ENME489Y: Remote Sensing
Course Details
3 credits
2 x 75-minute lectures / week
This course explores the fundamentals of remote sensing techniques including
light detection and ranging (lidar), radar, and computer vision in the
context of emerging technologies such as autonomous navigation and terrain mapping. Throughout the semester, students are exposed to
a variety of sensors from the research and commercial domains - both in terms of hardware and software.
UMD student working with a Velodyne Puck lidar sensor as part of ENME489Y
The course includes lectures from guest speakers of significant reputation in their respective branches of remote sensing. Guest lecturers join us from research, commercial, and government entities to discuss their work in remote sensing.
The course requires completion of a semester project employing the course material, CAD, rapid prototyping, and data collection & processing. The project provides students an opportunity to experience a hands-on project involving a remote sensing technology that is closely related to their area of study.
Lectures
Lecture slides upon request. Email me: mitchels@umd.edu
Week 1: Course Introduction
Week 2: Intro to Remote Sensing / Python / Project
Week 3: Lidar Remote Sensing / OpenCV Fundamentals
Week 4: The Lidar Equation / Automatic Lane Detection
Week 5: Lidar System Design / Automatic Lane Detection
Week 6: Lidar Altimetry: NASA Goddard Space Flight Center
Week 7: Lidar Altimetry: US Army Geospatial Research Lab
Week 8: Lidar Demonstration
Week 9: Spring Break
Week 10: Lidar Data Acquisition & Processing
Week 11: Velodyne & Project Support
Week 12: Project Support
Week 13: NASA Operation Ice Bridge & Project Support
Week 14: Navy Research Laboratory & Project Support
Week 15: Project Presentations
Week 16: Project Presentations
Homework
All codes available on 489Y Github
Assignment #2: Introduction to the Raspberry Pi
Assignment #3: Introduction to OpenCV and object tracking with Raspberry Pi
Assignment #4: Introduction to the triangulation lidar range measurement
Assignment #5: Introduction to field deployable lidar, Inertial Measurement Unit (IMU), and pySerial
Assignment #6: Initial collection of lidar data & initial 3D point cloud
Assignment #7: Completed 3D point cloud of lidar data
Assignment #8: Mesh of lidar point cloud data & 3D print
Project Details
Project instructions are described in each homework assignment
The lidar is integrated onto a standardized, 3D-printable mount. The mount consists of a single holder plate, which has mounting holes for an Arduino Uno, Raspberry Pi and Pi camera, and a LED line laser. The plate also has miscellaneous holes and slots allocated as cable tie downs, etc., along with two rectangular cutouts that can be used to tie the plate into a standard tripod.
A solid model file of the standardized plate is available for download. While it is
An additional 3D-printable piece is also available to attach the mount to a standard tripod via the two rectangular cutouts:
Here is one incarnation of the assembled, aligned instrument:
Examples of past student videos (full repository):
The following Google Map serves as a collection of student projects for ENME489Y: Remote Sensing. Zoom in/out and pan around to get an idea of campus coverage. Click on the green placemarks to view student videos.
Python Resources
Looking to learn Python? Great!
Begin by installing PyCharm on your machine.
Coming soon: my online Introduction to Python course (interested in joining? Email me)
Raspberry Pi & OpenCV Resources
New to OpenCV? Start with Adrian Rosebrock's Practical Python & OpenCV. We use it in class!