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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...
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Use of hyperspectral data for detection and classification of selected anthropogenic materials
Novotná, Kateřina ; Kupková, Lucie (advisor) ; Batistová, Jana (referee)
The thesis deals with use of hyperspectral data from APEX and AISA sensors for detection and classification of anthropogenic materials in the areas of Čáslav, Rokytnice nad Jizerou and Harrachov. The main goal is to propose methodology for the detection and classification of roof materials and road surface materials based on established spectral libraries. Another goal is to evaluate applicability of spectral libraries for classification, to compare possibilities of hyperspectral data with larger and smaller spectral range and to create maps of anthropogenic materials above. The methodological approach including masks of anthropogenic materials for roads surface materials and roof materials creation, settings of four classifications algorithms (Linear Spectral Unmixing, Multiple endmember spectral mixture analysis, Spectral Angle Mapper, Spectral Information Divergence) parameters and assessment of classification results, is in the methodology part. The results are visualized and evaluated using overall accuracy and percentage of classified pixels. Finally the results are compared with existing studies and possible improvements for further research are proposed. Powered by TCPDF (www.tcpdf.org)
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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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Proximity of schools to sources of air pollution: Estimation of health risk by GIS methods
Strejčková, Denisa ; Braniš, Martin (advisor) ; Kupková, Lucie (referee)
This diploma thesis deals with the estimation of potential health risks at schools exposed to traffic-related air aollutants. It is based on the method of a geographic information system (GIS). Road traffic is a source of suspended particles, whose long-term exposure has an effect on the growth of the lower respiratory tract disease, chronic obstructive pulmonary disease, reduction of lung function and cardiovascular disease, especially in the large urban agglomerations. Besides the long and seriously ill and the elderly, children belongs to the particularly vulnerable group of population. Children used to spend a great deal of time at schools. Many scientific studies have found associacions between proximity to traffic and increased risk of respiratory disease and a slower development of lung function among children attending schools close to busy roads. One of the aims of this study is to locate elementary schools in the region of Prague by GIS techniques and examine, whether the aquality of air in the place where schools stands to is influenced by the traffic air pollution. Although the estimation of the potential health risk is based on indirect methods of GIS, it is possible, that high concentrations of pollutants could infiltrate into the most exposed schools and cause adverse health effects,...
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Laboratory and image spectroscopy for mapping of selected rocks in peak areas of the Krkonoše Mountains
Kubečková, Jana ; Kupková, Lucie (advisor) ; Potůčková, Markéta (referee)
Laboratory and image spectroscopy for mapping of selected rocks in peak areas of the Krkonoše Mountains Abstract This thesis deals with geological mapping of selected rocks in peak areas of the Krkonoše Mountains. Four areas of interest were situated in two parts of Krkonše Mountains - on the west side it is the area of Vysoké kolo and Harrachovy kameny and on the east side there is the area of Sněžka and the area of Kozí hřbety. The main data were acquired by the hyperspectral sensor APEX. Ground spectral measurments of selected rocks and block fields were executed and the laboratory spectral measurments of geological samples and lichens were executed. Practical part aims at classification of rocks and lichens in selected areas using four classification methods: SAM, SID, MESMA and LSU. The spectral library is one of the outputs of this thesis. This spectral library contains the spectra of pure rocks and lichens and mixtured spectra of rocks and lichens. The output of this thesis is the comparation of used classification methods, the analysis of spatial and geological accuracy and evaluation of lichens influence on the classification results, spectral library and maps of classified rocks occurrence. Keywords: classification, block fields, hyperspectral data, spectral mixture, lichens, The Krkonoše Mountains
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Possibilities of remote sensing in grassland vegetation and management interventions monitoring in the Giant Mountains
Pomahačová, Michaela ; Kupková, Lucie (advisor) ; Hais, Martin (referee)
Possibilities of remote sensing in grassland vegetation and management interventions monitoring in the Giant Mountains Abstract The aim of this thesis was to evaluate suitability of WorldView-2 imagery for grassland associations classification in the model area of Giant Mountains. The classification was based both on the legend compiled by a botanist, and on the legend of Natura 2000. In order to eliminate the effects of other types of land cover on the classification accuracy, a mask of grasslands was created. Using discriminant analysis, the significance of spectral bands of WorldView-2, as well as signifikance of selected vegetation indices and components from Principal Component Analysis (PCA) - to distinguish particular classes of grassland vegetation were evaluated. Based on the results of discriminant analysis, classifications using neural networks method and also maximum likelihood method were performed in ENVI 4.7 version software. The results of the both method were compared Key words: remote sensing, meadows association, classification, Giant mountains, WorldView 2
