Remote sensing  

Lecture: Physical basics of remote sensing. Energy relations between Sun - object - sensor. Absorption bands in the electromagnetic spectrum and atmospheric windows used in remote sensing. Spectral characteristics of objects: measurement methods, spectral curves of typical objects and the influence of various factors on their course, the meaning of spectral characteristics knowledge in remote sensing. Aerial images: panchromatic, black-and-white infrared, color, color-infrared and multispectral. Characteristics of images in terms of interpretation tasks. Methodology of aerial image interpretation, typical relations: object - the look of object in different images. Visual and digital methods of interpretation, the logic of image interpretation. Aerial and satellite scanners: methods of imaging using scanners, the essence of digital format, image structure in digital format. Basic information on meteorological, optical and radar satellites. Characteristics of selected satellite systems, including Landsat, SPOT, Sentinel-2, WorldView, GeoEye, Plejades, Radarsat, TerraSAR-X. General information concerning digital image processing, color composite, image classification, creating a satellite map. Examples of remote sensing techniques usage in various fields of the economy. Remote sensing data as a data source for GIS. Exercises: Recognition and interpretation of objects in aerial images in selected band of the visible spectrum and black-and-white infrared images, the relation between spectral characteristics of object and its shade of grey in the image. Relations between shades of grey in the optical (visible spectrum) and infrared images. The update of selected elements in indicated spatial database using open-access remote sensing data. Basics of creating color composites. Landscape analysis on Sentinel-2 color composites. Creating image interpretation key based on satellite images.
Presential
English
Remote sensing
English

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