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Evalution of Time Series of Satellite Images to Observe Disturbancec in the Low Tatras
Laštovička, Josef ; Štych, Přemysl (advisor) ; Hais, Martin (referee)
The work is aimed at finding appropriate methods for observing changes in the status of forest vegetation and its evaluation in the years 1992-2015. The satellite images of the Low Tatras are analyzed by using Time Series technology. Specifically, the images Landsat 4, 5, 7 and 8, for which it is necessary to perform a calibration and an adjustment of input data values to realize the individual vegetation indices, due to the fact that the images are captured by different sensors with different radiometric resolution. From this perspective, the work deals with the possibilities of normalized relative radiometric corrections and search for a particular type of appropriate compensation for Landsat CDR images. Calibrated data sets are evaluated by Time Series of different vegetation indices. The resulting values are evaluated in relation with the occurrence of forest disturbances, eg. wind storms, biological and other pests. The final part is discussion of the results, evaluating the test methods of calibration and suitability of vegetation indices for observing the state of calamity. The App is created for generating the Time Series of Landsat images CDR and for preparing RRN datasets. Key words: Time Series, radiometric correction, atmospheric correction, Landsat CDR, vegetation indices,...
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Procedure of a smile effect radiometric correction for hyperspectral scanner
Skalický, Filip ; Kolář, Jan (advisor) ; Kopačková, Veronika (referee)
The diploma theses focused on the topic of removing spectral aberration of sensor. The anomaly is being called spectral smile effect, or spectral curvature. Usually are with this artifact affected hyperspectral sensors, whose sensing is based on principle corresponding to pushbroom scanner. The defect occurs in the data as brightness gradient in the cross-track direction to the sensor flight and affects the object's spectral characteristics shape. Removing is important particularly in case of applying atmospheric correction algorithm, which are being degraded with presence of this defect. The work contents description of current methods used for detecting and eliminating this anomaly. The work is closer focused on the methods removing the defect based on own measured data without use of calibration targets. There is being examined sensitivity of the methods on the scene perception character, meaning heterogeneity of the scene and other outside influence. One of the methods is deeply processed resulting in increasing quality of the method for removing the defect.
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