Advanced classification algorithm of raster data 1900-3-ZAK-KT
Giving knowledge and practical skills of advanced rules of classification and preprocessing remote sensing images to this process.
The course is dedicated to familiarize students with the idea of use of hyperspectral remote sensing for environmental studies. Will be presenter aerial and satellite hyperspectral images.
Preprocessing (calibration and correction), the creation of local spectral libraries and their application. The student learns the advanced methods of hyperspectral data classification.
Type of course
Mode
Prerequisites
Prerequisites (description)
Learning outcomes
Acquiring of practical and theoretical knowledge about basic rules of digital processing of satellite images.
Assessment criteria
Evaluation of the course is based on the exercises that the student performs during the classes and the exam (oral and practical).
Practical placement
-
Bibliography
Zagajewski B., Sobczak M., (red.) 2005. Imaging spectroscopy. New quality in environmental studies. EARSeL, Uniwersytet Warszawski WGiSR, Warszawa
ERDAS Field Guide, przewodnik geoinformatyczny, 1998. GEOSYSTEMS Polska, Warszawa.
Jensen J.R., 1996. Introductory digital image precessing – a remote sensing perspective. 2ed ed. Prentice Hall.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: