Jemil Avers Butt: Catalogue data in Autumn Semester 2023 |
| Name | Dr. Jemil Avers Butt |
| Address | Geosensorik und Ingenieurgeodäsie ETH Zürich, HIL D 45.1 Stefano-Franscini-Platz 5 8093 Zürich SWITZERLAND |
| Telephone | +41 44 633 34 84 |
| jemil.butt@geod.baug.ethz.ch | |
| Department | Civil, Environmental and Geomatic Engineering |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | |||||||||||||||||||||||
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| 103-0251-00L | Computational Methods for Geospatial Analysis | 4 credits | 4G | K. Schindler, J. A. Butt, B. Soja, Y. Xin | |||||||||||||||||||||||
| Abstract | Introduction to mathematical and statistical tools for geospatial data analysis. | ||||||||||||||||||||||||||
| Learning objective | The goal is to familiarise students with the principles and tools of geospatial data analysis, and to enable them to apply those tools to practical tasks. | ||||||||||||||||||||||||||
| Content | The course introduces basic methods of geostatistics and geospatial data analysis. Topics include spatial correlation, auto-correlation and the variogram; surface interpolation (kernel-based, kriging, parametric surface models); spatially adaptive filtering (bilinear, guided filter); spatial stochastic processes and random fields; time series models and spatio-temporal analysis. | ||||||||||||||||||||||||||
| Prerequisites / Notice | Bachelor level mathematics: analysis, linear algebra, statistics and probability theory, parameter estimation. Basic knowledge of multivariate statistics and machine learning is recommended. | ||||||||||||||||||||||||||
Competencies |
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| 103-0787-00L | Project Parameter Estimation | 3 credits | 2P | J. A. Butt, T. Medic | |||||||||||||||||||||||
| Abstract | Solving engineering problems with modern methods of parameter estimation for network adjustment in a real-world scenario; choosing adequate mathematical models, implementation and assessment of the solutions. | ||||||||||||||||||||||||||
| Learning objective | Learn to solve engineering problems with modern methods of parameter estimation in a real-world scenario. | ||||||||||||||||||||||||||
| Content | Analysis of given problems, selection of appropriate mathematical modells, implementation and testing using Matlab: Kriging; system calibration of a terrestrial laser scanner. | ||||||||||||||||||||||||||
| Lecture notes | The task assignments and selected documentation will be provided as PDF. | ||||||||||||||||||||||||||
| Prerequisites / Notice | Prerequisite: Statistics and Probability Theory, Geoprocessing and Parameterestimation, Geodetic Reference Systems and Networks | ||||||||||||||||||||||||||