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Forest species determination from satellite data
Launer, Michal ; Kolář, Jan (advisor) ; Kupková, Lucie (referee) ; Brodský, Lukáš (referee)
Forest species determination from satellite data Abstract Examining the species composition of forests from satellite imagery is constantly evolving. The new ways of exploring forests from the satellites make it easier for foresters to maintain a more accurate and up-to-date overview of the state of forests. In this work, the research was made on the forests in the cadastral territories of Osvětimany and Buchlovice in the Chřiby Mountains in the Czech Republic. In this work, data from the Landsat-8 satellite from three seasons and the Maximum Likelihood Classification method were used. The reference maps were used as reference data. The method of work consists in the fact that 6 frames were classified with the help of training sets using Maximum Likehood Classification. Subsequently, the pixels which were at least 4 times out of 6 ranked in the same class after the classification were selected. Based on these pixels, artificial training sets were calculated for each of the 6 frames, and they were used for another classification with the expectation of better results. The accuracy of the individual classification frames was verified by an error matrix on the crop maps. Keywords: remote sensing, forest canopy, forest tree types, forestry map
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Land cover change detection on the agriculture land
Klouček, Tomáš ; Štych, Přemysl (advisor) ; Brodský, Lukáš (referee)
The main purpose of thesis is creation and evaluation of models for change detection of arable land to grassland by Hybrid-based Change Detection method, which combined approaches based on the Vegetation Indices, Image Differencing and Principal Component Analysis. Six locations with different seasonal configuration of images with high resolution and one locality covered by image with very high resolution were used. The areas were spread across the foothill areas of the Czech Republic. The selection of predictors and the most suitable model was supported by statistical calculation. Application selected models were carried out using a multi-temporal object classification and their accuracy were verified using reference data. The benefit of this thesis is finding generally applicable model useful to investigate the land cover change and evaluation of the potentially most appropriate seasonal configuration of images. Valuable is also methodology in this thesis which focus on selection of predictors and calculation the order of the most appropriate models, which is unique in the available literature. The thesis provides useful findings fitting to insufficiently explored issue of Change Detection arable land to grassland. Powered by TCPDF (www.tcpdf.org)
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Assessment of lignin content in needles of Norway Spruce (Picea abies L. Karst.) using laboratory and image spectroscopy
Suchá, Renáta ; Kupková, Lucie (advisor) ; Brodský, Lukáš (referee)
The master thesis deals with determination of selected biochemicals (lignin, carotenoids, water) content in Norway spruce needles using laboratory and imaging spectroscopy. The first part of thesis summarizes literature dealing with methods of estimating lignin and other biochemicals content. Three types of data are used in this thesis: 1. spectra measured by contact probe and ASD FieldSpec 4 Wide Res spectroradiometer, 2. spectra measured by integrating sphere and spectroradiometer and 3. aerial hyperspectral image data acquired by APEX sensor. The most useful transformation methods - first derivative and continuum removal are applied to the spectrum. Further the linear relationship between measured spectrum and content of biochemicals is analysed. Stepwise multiple linear regression is applied to select suitable wavelengths for modeling of biochemicals content in spruce needles. The model is also calculated and applied on the level of image hyperspectral data. Maps of lignin content in Norway spruce are the final output of these part of this. Next part of the thesis compares spectra measured by contact probe and spectra measured by integrating sphere. Diffrerence between the studied areas based on biochemicals content in spruce needles and several chemical elements in the soil and based on...
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Recognition and classification of patterned ground polygons from remote sensing data
Kříž, Jan ; Potůčková, Markéta (advisor) ; Brodský, Lukáš (referee)
Recognition and classification of patterned ground polygons from remote sensing data Abstract The main objective of this thesis has been to prove the possibility of using object based image analysis classification for identification of the ice-wedge polygons and to find general method for their classification. The thesis contains a comparison of the object based and pixel based classification of the subject. The three classification rulesets for OBIA were developed on three test sites on Mars captured by HiRISE sensor. As a result, the general classification approach is suggested. The manually collected datasets, which are common in geomorphological research, were used as the reference sample. The OBIA classification provided better results in all three cases, whereas the pixel classification was valid in only one case. Another objective has been the automatization of the process of gaining information about morphometric characteristics of the ice-wedge polygons and the subsequent classification of the polygons. Within the scope of the process were developed methods for creating polygonal network and specified parameters of those methods. Several toolboxes for the ArcGIS software were prepared and they are part of the results of the thesis. Keywords: patterned ground, ice-wedge polygons, remote sensing,...
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Determination of Chlorophyll Content in Birch and Pine Trees Using Hyperspectral Data
Zachová, Kateřina ; Potůčková, Markéta (advisor) ; Brodský, Lukáš (referee)
The master thesis deals with the determination of the chlorophyll content in birch foliage (Betula pendula Roth) and Scots pine using hyperspectral data. The first part of the thesis concentrates on the literature search dealing with the methods of chlorophyll content in the foliage of selected plant species. In the practical part the emphasis is on the study of spectral reflectance curves and finding their relation to the chlorophyll content from the laboratory determination. Images taken with the hyperspectral sensor HyMap and spectral reflectance curves obtained with the ground ASD FieldSpec 3 spectrometer were available. Using the derived regression model chlorophyll maps were created for Scots pine for three selected locations in the Sokolov coal basin area.
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Monitoring of chemical parameters of mining waters from hyperspectral image data
Hladíková, Lenka ; Kupková, Lucie (advisor) ; Brodský, Lukáš (referee)
Monitoring of Chemical Parameters of Mining Waters from Hyperspectral Image Data Abstract The thesis deals with utilization of hyperspectral image data for mining water quality monitoring. Sokolov lignite basin, facing many environmental problems caused by brown coal mining activities is the area of interest. Airborne hyperspectral image data acquired by the HyMap sensor in 2009 and 2010 and ground truth data - chemical and physical parameters of water samples are the main data sources for the thesis. Practical part aims at estimating of the amount of the dissolved iron and suspended sediments in selected water bodies. Two approaches were used to achieve this goal - the empirically derived relationship between the ground measurements and reflectance of the water bodies, and spectral unmixing method. Comparison of the two mentioned approaches and evaluation of validity to use the proposed methods for the data acquired by the same sensor one year later is also a part of this thesis.
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Flood monitoring using satellite radar data for different land cover categories
Rauch, Tomáš ; Kolář, Jan (advisor) ; Brodský, Lukáš (referee)
The aim of this thesis is to find method for flood monitoring from radar images. The thesis deals with flood in general and with organization of flood protection. There are described principles of radar sensors. There is also summary of satellites with their parameters. Next part of the thesis describes interaction between radar beam and different types of surface. Theoretical part is closed by overview of the existing methods for flood monitoring. In the practical part there is method for flood monitoring applied to areas affected by flood. The process is based on the classification of the radar image. Using classification and digital elevation model is drawn boundary of flooded area. The result boundaries are compared with the existing maximal flooded areas.
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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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