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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Spectroscopic and statistical methods for detailed mapping of vegetation in the Krkonoše Mountains National Park
 Minárčik, Miroslav ; Kupková, Lucie (advisor) ; Potůčková, Markéta (referee)
Spectroscopic and statistical methods for detailed mapping of vegetation in the Krkonoše Mountains National Park Abstract The diploma thesis is focused on the detailed classification of vegetation in the Krkonoše Mountains National Park using DCA (Detrended Correspondence Analysis) ordination method in combination with PLSR (Partial Least Square Regression) analysis. The resulting regression analysis values were applied to the hyperspectral imagery (APEX). The classification results were compared to the supervised classification SVM (Support Vector Machine). The DCA method was able to explain 16,3 % variation for the first three axes of the ordination analysis. Subsequent correlation with spectral data of vegetation showed that the highest confidence value reached the first axis correlated with field spectral data (R2 = 0,56). The resulting classification map created using RGB composition showed detailed information on the composition of the vegetation. Keywords: The Krkonoše Mountains National Park, classification, APEX, DCA, PLSR, hyperspectral data
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Land-Cover classification of mountain ecosystem using image data with different spatial and spectral resolution
 Minárčik, Miroslav ; Kupková, Lucie (advisor) ; Kříž, Jan (referee)
Land-Cover classification of mountain ecosystem using image data with different spatial and spectral resolution Abstract The bachelor thesis is focused on land cover classification of the western part of the Krkonoše Mts. using multispectral images from WorldView-2 satellite with spatial resolution 2 m and from Landsat 8 satellite with a spatial resolution 30 m. The goal was to compare results of supervised classifications Maximum Likelihod and Support Vector Machine and unsupervised classification ISODATA for both images. The best result was achieved for WorldView-2 image using Maximum Likelihood classification (overall accuracy 73,1 %). The best result for Landsat image was achieved using Support Vector Machine classification (overall accuracy 70,78 %). Keywords: Krkonoše Mts., WorldView-2, Landsat 8, classification, multispectral image
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See also: similar author names
2 Minarčík, Martin
2 Minarčík, Michal
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