Applied mathematical analysis in geosciences

Course: Geoinformation systems and Technologies

Structural unit: Educational and Scientific Institute "Institute of Geology"

Title
Applied mathematical analysis in geosciences
Code
ОК 19
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
5 Semester
Number of ECTS credits allocated
6
Learning outcomes
Apply the conceptual knowledge of natural and socio-economic sciences in the performance of tasks of geodesy and land management. Collect, evaluate, interpret and use geospatial data, metadata on objects of natural and man-made origin, apply statistical methods for their analysis to solve specialized problems in the field of geodesy and land management. Develop and make effective decisions on professional activities in the field of geodesy and land management, including in conditions of uncertainty.
Form of study
Full-time form
Prerequisites and co-requisites
Successful mastering of courses: higher mathematics, basics of geoinformatics
Course content
Within the framework of the discipline the applied aspects of the application of the apparatus of mathematical analysis, analytical geometry, probability theory and mathematical statistics to solve typical problems of Earth sciences, in particular, geoinformatics. An overview of modern systems of mathematical analysis as proprietary (Matlab, Mathematica, Maple, Mathcad) and freely distributed (Python, R, Scilab, Octave, Mupad). The collection of thematic applied problems of geology, geophysics and other areas using spatial data demonstrates the tools and capabilities of modern systems of mathematical analysis, provides theoretical and practical information on formalizing the problem, building and optimizing computational algorithms, their software implementation, debugging, thematic analysis and interpretation of the obtained results.
Recommended or required reading and other learning resources/tools
1. Martin H. Trauth (2015) MATLAB Recipes for Earth Sciences. Fourth Edition. © Springer-Verlag Berlin Heidelberg. 2. Swan ARH, Sandilands M (1995) Introduction to geological data analysis. Blackwell Sciences, Oxford. 3. Carr JR (1994) Numerical Analysis for the Geological Sciences. Prentice Hall, Englewood Cliffs, New Jersey. 4. Davis JC (2002) Statistics and Data Analysis in Geology, Tird Edition. John Wiley and Sons, New York. 5. Quarteroni A, Saleri F, Gervasio P (2014) Scientif c Computing with MATLAB and Octave – 4th Edition. Springer, Berlin Heidelberg New York. 6. Middleton GV (1999) Data Analysis in the Earth Sciences Using MATLAB. Prentice Hall, New Jersey. 7. William Haneberg (2004) Computational Geosciences with Mathematica. Springer Science & Business Media. 8. Bivand, R. S., E. J.Pebesma, and V.Gomez-Rubio (2008), Applied Spatial Data Analysis With R, 378 pp.,Springer, New York.
Planned learning activities and teaching methods
Lectures, practical training, self-study
Assessment methods and criteria
Evaluation organization: - modular test 1 (on vector-matrix operations in automated systems of mathematical analysis) involves an oral interview (maximum - 15 points) and control over the implementation of practical tasks (maximum - 15 points); - modular control work 2 (on statistical processing of data of geological and geophysical researches) provides control over performance of practical tasks (maximum - 10 points) and estimation of program realization of the set geological task (maximum - 20 points); - the final assessment is carried out in the form of quality control of the program implementation of the proposed examination tasks (4 tasks of 10 points each).
Language of instruction
ukrainian

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline