Multi-touch 3D Exploratory Analysis of Ocean Flow Models

Modern ocean flow simulations are generating increasingly complex, multi-layer 3D ocean flow models. However, most researchers are still using traditional 2D visualizations to visualize these models one slice at a time. Properly designed 3D visualization tools can be highly effective for revealing the complex, dynamic flow patterns and structures present in these models. However, the transition from visualizing ocean flow patterns in 2D to 3D presents many challenges, including occlusion and depth ambiguity. Further complications arise from the interaction methods required to navigate, explore, and interact with these 3D datasets. We present a system that employs a combination of stereoscopic rendering, to best reveal and illustrate 3D structures and patterns, and multi-touch interaction, to allow for natural and efficient navigation and manipulation within the 3D environment. Exploratory visual analysis is facilitated through the use of a highly-interactive toolset which leverages a smart particle system. Multi-touch gestures allow users to quickly position dye emitting tools within the 3D model. Finally, we illustrate the potential applications of our system through examples of real world significance

Designing Improved Sediment Transport Visualizations

Monitoring, or more commonly, modeling of sediment transport in the coastal environment is a critical task with relevance to coastline stability, beach erosion, tracking environmental contaminants, and safety of navigation. Increased intensity and regularity of storms such as Superstorm Sandy heighten the importance of our understanding of sediment transport processes. A weakness of current modeling capabilities is the ability to easily visualize the result in an intuitive manner. Many of the available visualization software packages display only a single variable at once, usually as a two-dimensional, plan-view cross-section. With such limited display capabilities, sophisticated 3D models are undermined in both the interpretation of results and dissemination of information to the public. Here we explore a subset of existing modeling capabilities (specifically, modeling scour around man-made structures) and visualization solutions, examine their shortcomings and present a design for a 4D visualization for sediment transport studies that is based on perceptually-focused data visualization research and recent and ongoing developments in multivariate displays. Vector and scalar fields are co-displayed, yet kept independently identifiable utilizing human perception\u27s separation of color, texture, and motion. Bathymetry, sediment grain-size distribution, and forcing hydrodynamics are a subset of the variables investigated for simultaneous representation. Direct interaction with field data is tested to support rapid validation of sediment transport model results. Our goal is a tight integration of both simulated data and real world observations to support analysis and simulation of the impact of major sediment transport events such as hurricanes. We unite modeled results and field observations within a geodatabase designed as an application schema of the Arc Marine Data Model. Our real-world focus is on the Redbird Artificial Reef Site, roughly 18 nautical miles offshor- Delaware Bay, Delaware, where repeated surveys have identified active scour and bedform migration in 27 m water depth amongst the more than 900 deliberately sunken subway cars and vessels. Coincidently collected high-resolution multibeam bathymetry, backscatter, and side-scan sonar data from surface and autonomous underwater vehicle (AUV) systems along with complementary sub-bottom, grab sample, bottom imagery, and wave and current (via ADCP) datasets provide the basis for analysis. This site is particularly attractive due to overlap with the Delaware Bay Operational Forecast System (DBOFS), a model that provides historical and forecast oceanographic data that can be tested in hindcast against significant changes observed at the site during Superstorm Sandy and in predicting future changes through small-scale modeling around the individual reef objects

Effects of bark beetle outbreaks on forest landscape pattern in the southern rocky mountains, U.S.A.

