National Repository of Grey Literature 14 records found  1 - 10next  jump to record: Search took 0.01 seconds. 
Laboratory/Field Spectroscopy and Remote Sensing Image Data for Vegetation Studies
Červená, Lucie ; Kupková, Lucie (advisor) ; Pavelka, Karel (referee) ; Müllerová, Jana (referee)
Dominant vegetation species of two structurally and functionally different montane ecosystems were studied by means of laboratory and field spectroscopy and remote sensing image data: (1) a homogeneous human-influenced evergreen coniferous forest represented by a Norway spruce forest in the Krušné hory Mountains and (2) a heterogeneous natural ecosystem of a relict arctic-alpine tundra in the Krkonoše Mountains with predominance of grasses. The first part dealing with the Norway spruce forest is especially focused on the methods of laboratory spectroscopy. The assessment of Norway spruce stands on a regional and a global scales requires detailed knowledge of their spectral properties at the level of needles and shoots in the beginning, but ground research is very time-demanding. Open spectral libraries could help to get more ground-truth data for subsequent analysis of tree species in forests ecosystems. However, the problem may arise with the comparability of spectra taken by different devices. The present thesis focuses on a comparability of spectra measured by a field spectroradiometer coupled with plant contact probe and/or two integrating spheres (Paper 3) and proves the significant differences in spruce needle spectra measured by the contact probe and integrating sphere, spectra of...
The influence of spectral resolution on land cover classification in Krkonoše Mts. tundra
Palúchová, Miroslava ; Červená, Lucie (advisor) ; Kupková, Lucie (referee)
The influence of spectral resolution on land cover classification in Krkonoše Mts. tundra Abstract The aim of this diploma thesis was to specify the spectral resolution requirements for classification and to identify the most important spectral bands to discriminate classes of the predefined legend. Aerial hyperspectral data acquired by AisaDUAL sensor were used. The method applied for the selection of the important bands was discriminant analysis performed in IBM SPSS Statistics. The most discriminative bands were found in intervals 1500-1750 nm (beginning of SWIR), 1100- 1300 nm (longer wavelengths of NIR), 670-760 (red-edge) and 500-600 nm (green light). The classification of the selected bands was realized in ENVI 5.4 using the Support Vector Machine classifier, achieving overall accuracy of 80,54 %, Kappa coefficient 0,7755. The suitability of available satellite data for the classification of tundra vegetation in Krkonoše mountains based on spectral resolution was evaluated as well. Keywords: tundra, Krkonoše, classification, spectral resolution, class separability, discriminant analysis, hyperspectral data
Changes of land cover above the tree line in Krkonoše National Park based on Landsat data
Vyvialová, Linda ; Červená, Lucie (advisor) ; Suchá, Renáta (referee)
CHANGES OF LAND COVER ABOVE THE TREE LINE IN KRKONOŠE NATIONAL PARK BASED ON LANDSAT DATA Abstract This study evaluates land cover changes in the area above the tree line in Krkonoše Mts. National Park. The stress is put on the changes of Pinus mugo shrub. Two methods of change detection based on Landsat data in four time horizons from the eighties up to now were tested (years 1984, 1992, 2002 and 2013). The first method was classification of scenes with the Maximum Likelihood Classifier individually and evaluation of changes based on their overlay. Overall accuracies from the oldest scene were 86,04 %, 88,44 %, 86,91 % and 86,43 %. The second method evaluates detection of change above one dataset that consists of scenes for all the time horizons. Overall accuracies were from the oldest 86.63 %, 88.64 % and 86.11 %. The second method was more appropriate for this study of land cover changes. On the map results there can be seen thinning of Pinus mugo scrub (between the years 2002 and 2013, 1984 and 1992) as well as its natural thickening and spreading. Key words KRNAP, tundra, land cover, change detection, Landsat
Preparation of Dishes in Primary School Education
This master thesis deals with three topics in the theoretical part. The first part focuses on project method at primary school education; in the second part the goals and output competences of a pupil at primary education according to Framework training programme for primary schools can be found. Finally a chapter about creativity in the subject "practical activities" and introduction to history of food culture in last centuries concludes the theoretical part. In the practical part ten projects that focus on the food preparations and culture in the teaching are created. These are intended for the fourth and fifth classes of primary schools. A part of it are also preparations of the meals, experience from realisation of some projects, advantages and disadvantages, reactions of pupils or formulations of more general recommendations for the use of original educational projects.
Classification of forests damaged by disturbance using multispectral satellite data
Šmausová, Barbora ; Štych, Přemysl (advisor) ; Červená, Lucie (referee)
The main objective of this thesis is to create an appropriate methodological procedure for classifying damaged forest in the selected area of Šumava National Park. For this purpose, multispectral imagery WorldView-2 and Landsat 8 are used. Work emphasis on distribution of each phase of forest development affected by bark beetle. According to selected legend, involving multiple stages of damaged but also recovering forest, the images are classified by Neural Network, Support Vector Machine and object classification methods. Application of these methods on selected images required a suitable choice of parameters and rules to achieve optimal results. The results of this thesis compare and evaluate the final classification. Another outcome of this work is to evaluate the influence of the processed images WorldView-2 and Landsat 8 on the final classification performance. All work results are assessed by overall precision, error matrix and kappa coefficient. Powered by TCPDF (
Comparison of NATURA 2000 mapping with Earth Observation mapping (Case study of tundra in the Krkonoše Mts.)
