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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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The de minimis regime and financing of Czech theatres
Jonášová, Helena ; DVOŘÁKOVÁ, Jana (advisor) ; SOUČKOVÁ, Jaroslava (referee)
This diploma master thesis focuses on the de minimis regime and its application within financing of theatres in the Czech Republic. The de minimis regime is one of the instruments of finance regulations of finance from public budgets, in relations to enterprises in the Czech Republic. As it is an instrument of so-called state aid with considerable selective features, is it a subject of thorough regulations by the European Union. These regulations thus directly affect legal systems of member countries of the EU.
The aim of the master thesis is to describe how the de minimis regime affects the opportunities of Czech theatres to receive financial support from public budgets and to find out how the legal acts of the European Union affect the financial situation of these theatres. The thesis also deals with the problem as seen from the point of view of providers of these financial supports so that it could be possible to reflect the issue as a whole.
The theoretical background of the thesis is formed by the relevant legal acts, issued by the European Commission and by the commentaries made about them. An inseparable part of this work is also grant calls of individual grant providers in the Czech Republic. The practical part of the master thesis is then based on thorough research of all Czech theatres with regards to their relations to de minimis issues. The master thesis also works with data provided by the Czech Register of the de minimis regime.
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First class primary school pupil and its adaptation in the social sphere from the perspective of parents and elementary school teachers
Součková, Jaroslava ; Kropáčková, Jana (advisor) ; Stará, Jana (referee)
The diploma thesis deals with the adaptation 1st class primary school pupils, to the school environment in social area. It is divided into theoretical and practical part. The theoretical part is focused on the process of adaptation pupil to the school environment, it explains the concept of socialization, analyzing school maturity, the readiness and the terms of school education. The practical part is based on a combination of quantitative and qualitative research. The method of questionnaire, interview and observation provides the identified data to deal with the issue of adaptation pupil at the 1st class primary school in the social field and analyzes the attitude of parents and first class teachers to the adaptation pupils to the school environment in the social sphere. The aim of the diploma thesis is analyzing the opinion to that issue by parents and first class primary school teachers.
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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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