Since the late 1990s, extensive outbreaks of native bark beetles (Curculionidae: Scolytinae) have affected coniferous forests throughout Europe and North America, driving changes in carbon storage, wildlife habitat, nutrient cycling, and water resource provisioning. Remote sensing is a cru-cial tool for quantifying the effects of these disturbances across broad landscapes. In particular, Landsat time series (LTS) are increasingly used to characterize outbreak dynamics, including the presence and severity of bark beetle-caused tree mortality, though broad-scale LTS-based maps are rarely informed by detailed field validation. Here we used spatial and temporal information from LTS products, in combination with extensive field data and Random Forest (RF) models, to develop 30-m maps of the presence (i.e., any occurrence) and severity (i.e., cumulative percent basal area mortality) of beetle-caused tree mortality 1997–2019 in subalpine forests throughout the Southern Rocky Mountains, USA. Using resultant maps, we also quantified spatial patterns of cumulative tree mortality throughout the region, an important yet poorly understood concept in beetle-affected forests. RF models using LTS products to predict presence and severity performed well, with 80.3% correctly classified (Kappa = 0.61) and R2 = 0.68 (RMSE = 17.3), respectively. We found that ≥10,256 km2 of subalpine forest area (39.5% of the study area) was affected by bark beetles and 19.3% of the study area experienced ≥70% tree mortality over the twenty-three year period. Variograms indi-cated that severity was autocorrelated at scales \u3c 250 km. Interestingly, cumulative patch-size dis-tributions showed that areas with a near-total loss of the overstory canopy (i.e., ≥90% mortality) were relatively small (\u3c0.24 km2) and isolated throughout the study area. Our findings help to in-form an understanding of the variable effects of bark beetle outbreaks across complex forested regions and provide insight into patterns of disturbance legacies, landscape connectivity, and susceptibility to future disturbance

Scaling slowly rotating asteroids with stellar occultations

Context. As evidenced by recent survey results, the majority of asteroids are slow rotators (spin periods longer than 12 h), but lack spin and shape models because of selection bias. This bias is skewing our overall understanding of the spins, shapes, and sizes of asteroids, as well as of their other properties. Also, diameter determinations for large (>60 km) and medium-sized asteroids (between 30 and 60 km) often vary by over 30% for multiple reasons. Aims. Our long-term project is focused on a few tens of slow rotators with periods of up to 60 h. We aim to obtain their full light curves and reconstruct their spins and shapes. We also precisely scale the models, typically with an accuracy of a few percent. Methods. We used wide sets of dense light curves for spin and shape reconstructions via light-curve inversion. Precisely scaling them with thermal data was not possible here because of poor infrared datasets: large bodies tend to saturate in WISE mission detectors. Therefore, we recently also launched a special campaign among stellar occultation observers, both in order to scale these models and to verify the shape solutions, often allowing us to break the mirror pole ambiguity. Results. The presented scheme resulted in shape models for 16 slow rotators, most of them for the first time. Fitting them to chords from stellar occultation timings resolved previous inconsistencies in size determinations. For around half of the targets, this fitting also allowed us to identify a clearly preferred pole solution from the pair of two mirror pole solutions, thus removing the ambiguity inherent to light-curve inversion. We also address the influence of the uncertainty of the shape models on the derived diameters. Conclusions. Overall, our project has already provided reliable models for around 50 slow rotators. Such well-determined and scaled asteroid shapes will, for example, constitute a solid basis for precise density determinations when coupled with mass information. Spin and shape models in general continue to fill the gaps caused by various biases

A More Flexible Approach to Utilizing Depth Cameras for Hand & Touch Interaction

Many researchers have utilized depth cameras for tracking user\u27s hands to implement various interaction methods, such as touch-sensitive displays and gestural input. With the recent introduction of Microsoft\u27s low-cost Kinect sensor, there is increased interest in this strategy. However, a review of the existing literature on these systems suggests that the majority suffer from similar limitations due to the image processing methods used to extract, segment, and relate the user\u27s body to the environment/display. This paper presents a simple, efficient method for extracting interactions from depth images that is more flexible in terms of sensor placement, display orientation, and dependency on surface reflectivity

Low-Cost Coastal Mapping Using Kinect v2 Time-of-Flight Cameras

High-resolution elevation and bathymetry data for coastal zones is extremely valuable to many researchers, however the cost of acquiring such data is prohibitively expensive for most research budgets, as it relies on specialized hardware. Mass produced off-the-shelf consumer cameras and sensors are becoming increasingly powerful, and can be affordable alternatives for collecting data. Microsoft’s original Kinect sensor was repurposed to collect data for Earth sciences research, but its low depth resolution hindered its usefulness for creating accurate maps. In this paper, we evaluate Microsoft’s next generation Kinect for Windows v2 sensor, which employs time-of-flight technology. Based on our results, the new sensor has great potential for use in coastal mapping and other Earth science applications where budget constraints preclude the use of traditional remote sensing data acquisition technologies

