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Analysis of tundra vegetation developement using a time series of ortoimages in the Krkonoše Mountains
Pajmová, Petra ; Kupková, Lucie (advisor) ; Potůčková, Markéta (referee)
Analysis of tundra vegetation developement using a time series of ortoimages in the Krkonoše Mountains Abstract The aim of this study is to analyse changes in arctic-alpine tundra vegetation in the Krkonoše Mountains using archival and current aerial imagery with red, green and blue bands and spatial resolution of 0.5 m. Three small areas of interest (cca 100 100 m) with different types of vegetation and a one larger area of the eastern tundra were studied. Several classification methods (Maximum likelihood classification, Random forest and object-based classification) were tested to obtain the best classification results. For more detailed analysis of grass species development, unsupervised classification and extended time series (5 orthoimages) were used for the area of Bílá louka. Classification were executed in softwares ENVI 5.5 and R 4.2.1. The highest overall accuracy of the 2020 image classifications were over 70% in all study areas, in some cases over 80%. With the exception of the Luční hora area (58%), the best overall accuracies for 2004 image were above 65%. After comparing classification results between years 2004 and 2020, a possible development trend was revealed. But due to low accuracy of the 2004 data classifications, this cannot be reliably demonstrated. Key words: classification,...
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Automatic detection of zebra crossings from aerial images
Tomíček, Jiří ; Potůčková, Markéta (advisor) ; Fiala, Radek (referee)
There are a number of studies that deal with detection of road network from image Remote Sensing data. However, little work has been done on algorithms for horizontal road signs detection from Remote Sensing data. On the other hand there are many papers that deal with horizontal road signs detection in the field of Computer vision. Theoretical part of master thesis sumarizes the methods that are used to detect objects from both, Remote Sensing and Computer vision data. In the practical part an algorithm of automatic Zebra-crossing detection based on Aerial Images and vector road layer is designed. Zebra-crossings are detected using matching of image with set of predefined patterns. Obtained set of potential objects is then filtred using geometric and relational criteria. At the end of this thesis, the proposed algorithm is validated and the results are discussed with literature. Key words: Zebra-crossing, Horizontal road signs, Image matching, Aerial images
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