Ondrušková, Kateřina ; Kupková, Lucie (advisor) ; Červená, Lucie (referee)
Comparison of NATURA 2000 mapping with Earth observation mapping (Case study of tundra in the Krkonoše Mts.) Abstract The bachelor thesis is focused on comparing Natura 2000 mapping with results of classification of Landsat 8 and WorldView-2 satellite images with different spatial resolution in the case study of tundra in the Krkonoše Mts. Satellite images were classified using Maximum Likelihood supervised classification and ISODATA unsupervised classification. The aim of the thesis was to find out what categories of Natura 2000 mapping are detectable using satellite images. For all classifications two levels of modified legend of the Natura 2000 mapping were used. The best results for both satellite images were achieved by unsupervised classification on level 1 of the legend - overall accuracy for Landsat 8 image was 64,1 % and for Word-View-2 image 67,16 %. Software ENVI 5.1 was used for all classifications. Keywords: Earth observation, supervised classification, unsupervised classification, legend, classification accuracy, NATURA mapping
Possibilities of object-based classification for selected biotopes above tree-line in the Krkonoše Mts. National Park detection
Jakešová, Lucie ; Červená, Lucie (advisor) ; Potůčková, Markéta (referee)
Possibilities of object-based classification for selected biotopes above tree-line in the Krkonoše Mts. National Park detection Abstract The bachelor thesis is focused on the object-based classification of vegetation above the tree-line in the Krkonoše Mts. National Park using orthophoto with near infrared band and spatial resolution of 12.5 cm. Orthophoto was acquired in summer 2012. The classification legend was compiled by botanist of the national park. Software ENVI 5.1 was used for object-based classification using the field data. It provides two approaches to classification - Example-based and Rule-based. The overall accuracy of the best classification result was 75.97 % for 13 classes. Keywords: object-based classification, KRNAP, biotopes above tree-line, aerial optical scanner
Land cover changes in military areas of Czechia
Outrata, David ; Štych, Přemysl (advisor) ; Červená, Lucie (referee)
1 Land cover changes in military areas of Czechia The aim of this bachelor thesis was to analyze and compare land cover changes in two areas affected by military activities, in military area Brdy and former military area Ralsko between 1986, 1998 and 2011. Maximum Likelihood supervised classification algorithm and Landsat 5 satellite images was used. Within the work was also examined the usability of Landsat images CDR, with atmospheric corrections applied. Reference data to gain control data were RGB and monochromatic aerial images. The classification system contained eight classes adapted to explored territory. Satellite photographs was classified on surveyed territories for the years 1986, 1998 and 2011, with overall classification accuracy ranged from 80.45% to 90.02%.With these data was further worked, and tables and graphs showing the area of individual land cover in the given time horizons was compiled. Outputs are also land cover maps, change maps and stable land cover maps. The expected trend that in the former military area after leaving the army land cover changed significantly, contrary to the current military area, where changes are minor, was confirmed. Key words: land cover changes, supervised classification, Landsat, Landsat CDR, military areas, Brdy, Ralsko, Geomatica, ArcGIS
Tick-borne encephalitis risk assessment based on classification of vegetation from remote sensing data
Červená, Lucie ; Potůčková, Markéta (advisor) ; Pavelka, Karel (referee)
Tick-borne encephalitis risk assessment based on classification of vegetation from remote sensing data Abstract The main aim of this thesis has been to find out how to classify various categories of forest vegetation with a different risk of exposure to the tick-borne encephalitis based on the Landsat imagery. The legend used here is derived from the one used in the projects by Daniel, Kolář, Zeman (1995) and Daniel, Kolář, Beneš (1999) but has been reduced to only five classses with no overlaps in their definitions (I. coniferous stands, II. mixed stands, III. young deciduous stands and stand ecotones with a highly heterogeneous structure, IV. deciduous stands with a homogeneous structure, V. deciduous stands with a heterogeneous structure). The supervised classification with the Maximum Likelihood Classifier has been used on the Landsat imagery from various seasons. Difficulties concerned with the presence of clouds and varying Sun elevation across the imagery had to be adressed in the course of the work. The training sites and the control points have been defined by the field research and interpretation of the relevant orthophotomaps and Landsat imagery in 5-4-3 RGB composite. The mask of the forest has been created on the ZABAGED data basis. The time horizon of 2006 - 2010 has been the primary focus....

National Repository of Grey Literature : 14 records found   1 - 10next  jump to record:
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8 ČERVENÁ, Lucie
2 Červená, Lenka
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