Visualization and Analysis of Multi-terabyte Geophysical Datasets in an Interactive Setting with Remote Webcam Capabilities

Visualizing and analyzing datasets in the geosciences is becoming increasingly complicated as their volumes are growing explosively. This poses a challenging problem for researchers who must sift through terabytes of data to discover useful relationships inside the information. There is a great need for geophysicists to interactively explore their data sets. Conventional visualization systems lack adequate bandwidth and rendering capabilities necessary for the largest data sets. CAVE and Powerwall display devices are necessary for researchers to explore their data sets in an immersive setting. We describe a utilitarian system targeted specifically at the cost-effective interactive exploration of data sets tens of terabytes in size and harness this system for visualization and analysis of geophysical simulations. Webcams can be used as a steering device to track a local region of interest, which is useful for remote visualization of large data sets. This system will be employed as a web-service under the auspices of Narada-Brokering, while using webcam technologies to enable remote visualization for collaborating researchers. Webcams can be incorporated in a point-to-point network for rapid exchange of information and quickly announcing natural disasters, such as tsunamis, landslides and earthquakes.     

Improving radiometry of imaging spectrometers by using programmable spectral regions of interest

Programmable imaging spectrometers can be adjusted to fit specific application requirements that differ from the instrument initial spectral design goals. Sensor spectral characteristics and its signal-to-noise ratio (SNR) can be changed by applying customized online binning patterns.We present a software utility that generates application driven spectral binning patterns by using an SNR dependent sensor model. The utility, named BinGO (BInning patterN Generator and Optimiser), is used to produce predefined binning patterns that either (a) allow an existing imaging spectrometer to optimize its spectral characteristics for a specific application, (b) allow an existing imaging spectrometer to spectral and/or spatially emulate another instrument, or (c) design new multispectral or imaging spectrometer missions (i.e. spaceborne, airborne, terrestrial). We present a variety of BinGO case studies, including the simulation of airborne (APEX) [Itten, K.I. et al., 2008. APEX — The hyperspectral ESA Airborne Prism Experiment. Sensors 8(1), 1–25], spaceborne (SENTINEL III) [Nieke, J., Frerick, J., Stroede, J., Mavrocordatos, C., Berruti, B., 2008. Status of the optical payload and processor development of ESA’s Sentinel 3 mission. In: Proceedings of the Geoscience and Remote Sensing Symposium IGARSS 2008, pp. 427–430], as well as scientific and performance optimized approaches. We conclude that the presented approach can successfully be used to increase the efficiency of spectral information retrieval by using imaging spectroscopy data and to simulate various missions and requirements, finally supporting proper trade-off decisions to be made between performance optimization and scientific requirements. In addition, if specific sensor parameters are known, BinGO can also model other imaging spectrometers.     

Magma batches in the Timber Mountain magmatic system, Southwestern Nevada Volcanic Field, Nevada, USA

The common occurrence of compositionally and mineralogically zoned ash flow sheets, such as those of the Timber Mountain Group, provides evidence that the source magma bodies were chemically and thermally zoned. The Rainier Mesa and Ammonia Tanks tuffs of the Timber Mountain Group are both large volume (1200 and 900 km³, respectively) chemically zoned (57–78 wt.% SiO₂) ash flow sheets. Evidence of distinct magma batches in the Timber Mountain system are based on: (1) major- and trace-element variations of whole pumice fragments; (2) major-element variations in phenocrysts; (3) major-element variations in glass matrix; and (4) emplacement temperatures calculated from Fe-Ti oxides and feldspars. There are three distinct groups of pumice fragments in the Rainier Mesa Tuff: a low-silica group and two high-silica groups (a low-Th and a high-Th group). These groups cannot be related by crystal fractionation. The low-silica portion of the Rainier Mesa Tuff is distinct from the low-silica portion of the overlying Ammonia Tanks Tuff, even though the age difference is less than 200,000 years. Three distinct groups occur in the Ammonia Tanks Tuff: a low-silica, intermediate-silica and a high-silica group. Part of the high-silica group may be due to mixing of the two high-silica Rainier Mesa groups. The intermediate-silica group may be due to mixing of the low- and high-silica Ammonia Tanks groups. Three distinct emplacement temperatures occur in the Rainier Mesa Tuff (869, 804, 723 °C) that correspond to the low-silica, high-Th and low-Th magma batches, respectively. These temperature differences could not have been maintained for any length of time in the magma chamber (cf. Turner, J.S., Campbell, I.H., 1986. Convection and mixing in magma chambers. Earth-Sci. Rev. 23, 255–352; Martin, D., Griffiths, R.W., Campbell, I.H., 1987. Compositional and thermal convection in magma chambers. Contrib. Mineral. Petrol. 96, 465–475) and therefore eruption must have occurred soon after emplacement of the magma batches into the chamber. Emplacement temperatures of the pumice fragments from the Ammonia Tanks Tuff show a continuous gradient of temperatures with composition. This continuous temperature gradient is consistent with the model of storage of magma batches in the Ammonia Tanks group that have undergone both thermal and chemical diffusion.     

Integrating the maximum capture problem into a GIS framework

This paper presents a methodology for reformulating the maximal capture problem by using the data representation and manipulation capabilities of GIS to define: (1) the coverage region captured by each potential facility, and (2) each unique demand region covered by a specific combination of potential facilities. The formulation is modeled on the maximum covering problem although the integer restriction on the demand capture variables is relaxed. Because demand regions are not exogenously given, areal interpolation is used to estimate the demand associated with each of these regions The model is used to determine the location on a network for a set of home improvement stores that are hypothetically in competition with existing Home Depot stores in Southeastern New Hampshire.      

A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams

This article outlines a semi‐autonomous approach for using a fusion of light detection and ranging (LiDAR) and optical remote sensing data to identify and measure small impoundments (SIs) and their dams. Quantifying such water bodies as hydrologic network features is critical for ecosystem and species conservation, emergency management, and water resource planning; however, such features are incompletely mapped at national and state levels. By merging an airborne LiDAR‐derived point cloud with a normalized water index using airborne optical imagery we demonstrate an improvement upon single‐source methods for identifying these water bodies; classification accuracies increased over 10% by using this multi‐source fusion method. Furthermore, the method presented here illustrates a cost‐effective pathway to improve the National Inventory of Dams (NID) and includes a framework for estimating dam heights, with results showing strong correlations between derived dam heights and those recorded in the NID (r=.78). With the steady increase in available LiDAR coverage, the 87,000+ dams in the NID could be updated using this technique, a method which could also be expanded for global inventories of SIs and dams.     

A carbon balance model for the great dismal swamp ecosystem

Background

Carbon storage potential has become an important consideration for land management and planning in the United States. The ability to assess ecosystem carbon balance can help land managers understand the benefits and tradeoffs between different management strategies. This paper demonstrates an application of the Land Use and Carbon Scenario Simulator (LUCAS) model developed for local-scale land management at the Great Dismal Swamp National Wildlife Refuge. We estimate the net ecosystem carbon balance by considering past ecosystem disturbances resulting from storm damage, fire, and land management actions including hydrologic inundation, vegetation clearing, and replanting.

Results

We modeled the annual ecosystem carbon stock and flow rates for the 30-year historic time period of 1985–2015, using age-structured forest growth curves and known data for disturbance events and management activities. The 30-year total net ecosystem production was estimated to be a net sink of 0.97 Tg C. When a hurricane and six historic fire events were considered in the simulation, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and below-ground carbon loss estimated from the South One and Lateral West fire events totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The carbon loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus.

Conclusions

Natural disturbances substantially impact net ecosystem carbon balance in the Great Dismal Swamp. Through alternative management actions such as re-wetting, below-ground biomass loss may have been avoided, resulting in the added carbon storage capacity of 1.38 Tg. Based on two model assumptions used to simulate the peat system, (a burn scar totaling 70 cm in depth, and the soil carbon accumulation rate of 0.36 t C/ha^?1/year^?1 for Atlantic white cedar), the total soil carbon loss from the South One and Lateral West fires would take approximately 1740 years to re-amass. Due to the impractical time horizon this presents for land managers, this particular loss is considered permanent. Going forward, the baseline carbon stock and flow parameters presented here will be used as reference conditions to model future scenarios of land management and disturbance.

     

A Spatial Filtering Specification for an Auto-negative Binomial Model of Anopheles arabiensis Aquatic Habitats

This research accounts for spatial autocorrelation by including latent map pattern components as predictor variables in a malaria mosquito aquatic habitat model specification. The data used to derive the model was from a digitized grid-based algorithm, generated in an ArcInfo database, using QuickBird visible and near-infrared (NIR) data. The Feature Extraction (FX) Module in ENVI 4.4^® was used to categorize individual pixels of field sampled aquatic habitats into separate spectral classes, convert remotely sensed raster layers to vector coverages, and classify output layers to vector format as ESRI shapefiles. These data were used to construct a geographic weights matrix for evaluation of field and remote sampled covariates of Anopheles arabiensis aquatic habitats, a major vector of malaria in East Africa. The principal finding is that synthetic map pattern variables, which are eigenvectors computed for a geographic weights matrix, furnish an alternative way of capturing spatial dependency effects in the mean response term of a regression model. The spatial autocorrelation components suggest the presence of roughly 11 to 28% redundant information in the aquatic habitat larval count samples. The presence of redundant information in the models suggest that the sampling configuration of the An. arabiensis aquatic habitats, in the study sites, may cause field and remote observations of aquatic habitats to be dependent, rather than independent, moving data analysis away from the classical statistical independence model. A Poisson regression model, with a non-constant, gamma-distributed mean, can decompose field and remote sampled An. arabiensis data into positive and negative spatial autocorrelation eigenvectors, which can assess the precision of a malaria mosquito aquatic habitat map and the significance of all factors associated with larval abundance and distribution in a riceland agroecosystem.     

Experimental evaluation of the coalescence efficiencies of colliding water drops

The coalescence of water drops of sizes comparable to rain drops (200–2500 m diameter) was investigated. The method used provided a good separation between collision and coalescence effects. The result suggests a dependence of the coalescence efficiency on both the size of the large drop and the ratio of the radii of the interacting drops (p-ratio). The coalescence was observed to rapidly decrease due to bouncing and partial coalescence as the angle of impact increased from head-on to grazing angle. However, some bouncing was observed at very low impact angles.The results of the coalescence efficiency were fitted with an empirical equation for use in numerical models of cloud growth and precipitation development.On sabbatical leave (1976–77) from the Department of Geophysics and Planetary Sciences, Tel Aviv University, Ramat Aviv, Israel.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Electrical-hydraulic conductivity model for a weathered-fractured aquifer system of Olbanita,Lower Baringo Basin,Kenya Rift

Groundwater yield in the Kenya Rift is highly unsustainable owing to geological variability. In this study, field hydraulic characterization was performed by using geo-electric approaches. The relations between electrical-hydraulic (eh) conductivities were modeled hypothetically and calibrated empirically. Correlations were based on the stoch-astic models and field-scale hydraulic parameters were contingent on pore-level parameters. By considering variation in pore-size distributions over eh conduction interval, the relations were scaled-up for use at aquifer-level. Material-level electrical conductivities were determined by using Vertical Electrical Survey and hydraulic conductivities by analyzing aquifer tests of eight boreholes in the Olbanita aquifer located in Kenya rift. VES datasets were inverted by using the computer code IP2Win. The main result is that ln T=0.537 (ln Fa)+3.695; the positive gradient indicating eh conduction through poresurface networks and a proxy of weathered and clayey materials. An inverse (1/F-K) correlation is observed. Hydraulic parameters determined using such approaches may possibly contri-bute significantly towards sustainable yield management and planning of groundwater resources.