Interactive Visual Analysis within Dynamic Ocean Models

The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas

Measuring Waves and Erosion in Underwater Oil Blobs and Monitoring Other Arbitrary Surfaces with a Kinect v2 Time-of-Flight Camera

We developed free software that enables researchers to utilize Microsoft’s new Kinect for Windows v2 sensor for a range of coastal and ocean mapping applications, as well as monitoring and measuring experimental scenes. While the original Kinect device used structured light and had very poor resolution, many geophysical researchers found uses for it in their experiments. The new next generation of this sensor uses time-of-flight technology, and can produce higher resolution depth measurements with an order of magnitude more accuracy. It also is capable of measurement through and under water. An analysis tool in our application lets users quickly select any arbitrary surface in the sensor’s view. The tools automatically scans the surface, then calibrates and aligns a measurement volume to it. Depth readings from the sensor are converted into 3D point clouds, and points falling within this volume are projected into surface coordinates. Raster images can be output which consist of height fields aligned to the surface, generated from these projected measurements and interpolations between them. Images have a simple 1 pixel = 1 mm resolution and intensity values representing mm in height from the base-plane, which enables easy measurement and calculations to be conducted on the images in other analysis packages. Single snapshots can be taken manually on demand, or the software can monitor the surface automatically, capturing frames at preset intervals. This produces time lapse animations of dynamically changing surfaces. We apply this analysis tool to an experiment studying the behavior of underwater oil in response to flowing water of different speeds and temperatures. Blobs of viscous oils are placed in a flume apparatus, which circulates water past them. Over the course of a couple hours, the oil blobs spread out, waves slowly ripple across their surfaces, and erosions occur as smaller blobs break off from the main blob. All of this can be captured in 3D, with mm accuracy, through the water using the Kinect for Windows v2 sensor and our K2MapKit software

Interactive 4D Visualization of Sediment Transport Models

Coastal sediment transport models simulate the effects that waves, currents, and tides have on near-shore bathymetry and features such as beaches and barrier islands. Understanding these dynamic processes is integral to the study of coastline stability, beach erosion, and environmental contamination. Furthermore, analyzing the results of these simulations is a critical task in the design, placement, and engineering of coastal structures such as seawalls, jetties, support pilings for wind turbines, etc. Despite the importance of these models, there is a lack of available visualization software that allows users to explore and perform analysis on these datasets in an intuitive and effective manner. Existing visualization interfaces for these datasets often present only one variable at a time, using two dimensional plan or cross-sectional views. These visual restrictions limit the ability to observe the contents in the proper overall context, both in spatial and multi-dimensional terms. To improve upon these limitations, we use 3D rendering and particle system based illustration techniques to show water column/flow data across all depths simultaneously. We can also encode multiple variables across different perceptual channels (color, texture, motion, etc.) to enrich surfaces with multi-dimensional information. Interactive tools are provided, which can be used to explore the dataset and find regions-of-interest for further investigation. Our visualization package provides an intuitive 4D (3D, time-varying) visualization of sediment transport model output. In addition, we are also integrating real world observations with the simulated data to support analysis of the impact from major sediment transport events. In particular, we have been focusing on the effects of Superstorm Sandy on the Redbird Artificial Reef Site, offshore of Delaware Bay. Based on our pre- and post-storm high-resolution sonar surveys, there has significant scour and bedform migration around the sunken subway cars and other vessels present at the Redbird site. Due to the extensive surveying and historical data availability in the area, the site is highly attractive for comparing hindcasted sediment transport simulations to our observations of actual changes. This work has the potential to strengthen the accuracy of sediment transport modeling, as well as help predict and prepare for future changes due to similar extreme sediment transport events