Semester: 6
ECTS: 5
Lectures: 30
Practice sessions: 30
Independent work: 90
Module Code: 24-121-0139
Semester: 6
ECTS: 5
Lectures: 30
Practice sessions: 30
Independent work: 90
Module Code: 24-121-0139

Module title:


Application of satellite and radar images in remote sensing

Lecturers and associates:



Module overview:


This optional module introduces students to the extended concepts of remote sensing through an introduction to satellite and other remote data collection systems, their processing and visualization methods. The main objectives of the module are:
Become familiar with the remote survey data manipulation methods and data sources.
Become familiar with the types of optical data sources in remote sensing.
Become familiar with the types of microwave data sources in remote sensing.
Learn the types and methods of analysis and processing of raster data obtained by remote sensing.
Learn the types and methods of pixel classification of raster.
Learn the types and methods of object classification of raster.

The module requires basic previous experience in working with spatial data and an understanding of terms used in geoinformatics and remote sensing. It is taught using more advanced practical examples to gain a functional level of use of the newly acquired knowledge as soon as possible. Module evaluation is based on solving various tasks in available software packages and developing own more advanced solutions in the development environment and their visualizations.
In this module students will learn:
which remote sensing methods are suitable for which types of practical applications.
how to find suitable data depending on the need.
what is georeferencing of raster data and how to apply it for non-georeferenced data.
what is orthorectification and how to collect control points and apply relief models in orthorectification.
what is pixel analysis of an image, for which applications is it used and in what ways and with which algorithms can the problem of spatial data be best approached to reach valid conclusions.
types and methods of subpixel analyses.
what is the segmentation of images and why is it needed, and what are the geometric primitives that are a direct result of the segmentation.
what is object analysis of an image, for which applications is it used and in what ways and with which algorithms can the issue of spatial data be best approached to make valid conclusions based on geometric primitives.
what is the difference between pixel and object analysis methods and when to apply which.

Literature:


Required readings:
1. Lillesand, T., Kiefer W. R., Chipman, J. (2015) Remote sensing and image interpretation. 7th edn. Hoboken: John Wiley and Sons.

Supplementary readings:
1. Green, K., Congalton, R. G., Tukman, M. (2017) Imagery and GIS: best practices for extracting information from imagery. Redlands: Esri Press.