Geospatial Technologies: Drones, Sensors, and Applications
Intro to geospatial technologies like drones, LiDAR, DGPS, GNSS, VR, and sensors for capturing landscape properties and understanding environmental change.
Summary
Recent recorded grades — Fall 2023: 3.91 GPA, 100.0% A/AB (n=17 letter grades).
What you’ll be able to do
Identify Unmanned Aerial Systems hardware, safety, regulations, mission planning, and applications for the sciences.
Develop skills in the area of structure-from-motion 3D point cloud model development and visualization.
Identify and use high-grade differential Geographic Positioning Systems and Global Navigation Satellite Systems.
Develop proficiency in LiDAR technologies from satellite, airborne, Unmanned Aerial Systems, and terrestrial, including LiDAR data collection, visualization, and processing.
Use remote sensing instruments, such as multispectral and hyperspectral sensors and thermal cameras.
Become familiar with Virtual reality, augmented reality, geocaching and geotagging.
Apply geospatial technology data collection and processing to research.
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapSophomore standing
- Sophomore standing
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Sophomore standing
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
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Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
Student experience
the class
Recent recorded grades — Fall 2023: 3.91 GPA, 100.0% A/AB (n=17 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
- Unmanned aerial systems, LiDAR, DGPS, GNSS, virtual reality, optical sensors, geocaching, and geotagging
- Landscape property capture and environmental change characterization
- Structure-from-motion 3D point cloud models
Skills
- Geospatial systems applicable to research and industry fields
- Unmanned Aerial Systems hardware, safety, regulations, and mission planning
- Structure-from-motion 3D point cloud model development and visualization
- High-grade differential GPS and GNSS usage
- LiDAR technology data collection, visualization, and processing
- Remote sensing instrument operation (multispectral, hyperspectral, thermal)
- Virtual reality, augmented reality, geocaching, and geotagging familiarity
- Applying geospatial data collection and processing to research
Grades
Latest available · Fall 2023— not enough history to project Spring 2027.
Grade distribution · % of letter grades
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
No offering records for the selected term.
Raw records
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
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Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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"model": "Qwen/Qwen3.8-27B",
"model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
"task_version": "17",
"output_id": "df4f921c853008f6ad87f6246c74f4ea98beb666e13c570003ab062e0920189c",
"requirements_status": "valid",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
}