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Utilization of airborne laser scanning data for the detection of agrarian forms of relief in the Giant Mountains
Jebavá, Lucie ; Kupková, Lucie (advisor) ; Potůčková, Markéta (referee)
Utilization of airborne laser scanning data for the detection of agrarian forms of relief in the Giant Mountains Abstract This thesis deals with the possible use of airborne laser scanning data for the detection of agrarian forms of relief in the Giant Mountains. The main research method is the analy- sis of the digital terrain model and digital surface model in the area of the Giant Mountains in the software ArcGIS 10.0. The analysis is based on specific functions in ArcGIS software (Slope, Curvature) as well as on combinations of rasters of shaded reliefs which led to the detection of further agrarian forms. To verify the precision of agrarian forms detection field verification was used. Based on verification and accuracy assessment the results can be designated as a very satisfactory. The Administration of the Giant Moun- tains National Park can use the research results to quantify the agrarian forms of relief, to improve their protection and, possibly also for further research and management. Keywords: airborne laser scanning, agrarian forms of relief, anthropogenic geo- morphology
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Monitoring of water eutrofization in model reservoir of Czech republic by remote sensing data
Běhounová, Petra ; Štych, Přemysl (advisor) ; Kupková, Lucie (referee)
Present study compares possibilities of monitoring water eutrophication in the Czech republic using remote sensing. The theoretical part describes basic spectral characteristics of water and their change caused by eutrophication. Chlorophyll-a was chosen as the quantitative indicator of trophic rate. Methods of obtaining value of chlorophyll-a content from scanner TM and ETM+ Landsat satellite data and from in situ measurements data are described. Three regression equations, that employ variety of channels or channel ratios of Landsat data were utilized. The regression equations were applied on three satellite images of model area of Vltava's steps (water reservoirs of Lipno, Hnevkovice, Korensko and Orlík) from the years 2001, 2004 and 2007. The regression equation ln(chl-a) = a.TM2 + b.TM3 + c.TM4 +d gives the best results, where the determination coefficient varies from 0,245 to 0,422. Maps showing distribution of chlorophyll-a concentration in water reservoir Lipno and in the part of water reservoir Orlík were created based on obtained results. Powered by TCPDF (www.tcpdf.org)
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Evaluation of global changes of forest land based on remote sensing
Hladká, Anna ; Štych, Přemysl (advisor) ; Kupková, Lucie (referee)
Evaluation of global changes in forest area based on remote sensing data Abstract: The aim of this project is using remote sensing data to assess change in global forest area. This work should give the outline of the principles of land cover classification, with a focus on forests based on satellite images, but also show a real solution in the evaluation of changes in forest areas in two selected regions. The first part is performed a literature review of all aspects of this sub-topic from the basic principles of remote sensing across the typology and characteristics of satellite sensors, which are giving the satellite images to land cover classification systems and characteristics of forest area. The next section describes the basic procedure for classification of satellite imagery and its possible variants. In my work there are explain the image corrections, the supervised and unsupervised classification, the method of checking the accuracy of classification or use of software. Selected area for my work was Riau in Indonesia and state of Oregon, USA. To these regions there are demonstrated practical procedure for classifying land cover and then its changes from the forest areas. In conclusion of my work the results are discussed and compared with available land cover databases. Key Words: Remote Sensing,...
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Analysis of the Frequency of Connections in Czech Rail Transport
Ambrož, Jiří ; Hudeček, Tomáš (advisor) ; Kupková, Lucie (referee)
Analysis of the frequency of connections in Czech railway transport Abstract This paper deals with cartographic representation of frequency of connections in maps and with analysis in suitable level using software ArcGIS 9.3. Theoretical part is aimed at train categories and use of GIS mainly in analysis of traffic accessibility. Next there is a description of used methods which are isoline and cartodiagram. The main part of the paper discribes a creation of relevant data layers and methodology of data capture. Here is also evaluation of the results and suitability of used methods. The frequency of connections is devided into two types. Their differences are discussed in final section where is also warning about several complications that occurred during the work. The main output are two maps for the Czech Republic and one for Středočeský district. Keywords: frequency of connections, accessibility, cartographical methods, railway transport
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