Thomas Pingel's Projects
A-Frame component using 3D-Tiles
Load PointClouds with Potree
Bidimensional regression is a technique to measure the agreement between two, two-dimensional vectors. R-square provides a single value of overall agreement, while scale, translation, and rotation information is also provided. This function has been validated against Friedman and Kohler's provided sample dataset.
This is a simple implementation of Cohen's Kappa statistic, which measures agreement for two judges for values on a nominal scale. See the Wikipedia entry for a quick overview, or you can get the original article from Sage Publications. Kappa has been used extensively in psychology, and has been more recently applied to land cover / land use changes and to assessments of accuracy for classification algorithms in Remote Sensing (Congalton, 1991; Jensen, 2005).
This is a project that tries to combine various DJI related tools
playing with the javascript gamepad API
A collection of simple geodata, primarily for teaching.
Notebooks for Northern Illinois University's GEOG 493 (Computer Programming for the Geographic and Atmospheric Sciences)
These are random, single-purpose notebooks generally created to explore a particular topic in geospatial computing.
Very simple implementation of a great circle distance calculator, assuming a spherical Earth. It isn't, by the way. You should use: d = distance(lon1, lat1, lon2, lat2, almanac('earth', 'wgs84')); if you have the Mapping Toolbox.
3D LIDAR-based Graph SLAM
A collection of notebooks formerly used to teach an Introduction to Geospatial Programming in Python course
LiDAR binary reader for Matlab
least cost path modeling
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.
A robust LiDAR Odometry and Mapping (LOAM) package for Livox-LiDAR
Laser Odometry And Mapping (LOAM) SLAM ROS package for 3D Velodyne VLP-16 laser scanner
Nonparametric Two-way ANOVA Used For Block Designs with Unequal Numbers of Multiple Observations