Sensing and spatial modeling for earth observation
Summary
Students get acquainted with the process of mapping from images (orthophoto and DEM), as well as with methods for monitoring the Earth surface using remotely sensed data. Methods will span from machine learning to geostatistics and model the spatiotemporal variability of processes.
Content
The course is organized in three main parts.
1. 3D reconstruction from images
- Processes of image creation
- Image matching, orientation and camera calibration
- Construction of digital elevation models (DEM) and orthophotos
2. Environmental monitoring with machine learning
- Extracting features from elevation or image data
- Prediction with linear and nonlinear regression
3. Geostatistics:
- Definitions and spatial context
- Structural analysis
- Interpolation using kriging
Learning Prerequisites
Important concepts to start the course
Good Python programming skills are required
Learning Outcomes
By the end of the course, the student must be able to:
- Implement state of the art geostatistical and machine learning approaches in Python
- Establish 3D model from captured imagery.
- Analyze various properties of obtained 3D model.
- Plan relavant aspects in drone & airborne mapping.
Assessment methods
Final exam (80%) + 1 graded exercise (20%)
Supervision
| Office hours | No |
| Assistants | Yes |
| Forum | No |
In the programs
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Courses: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Lab: 1 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Courses: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Lab: 1 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Courses: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Lab: 1 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Courses: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Lab: 1 Hour(s) per week x 14 weeks
- Type: optional
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Courses: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Courses: 2 Hour(s) per week x 14 weeks
- Exercises: 2 Hour(s) per week x 14 weeks
- Type: optional