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Water Object Detection in Image
Čeloud, David ; Španěl, Michal (referee) ; Šilhavá, Jana (advisor)
Bachelor's thesis describes history of remote sensing, image data structure, their processing and analyzing. It defines mulstispectral space and explains basics of quantitative analysis and differences between supervised and unsupervised classification. Implementation section describes designing and developing of program, which will be able to open and process image data and detect water objects in him.
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Comparison of NATURA 2000 mapping with Earth Observation mapping (Case study of tundra in the Krkonoše Mts.)
Ondrušková, Kateřina ; Kupková, Lucie (advisor) ; Červená, Lucie (referee)
Comparison of NATURA 2000 mapping with Earth observation mapping (Case study of tundra in the Krkonoše Mts.) Abstract The bachelor thesis is focused on comparing Natura 2000 mapping with results of classification of Landsat 8 and WorldView-2 satellite images with different spatial resolution in the case study of tundra in the Krkonoše Mts. Satellite images were classified using Maximum Likelihood supervised classification and ISODATA unsupervised classification. The aim of the thesis was to find out what categories of Natura 2000 mapping are detectable using satellite images. For all classifications two levels of modified legend of the Natura 2000 mapping were used. The best results for both satellite images were achieved by unsupervised classification on level 1 of the legend - overall accuracy for Landsat 8 image was 64,1 % and for Word-View-2 image 67,16 %. Software ENVI 5.1 was used for all classifications. Keywords: Earth observation, supervised classification, unsupervised classification, legend, classification accuracy, NATURA mapping
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Water Object Detection in Image
Čeloud, David ; Španěl, Michal (referee) ; Šilhavá, Jana (advisor)
Bachelor's thesis describes history of remote sensing, image data structure, their processing and analyzing. It defines mulstispectral space and explains basics of quantitative analysis and differences between supervised and unsupervised classification. Implementation section describes designing and developing of program, which will be able to open and process image data and detect water objects in him.
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