Geostatistics and Remote Sensing

• Lecture 1: Course overview; Digital mapping: Geoids, local and global coordinate systems, coordinate transformations; Map projections;

• Lecture 2: Electromagnetic spectrum, spectral data, false color images, resolution, photogrammetry

• Lecture 3: Errors in measurements; Global Navigation Satellite System data

• Lecture 4: Deterministic interpolation, distance, spatial continuity, Inverse distance, LiDAR data

• Lecture 5: Convex hull, Voronoi diagrams, Delaunay triangulation, Triangulated Irregular Networks,

• Lecture 6: Terrain classification. Band data, feature space, Supervised classification, training data, decision tree, linear separation, nearest centroid classification, Spectral angular mapping or Support Vector Machines, Maximum likelihood classification. Unsupervised classification, K-means clustering, Confusion matrix

• Lecture 7: Least squares: mean, variance, covariance, correlation, Random function, minimizing the least squares error, least squares geometry

• Lecture 8: Stochastic interpolation. Kriging the mean, Simple Kriging equations, experimental covariance function, Positive definiteness, variogram, Sill, Range, Nugget.

• Lecture 9: Quality en Digital Terrain Analysis. plane fitting, variance, roughness, surface normals, slope, aspect, orientation, gradient, Quality assessment. Robust methods, RANSAC, Monte Carlo simulation.

50 % Assignments
50 % Final written exam

The written exam will take place in the exam period at the end of the term; Assignment deadlines are planned shortly after corresponding lectures. The final schedule will be adapted to the fieldwork planning

For more information on grading, see article 14 in the Rules and Guidelines (RGBE):
https://www.tudelft.nl/en/student/ceg-student-portal/education/education-information/educational-rules-and-regulations

Permitted Materials during Exam

Students are allowed to use and recommended to bring

* a simple pocket calculator without memory

* a pair of compassess