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Costing in the Selected Firm
Součková, Jana ; Lásková, Helena (referee) ; Hanušová, Helena (advisor)
This master’s thesis is focused on costing of company Jihlavan a.s. It consists from two main parts: theoretical base and analysis of current company situation. There are explained terms of cost and costing in the first part and system of creating of company costing in the second part. There are recommendations for quality improvement on base of performed analysis in last part of this thesis.
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Determination of Snow Cover Area from RADAR imagery
Součková, Jana ; Potůčková, Markéta (advisor) ; Brodský, Lukáš (referee)
This thesis deals with snow cover mapping by using time-series of SAR images of the sensors ENVISAT ASAR and TerraSAR-X. The methodology is based on the so-called Nagler's algorithm, which is based on determination of the change of absorption of radar signal due to the liquid water content in the snow cover. The resulting ratio image is classified into the areas with wet snow or without it according to the selected threshold value. The results are compared with the maps of snow cover derived from MODIS optical data and with data from meteorological stations of CHMI. The main aims of this work are to suggest most suitable conditions (time of the year, weather) for acquisition of reference images, to find the change of the threshold value with respect the chosen reference image and the type of land cover. The same methodology should then be applied on the radar data of shorter wavelength. The obtained results will be further used for improving the methodology of snow cover mapping from SAR data in the Czech Republic.
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Land cover changes in Bohemian Switzerland using remote sensing data
Lihanová, Kristýna ; Štych, Přemysl (advisor) ; Součková, Jana (referee)
Land cover changes in Bohemian Switzerland using remote sensing data Abstract The purpose of this project was to classify land cover in The National Park Bohemian Schwitzerland from LAMDSAT data (1999, 2002, 2009), FORMOSAT data (2006) and QuickBird data (2009). Data used in this paper are described in details. The method used for images classification was method of unsupervised classification in Geomatica program. Created classes were merged into the final five classes. An Assessment of accuracy of classification showed that results don't reflect reality. Mixed forests are the biggest problem because they can be mistaken for coniferous or deciduous forests. Classification results were smoothed low pass filer and converted into a vector formats in ArcGIS program. For the years 2006 and 2009 was counted the vegetation indexes NDVI and LAI. Results showed that the densest vegetation is in deciduous forests. Changes in land cover were assessed in two ways. Shares of each class were calculated for all years. Overlays layers are created in ArcGIS. Overlap was conducted between 1999 and 2002 and between 1999 and 2009. Most changes were found between the coniferous and mixed forests. These changes are caused by the inaccuracies in classification. Key words: land cover, Bohemian Switzerland, forest, Landsat,...
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An Analysis of the Subject Humans and Their World in the Framework of an Educational Programme
Součková, Jana ; Kalbáčová, Jaroslava (advisor) ; Linková, Marie (referee)
V této diplomové práci se snažím odpovědět na otázku, jak vidím uplatnění zásad RVP ve své pedagogické praxi za současných podmínek a při použití stávajících učebních materiálů. Podávám zde v proto stručný přehled učebnic s akreditací MSMT, s nimiž se nyní ve školách pracuje a které byly pochopitelně napsány i vydány dříve, než byl vytvořen RVP. V přehledu uvádím učebnice vzdělávacích programů základní škola, obecná škola i národní škola. Obsah předmětů prvouka i vlastivěda se u jednotlivých koncepcí příliš neliší a všechny zhruba odpovídají i RVP. Powered by TCPDF (www.tcpdf.org)
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Using SAR data for wet snow monitoring
Matyáš, Jiří ; Kolář, Jan (advisor) ; Součková, Jana (referee)
Using SAR data for wet snow monitoring Abstract This paper focuses on an existing method of snow information retrieval by means of satellite SAR data. The method was first presented by Malnes and Guneriussen (2002), and has been proven to be capable of sub-pixel classification of wet snow. It is also able to classify dry snow pixels. The classification is based on change detection, so a snow-free reference image is required. Some flaws in this algorithm have been discovered during the work on this paper and are discussed, as well as a possible solution is suggested. I have also proposed a modification of the algorithm which could improve the classification results and tested the modified algorithm. Keywords: SAR, snow cover, remote sensing, wet snow
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Radar data in the land use/land cover change
Gerschon, Jan ; Štych, Přemysl (advisor) ; Součková, Jana (referee)
