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3D RECONSTRUCTION OF ABANDONED SETTLEMENTS OF THE CENTRAL POVLTAVÍ
Andrštová, Martina ; Štych, Přemysl (advisor) ; Jaroš, Jakub (referee)
3D reconstruction of abandoned settlements of the central Povltaví ABSTRACT This work deals with the use of Geoinformatic systems to create the three-dimensional model of an extinct landscape. The main subject of this bachelor work is the three-dimensional reconstruction of extinct municipalities in the central area of the Vltava River. The main task was to create digital terrain model of the original Vltava valley. The passage from Zvírotice to Svatojánské proudy has been chosen as the model territory. Two selected municipalities Zvírotice and Živohošť were thoroughly worked up. Many data sources were used in this work, such as historical photographs, historical aerial photographs or current orthophoto maps. Digital terrain models were created with the help of these datas and then the models were overlain with the orthophotos. 3D models of buildings and vegetation were put in the terrain models. Two periods were compared, 50th of the 20th century and present. Results of this work are fly-by animations and perspective scenes. The results will be used in newly built museum in Chotilsko town. Keywords: 3D reconstruction, DTM, land cover changes, orthophoto
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Hyperspectral data for classification of alpine treeless vegetation in the Krkonoše Mts.
Andrštová, Martina ; Kupková, Lucie (advisor) ; Potůčková, Markéta (referee)
Hyperspectral data for classification of vegetation of alpine treeless in the Krkonoše Mts. ABSTRACT The Master Thesis is a part of the HyMountEcos project, which deals with a complex evaluation of mountain's ecosystems in the Giant Mountains National Park using the hyperspectral data. The area of interest is alpine treeless in the Giant Mountains National Park. The main goal of this thesis was to create detailed methodology for classification of vegetation cover using hyperspectral data from AISA DUAL and APEX sensors, to find a classification method, which would improve the accuracy of the results compared to those found in the literature, and to compare the accuracy reached with these two types of the data. Many different classification algorithms (Spectral Angle Mapper, Linear Spectral Unmixing, Support Vector Machine, MESMA a Neural Net) were applied and the classification results were statistically evaluated and compared in the next part of the work. The classification method Neural Net was found as the most accurate one, as it gives the most accurate results for APEX data (the overall accuracy 96 %, Kappa coefficient 0,95) as well as for AISA DUAL data (the overall accuracy 90 %, Kappa coefficient 0,88). The resulting accuracy of the classification (the overall one and also for some classes) reached...
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Hyperspectral data for classification of alpine treeless vegetation in the Krkonoše Mts.
Andrštová, Martina ; Kupková, Lucie (advisor) ; Potůčková, Markéta (referee)
Hyperspectral data for classification of vegetation of alpine treeless in the Krkonoše Mts. ABSTRACT The Master Thesis is a part of the HyMountEcos project, which deals with a complex evaluation of mountain's ecosystems in the Giant Mountains National Park using the hyperspectral data. The area of interest is alpine treeless in the Giant Mountains National Park. The main goal of this thesis was to create detailed methodology for classification of vegetation cover using hyperspectral data from AISA DUAL and APEX sensors, to find a classification method, which would improve the accuracy of the results compared to those found in the literature, and to compare the accuracy reached with these two types of the data. Many different classification algorithms (Spectral Angle Mapper, Linear Spectral Unmixing, Support Vector Machine, MESMA a Neural Net) were applied and the classification results were statistically evaluated and compared in the next part of the work. The classification method Neural Net was found as the most accurate one, as it gives the most accurate results for APEX data (the overall accuracy 96 %, Kappa coefficient 0,95) as well as for AISA DUAL data (the overall accuracy 90 %, Kappa coefficient 0,88). The resulting accuracy of the classification (the overall one and also for some classes) reached...
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3D RECONSTRUCTION OF ABANDONED SETTLEMENTS OF THE CENTRAL POVLTAVÍ
Andrštová, Martina ; Štych, Přemysl (advisor) ; Jaroš, Jakub (referee)
3D reconstruction of abandoned settlements of the central Povltaví ABSTRACT This work deals with the use of Geoinformatic systems to create the three-dimensional model of an extinct landscape. The main subject of this bachelor work is the three-dimensional reconstruction of extinct municipalities in the central area of the Vltava River. The main task was to create digital terrain model of the original Vltava valley. The passage from Zvírotice to Svatojánské proudy has been chosen as the model territory. Two selected municipalities Zvírotice and Živohošť were thoroughly worked up. Many data sources were used in this work, such as historical photographs, historical aerial photographs or current orthophoto maps. Digital terrain models were created with the help of these datas and then the models were overlain with the orthophotos. 3D models of buildings and vegetation were put in the terrain models. Two periods were compared, 50th of the 20th century and present. Results of this work are fly-by animations and perspective scenes. The results will be used in newly built museum in Chotilsko town. Keywords: 3D reconstruction, DTM, land cover changes, orthophoto
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