryoGrid) is adapted for the application in vegetated areas and used to reproduce the energy transfer and thermal regime of permafrost ground in typical boreal larch stands. In order to simulate the responds of Arctic trees to local climate and permafrost conditions we have implemented a multilayer canopy parameterization originally developed for the Community Land Model (CLM-ml_v0). The coupled model is capable of calculating the full energy balance above, within and below the canopy including the radiation budget, the turbulent fluxes and the heat budget of the permafrost ground under several forcing scenarios. We will present first results of simulations performed for different study sites in larch-dominated forests of Eastern Siberia and Mongolia under current and future climate conditions. Model performance is thoroughly evaluated based on comprehensive in-situ soil temperature and radiation measurements at our study sites.

Bayesian Evidential Learning 1D Imaging (BEL1D) has been recently introduced as a new computationally efficient tool for the interpretation of 1D geophysical datasets in a Bayesian framework. Applications have already been demonstrated for Surface Nuclear Magnetic Resonance (SNMR) data and surface waves dispersion curves. The case of SNMR is particularly relevant in hydrogeophysics, as it directly sounds the water content of the subsurface. BEL1D relies on the constitution of statistical relationships in a reduced dimension space between model parameters and simulated data using prior model samples that replicate the field experiment. In BEL1D, this relationship is deduced through Canonical Correlation Analysis (CCA). When using large prior distributions, CCA may lead to numerous poorly correlated distributions for higher dimensions. Those poorly correlated distributions are resulting in a low reduction of uncertainty on some parameters, even if the experiment is supposed to be sensitive to them. This phenomenon is related to the aggregation of multiple parameters in the same dimension, hence the possible aggregation of sensitive and insensitive parameters. However, arbitrarily reducing the extent of the prior will lead to biased estimations. To overcome this impediment, we introduce an iterative procedure, using the posterior model space of the previous iteration as prior model of the current iteration. This approach frequently reveals higher correlations between the datasets and the model parameters, while still using large unbiased priors. It enables BEL1D to produce better estimations of the posterior probability density functions of the model parameters. Nonetheless, iterating on BEL1D presents several challenges related to the presence of insensitive parameters, that will always mitigate the capacity to reduce at once the uncertainty on the whole set of parameters describing the models. On noise-free synthetic datasets, this method leads to near-exact estimation of the sensitive parameters after few (two to three) iterations. On noisy datasets, the resulting distributions bear some uncertainty, arising directly from the presence of noise, but to a lesser extent than the non-iterative approach. The procedure remains more computationally efficient than McMC.

Carbon capture and storage (CCS) has been identified as an area of research interest due to its potential for reducing the global greenhouse effect. CCS typically involves injection of supercritical CO2 into abandoned oil and gas reservoirs or saline aquifers with sufficient porosity and permeability. CO2 is trapped by a number of mechanisms which differ in security with storage in carbonate minerals (geological carbon storage) being the most secure long term mechanism. Consequently, it is important to understand the behaviour of reactive flows and what influences the mineralisation process to occur so that the CCS process can be optimised as a tool for reducing the greenhouse effect. In this work, we present a novel methodology based on 3D models of connected pore structures extracted from micro computed tomography (microCT). The pore geometry is used to build a representative volume in which fluid flow and mineral precipitation takes place. We numerically solve the governing equations of coupled advection-diffusion-reaction using Finite Element Discretisation. The performed simulations describe advection and diffusion of an injected CO2 brine as well as reaction of this fluid phase with the pore walls to form carbonate minerals. A series of different Damköhler (Da) and Péclet (Pe) numbers are employed to investigate the effect on mineralisation and brine migration of differing advective, diffusive and reactive strengths in the system. We complement our microscale model of porous flow with a regional scale model taking into account geological structures relevant to the subsurface of the UK Geoenergy Observatories Cheshire Energy Research Facility Site, UK.

This work presents system concepts, integration efforts and results of the incorporation of recent advances in geospatial technologies, including augmented reality, virtual reality and unmanned aerial systems (UAS), into teaching and learning in the geosciences. Descriptions include the exploration of multiple technological alternatives and introduce system design and integration to enhance and innovate instructional materials in classrooms. The 3D Immersion and Geovisualization (3DIG) system, implemented at the Center for Geospatial Research at the University of Georgia incorporates augmented/customized commercial-off-the-shelf solutions for data acquisition, visualization and human-machine interaction. Through the immersive capabilities of 3DIG, students can be involved in a full data acquisition-processing-analysis workflow. Data streams are used for system integration, with emphasis to model generation/manipulation and remote sensing applications, including multispectral data acquisition/analyses, structure-from-motion based point-cloud/model generation, DEM and texture extraction, and orthomosaics. Resulting products are used with virtual and mixed reality holographic devices, a Geographic Information System (GIS) and with game engines (Unreal Engine and Unity) to create realistic multi-scale multi-theme 3D reconstructions of planet Earth, landscapes and/or objects. Among other system components, an augmented reality digital sandbox equipped with two depth cameras supports experiential learning and experimentation involving scaled down replicas of landscapes or user-defined topographies. The system allows for fast representation of landscape changes (near-real time response), which simulates fluid flow over modified terrain, as well as quantitative analyses, modeling and what-if scenarios through the integration with a GIS. The 3DIG system has been incorporated into classwork and results have been evaluated. This work introduces the interconnected and complementary technologies of 3DIG; presents lessons learned during system design; introduces system implementation and evolution (including the recent integration of new components); describes system use for hands-on and immersive experiential learning; and discusses system evaluation.

Challenges in remote sensing, including remote sensing of vegetation, include the spectral characterization of objects over space and time. One key aspect for this characterization involves the geometry of data acquisition and positional relationships between light source, the target and the remote sensor. Several configurations of goniometers have been used to acquire spectral data as a function of this geometry and this strategy has been particularly efficient when applied to the study of short canopies (e.g., grasses). Tall canopies present logistical challenges when conducting these analyses, which can be resolved by replacing physical structures (rails) with flying systems capable to conform to different canopy geometries and data acquisition requirements. This work (the Droniometer Experiment) investigates anisotropies of a forest using radiometrically calibrated images from a multispectral camera (MicaSense RedEdge) mounted on a rotary-wing unmanned aerial system programmed to follow a planned flight that simulates data acquisition by a goniometer assembled over tall canopy. The experiment used multiple planned flights, conducted to represent changes in illumination, considering sun azimuth and elevation (multiple flights per day and over the course of months). Multi-angle data acquisition was addressed by controlling aircraft position and camera pitch at regular intervals. This work presents the integration of the droniometer system, including platform and camera requirements and control, data acquisition and processing, and analyses of results for target/vegetation characterization and to support information extraction and multi-angle remote sensing. A radiative transfer model, the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) was used for comparative analysis and to further describe anisotropies in spectral responses of tall canopies.