Thomas Butkiewicz

Multi-Focused Geospatial Analysis Using Probes

Traditional geospatial information visualizations often present views that restrict the user to a single perspective. When zoomed out, local trends and anomalies become suppressed and lost; when zoomed in for local inspection, spatial awareness and comparison between regions become limited. In our model, coordinated visualizations are integrated within individual probe interfaces, which depict the local data in user-defined regions-of-interest. Our probe concept can be incorporated into a variety of geospatial visualizations to empower users with the ability to observe, coordinate, and compare data across multiple local regions. It is especially useful when dealing with complex simulations or analyses where behavior in various localities differs from other localities and from the system as a whole. We illustrate the effectiveness of our technique over traditional interfaces by incorporating it within three existing geospatial visualization systems: an agent-based social simulation, a census data exploration tool, and an 3D GIS environment for analyzing urban change over time. In each case, the probe-based interaction enhances spatial awareness, improves inspection and comparison capabilities, expands the range of scopes, and facilitates collaboration among multiple users.

Legible Simplification of Textured Urban Models

Most of the algorithms used for research in mesh simplification and discrete levels of detail (LOD) work well for simplifying single objects with a large number of polygons. For a city-sized collection of simple buildings, using these traditional algorithms could mean the disappearance of an entire residential area in which the buildings tend to be smaller than those in commercial regions. To solve this problem, we developed a mesh-simplification algorithm that incorporates concepts from architecture and city planning. Specifically, we rely on the concept of urban legibility, which segments a city into paths, edges, districts, nodes, and landmarks. If we preserve these elements of legibility during the simplification process, we can maintain the citys image and create urban models that users can understand more effectively. To accomplish this goal, we divide our algorithm into five steps. During preprocessing, it performs hierarchical clustering, cluster merging, model simplification, and hierarchical texturing, at runtime, it employs LOD to select the appropriate models for rendering.

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. Microsofts 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 Microsofts 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.

A two-stage framework for designing visual analytics system in organizational environments

A perennially interesting research topic in the field of visual analytics is how to effectively develop systems that support organizational users decision-making and reasoning processes. The problem is, however, most domain analytical practices generally vary from organization to organization. This leads to diverse designs of visual analytics systems in incorporating domain analytical processes, making it difficult to generalize the success from one domain to another. Exacerbating this problem is the dearth of general models of analytical workflows available to enable such timely and effective designs. To alleviate these problems, we present a two-stage framework for informing the design of a visual analytics system. This design framework builds upon and extends current practices pertaining to analytical workflow and focuses, in particular, on incorporating both general domain analysis processes as well as individuals analytical activities. We illustrate both stages and their design components through examples, and hope this framework will be useful for designing future visual analytics systems. We validate the soundness of our framework with two visual analytics systems, namely Entity Workspace [8] and PatViz [37].

Visual analysis and semantic exploration of urban LIDAR change detection

Many previous approaches to detecting urban change from LIDAR point clouds interpolate the points into rasters, perform pixel‐based image processing to detect changes, and produce 2D images as output. We present a method of LIDAR change detection that maintains accuracy by only using the raw, irregularly spaced LIDAR points, and extracts relevant changes as individual 3D models. We then utilize these models, alongside existing GIS data, within an interactive application that allows the chronological exploration of the changes to an urban environment. A three‐tiered level‐of‐detail system maintains a scale‐appropriate, legible visual representation across the entire range of view scales, from individual changes such as buildings and trees, to groups of changes such as new residential developments, deforestation, and construction sites, and finally to larger regions such as neighborhoods and districts of a city that are emerging or undergoing revitalization. Tools are provided to assist the visual analysis by urban planners and historians through semantic categorization and filtering of the changes presented.

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.

Alleviating the modifiable areal unit problem within probe-based geospatial analyses

We present a probe‐based interface for the exploration of the results of a geospatial simulation of urban growth. Because our interface allows the user great freedom in how they choose to define regions‐of‐interest to examine and compare, the classic geospatial analytic issue known as the modifiable areal unit problem (MAUP) quickly arises. The user may delineate regions with unseen differences that can affect the fairness of the comparisons made between them. To alleviate this problem, our interface first alerts the user if it detects any potential unfairness between regions when they are selected for comparison. It then presents the dimensions with potential problematic outliers to the user for evaluation. Finally, it provides a number of semi‐automated tools to assist the user in correcting their regions boundaries to minimize the inequalities they feel could significantly impact their comparisons.

Hierarchical simplification of city models to maintain urban legibility

Mesh simplification and discrete levels of detail (LOD) are wellstudied areas of research in computer graphics. However, until recently, most of the developed algorithms have focused on simplification and viewing of a single object with a large number of polygons. When these algorithms are used on a large collection of simple models, many objects may be completely erased, leading to results that are misleading to the viewer. In this paper, we present a novel approach to simplifying city-sized collections of 2.5D buildings based on the principles of “urban legibility” as defined by architects and city planners. Our main contributions include a clustering algorithm tailored towards forming logical groups while respecting roads, a polyline simplification algorithm that maintains boundary facades, and a LOD process that preserves landmarks and skylines. The advantage of our approach is that the legibility and understandability of a complex urban space is preserved at all levels of simplification. CR Categories: I.3.5 [Computational Geometry and Object Modeling]: Hierarchy and geometric transformations—Curve, surface, solid, and object representations;

Visual analysis for live LIDAR battlefield change detection

We present the framework for a battlefield change detection system that allows military analysts to coordinate and utilize live collection of airborne LIDAR range data in a highly interactive visual interface. The system consists of three major components: The adaptive and self-maintaining model of the battlefield selectively incorporates the minority of new data it deems significant, while discarding the redundant majority. The interactive interface presents the analyst with only the minute portion of the data the system deems relevant, provides tools to facilitate the decision making process, and adjusts its behavior to reflect the analysts objectives. Finally, the cycle is completed by the generation of a goal map for the LIDAR collection hardware that instructs as to which areas should be sampled next in order to best advance the change detection task. All together, the system empowers analysts with the ability to make sense of a deluge of measurements by extracting the salient features and continually refining its definitions of relevancy.

Hierarchical multi-touch selection techniques for collaborative geospatial analysis

In time critical visual analytic environments collaboration between multiple expert users allows for rapid knowledge discovery and facilitates the sharing of insight. New collaborative display technologies, such as multi-touch tables, have shown great promise as the medium for such collaborations to take place. However, under such new technologies, traditional selection techniques, having been developed for mouse and keyboard interfaces, become inconvenient, inefficient, and in some cases, obsolete. We present selection techniques for multi-touch environments that allow for the natural and efficient selection of complex regions-of-interest within a hierarchical geospatial environment, as well as methods for refining and organizing these selections. The intuitive nature of the touch-based interaction permits new users to quickly grasp complex controls, while the consideration for collaboration coordinates the actions of multiple users simultaneously within the same environment. As an example, we apply our simple gestures and actions mimicking real-world tactile behaviors to increase the usefulness and efficacy of an existing urban growth simulation in a traditional GIS-like environment. However, our techniques are general enough to be applied across a wide range of geospatial analytical applications for both domestic security and military use.