Thomas J. Pingel
- Courses5
- Reviews12
- School: Northern Illinois University
- Campus:
- Department: Geography
- Email address: Join to see
- Phone: Join to see
-
Location:
1425 W. Lincoln Hwy
DeKalb, IL - 60115 - Dates at Northern Illinois University: November 2012 - June 2016
- Office Hours: Join to see
Biography
Northern Illinois University - Geography
Associate Professor at Virginia Tech
Higher Education
Thomas
Pingel
Dekalb, Illinois
I'm an Associate Professor at Virginia Tech in the Geography Department, specializing in Geographic Information Systems and Science, Geovisualization, Computational Modeling, and Web Mapping. My research focuses primarily on the development of Python-based tools for LiDAR processing and visualization. I'm currently developing Unmanned Aerial Vehicle deployment and Indoor Mapping techniques for LiDAR, with the aim of rapidly mapping urban and mixed environments to aid in emergency response and disaster relief. I teach upper division courses in GIS, Geospatial Programming in Python, and Web Mapping.
Specialties: ArcGIS, COLLADA, GIS, Java, JavaScript, Leaflet, LiDAR, Matlab, OpenStreetMap, Python, QGIS, X3D, OpenCV
Experience
University of California, Santa Barbara
Postdoctoral Research Fellow
Research Interest: Automation and Visualization in Immersive Geographic Virtual Environments
UC Santa Barbara
Instructor
Developed and instructed course on Maps and Mapping four times between 2005 and 2009. Maps and Mapping focused on the use of maps for analysis, including aspects of cartography, GIS, and remote sensing.
Northern Illinois University
Assistant Professor
I'm an Assistant Professor at Northern Illinois University in the Geography Department, specializing in Geographic Information Systems and Science, Geovisualization, Computational Modeling, and Web Mapping. My research focuses primarily on the development of Python-based tools for LiDAR processing and visualization. I'm currently developing Unmanned Aerial Vehicle deployment and Indoor Mapping techniques for LiDAR, with the aim of rapidly mapping urban and mixed environments to aid in emergency response and disaster relief. I teach upper division courses in GIS, Geospatial Programming in Python, and Web Mapping.
Virginia Tech
Associate Professor
Thomas worked at Virginia Tech as a Associate Professor
Humanitarian OpenStreetMap Team
The Humanitarian OpenStreetMap Team [HOT] applies the principles of open source and open data sharing for humanitarian response and economic development.
Education
University of California, Santa Barbara
Ph.D.
Geography
My dissertation work investigated the role of strategy in wayfinding. The first portion of this work culminated in the development of a questionnaire that characterized a subject's strategic disposition and attitudes about risk, as well as differences in how mode of travel affected his or her route selection criteria. The second portion investigated the interaction of vision and scale on strategy formulation during search problems. The third portion sought to improve accounts of how strategy and risk perception impact route choices by exploiting the interesting phenomena of asymmetry in route selection, as happens when individuals take a different route when traveling from A to B than when traveling from B to A. The results of these studies, taken together, can be used to guide the interaction between humans and navigation systems.University of California, Santa Barbara
M.A.
Geography
My thesis explored the significance of defensive terrain in the space of computer networks via an experiment conducted on a live network.University of California, Santa Barbara
Postdoctoral Research Fellow
Research Interest: Automation and Visualization in Immersive Geographic Virtual EnvironmentsGeorgetown University
BSFS
Science and Technology in International Affairs
Personalized research program emphasized the role of public policy in guiding environmental science and the security challenges posed by information technology.UC Santa Barbara
Instructor
Developed and instructed course on Maps and Mapping four times between 2005 and 2009. Maps and Mapping focused on the use of maps for analysis, including aspects of cartography, GIS, and remote sensing.
Publications
An Improved Simple Morphological Filter for the Terrain Classification of Airborne LIDAR Data
ISPRS Journal of Photogrammetry and Remote Sensing
Terrain classification of LIDAR point clouds is a fundamental problem in the production of Digital Elevation Models (DEMs). The Simple Morphological Filter (SMRF) addresses this problem by applying image processing techniques to the data. This implementation uses a linearly increasing window and simple slope thresholding, along with a novel application of image inpainting techniques. When tested against the ISPRS LIDAR reference dataset, SMRF achieved a mean 85.4% Kappa score when using a single parameter set and 90.02% when optimized. SMRF is intended to serve as a stable base from which more advanced progressive filters can be designed. This approach is particularly effective at minimizing Type I error rates, while maintaining acceptable Type II error rates. As a result, the final surface preserves subtle surface variation in the form of tracks and trails that make this approach ideally suited for the production of DEMs used as ground surfaces in immersive virtual environments.
An Improved Simple Morphological Filter for the Terrain Classification of Airborne LIDAR Data
ISPRS Journal of Photogrammetry and Remote Sensing
Terrain classification of LIDAR point clouds is a fundamental problem in the production of Digital Elevation Models (DEMs). The Simple Morphological Filter (SMRF) addresses this problem by applying image processing techniques to the data. This implementation uses a linearly increasing window and simple slope thresholding, along with a novel application of image inpainting techniques. When tested against the ISPRS LIDAR reference dataset, SMRF achieved a mean 85.4% Kappa score when using a single parameter set and 90.02% when optimized. SMRF is intended to serve as a stable base from which more advanced progressive filters can be designed. This approach is particularly effective at minimizing Type I error rates, while maintaining acceptable Type II error rates. As a result, the final surface preserves subtle surface variation in the form of tracks and trails that make this approach ideally suited for the production of DEMs used as ground surfaces in immersive virtual environments.
