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 and orientation
- Calibration and optimization
- 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
Keywords
Geostatistics, spatial variability, variograms, kriging interpolation
Learning Prerequisites
Recommended courses
Basic statistics
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:
- Explain pipelines of image acquisition and their conversion to 3D models
- Assess / Evaluate problems related to spatial correlation
- Design solutions to address those
- Implement state of the art geostatistical and machine learning approaches in Python
Transversal skills
- Demonstrate the capacity for critical thinking
- Access and evaluate appropriate sources of information.
Teaching methods
Ex-cathedra lectures and exercice sessions
Assessment methods
Tests during the semester (30%) and final exam (70%)
In the programs
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Sensing and spatial modeling for earth observation
- Lecture: 2 Hour(s) per week x 14 weeks
- Exercises: 3 Hour(s) per week x 14 weeks