This bachelor thesis is focused on processing and classification of radar data. The images recorded in 2009 by the AMI-SAR sensor placed on the ERS-2 satellite were used for a pixel and object-based classification of agricultural land. The classifications were tested for two selected areas of interest. The legend was taken from the LPIS database and includes three classes - arable land, grassland and a class that involves hop fields, vineyards, and orchards. Preprocessing of the images was held in the NEST software and the subsequent classification in the ENVI software. The classification outcomes were compared and it was found out that the object classification seems to be significantly better using the SVM algorithm. The best result of the classification reached the overall accuracy of 90.74 % and the Kappa coefficient of 0.5. Powered by TCPDF (www.tcpdf.org)
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Radar data in the land use/land cover change
Gerschon, Jan ; Štych, Přemysl (advisor) ; Součková, Jana (referee)
This bachelor thesis is focused on processing and classification of radar data. The images recorded in 2009 by the AMI-SAR sensor placed on the ERS-2 satellite were used for a pixel and object-based classification of agricultural land. The classifications were tested for two selected areas of interest. The legend was taken from the LPIS database and includes three classes - arable land, grassland and a class that involves hop fields, vineyards, and orchards. Preprocessing of the images was held in the NEST software and the subsequent classification in the ENVI software. The classification outcomes were compared and it was found out that the object classification seems to be significantly better using the SVM algorithm. The best result of the classification reached the overall accuracy of 90.74 % and the Kappa coefficient of 0.5. Powered by TCPDF (www.tcpdf.org)
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Using SAR data for wet snow monitoring
Matyáš, Jiří ; Kolář, Jan (advisor) ; Součková, Jana (referee)
Using SAR data for wet snow monitoring Abstract This paper focuses on an existing method of snow information retrieval by means of satellite SAR data. The method was first presented by Malnes and Guneriussen (2002), and has been proven to be capable of sub-pixel classification of wet snow. It is also able to classify dry snow pixels. The classification is based on change detection, so a snow-free reference image is required. Some flaws in this algorithm have been discovered during the work on this paper and are discussed, as well as a possible solution is suggested. I have also proposed a modification of the algorithm which could improve the classification results and tested the modified algorithm. Keywords: SAR, snow cover, remote sensing, wet snow
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Evalution of forest vegetation in National park Šumava by using remote sensing data
Kolešová, Petra ; Štych, Přemysl (advisor) ; Součková, Jana (referee)
EVALUATION OF FOREST VEGETATION IN NATIONAL PARK ŠUMAVA BY USING REMOTE SENSING DATA Abstract: The goal of this work was to evaluate the changes of forest land cover in NP Šumava. It include health, species specification and also the evaluation of the landscape type changes per time by using satellite high- and very-high resolution screening between 1995 - 2010. In background research, the importance of remote-land-search in general and specially in forestry was analysed. Furter more, the theoretical background for used methods was described, f.e. classification, "tresholding" or the NDVI and LAI vegetation index Metod . The last one was used for tree healthiness detection and different forest species composition was classified. In practical part the detailed procedure of classification and the creation of the vegetation indexes has been described. In epilogue the achieved result were evaluated, discussed and compared with subject publications. Key Words: Repote Sensing, Forests, Classification, Vegetation Index, Spruce Bark Beetle, National Park Šumava
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Cult Terminology in Old Hittite Texts
Velhartická, Šárka ; Zemánek, Petr (advisor) ; Rychtařík, Marek (referee) ; Součková, Jana (referee)
Univerzita Karlova v Praze Filozofická fakulta Ústav srovnávací jazykovědy Jazyky zemí Asie a Afriky Šárka Velhartická Kultovní terminologie starochetitských textů Cult Terminology in Old Hittite Texts Disertační práce vedoucí práce - Doc. PhDr. Petr Vavroušek, CSc. 2011 ABSTRAKT V ČESKÉM JAZYCE Univerzita Karlova v Praze Filozofická fakulta Ústav srovnávací jazykovědy Jazyky zemí Asie a Afriky Šárka Velhartická Kultovní terminologie starochetitských textů Cult Terminology in Old Hittite Texts Disertační práce vedoucí práce - Doc. PhDr. Petr Vavroušek, CSc. 2011 Cílem disertační práce "Kultovní terminologie starochetitských textů" je vytvoření uceleného přehledu všech dnes nám známých chetitských textů datovaných do starochetitského období s důrazem na texty rituálního charakteru. Základním východiskem jsou detailní kriteria datace klínopisných textů (paleografický rozbor, grafická a lingvistická analýza pramenů) a jejich přesná definice, které tvoří úvod k následné prezentaci jednotlivých textů. Hlavní část práce je rozdělena do dvou oddílů. První z nich je výčet starochetitských textů a jejich překlad do českého jazyka. V případech, kdy se jedná o dosud nezpracované rituální texty, nebo texty, jejichž transkripci je nutno doplnit a pozměnit na základě nově získaných fragmentů, přináší autorka i jejich...
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