Remote sensing 2  

General Introduction to software. Raster images - basic features, notation, formats, metadata. Image visualization, the concept, and role of the histogram. Image quality improvement; contrast enhancement with a linear function and non-linear functions, visual evaluation of the quality of processed images. The creation of color compositions in various combinations and the overall assessment of the information content - the importance of selecting specific channels, selecting the contrast enhancement function, and the RGB filters assignment method. Interpretation of the image of color composition and the knowledge of spectral characteristics of objects. Vegetation condition analysis using the NDVI and TASSCAP index. Combining panchromatic and multispectral data - examples using the following methods: RGB transformation => HLS => RGB, val. the mean of (MS + PAN). Digital classification of land cover forms in a supervised approach - initial assumptions, class definition, preparation of training fields, analysis of statistics (signatures), assessment of the correctness of classes and preparation of training fields, classification with the use of selected algorithms. Assessment of the accuracy of the thematic digital classification of land cover classes.
Presential
English
Remote sensing 2
English

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