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Aplikace Galileo High Accuray Service
Kazmierski, Kamil ; Hadas, Tomasz ; Kudłacik, Iwona ; Marut, Grzegorz ; Madraszek, Szymon
Since January 2023 the Galileo High Accuracy Service (HAS) is available to registered users. Within the HAS users can retrieve clock and orbit corrections, as well as code biases for Galileo and GPS constellations. Galileo HAS covers almost the entire globe and is the next system, after the Japanese CLAS (Japanese Centimeter Level Augmentation Service) and the Chinese PPP-B2b, that provides corrections via a satellite signal. These Galileo corrections are transmitted in the Galileo E6 signal but also via the Internet stream. The official HAS Service Definition Document indicates that the positioning accuracy is better than 25 cm and better than 30 cm for horizontal and vertical components, respectively. HAS corrections can be used in difference real-time applications without Internet connection. The presented work shows the use of Galileo HAS corrections in various geoscience applications such as positioning, timing, troposphere monitoring or coseismic vibrations detection. Additionally, the quality of the transmitted HAS correction is also verified using the SISRE parameter. The computations are carried out in the in-house developed GNSS-WARP software with the Internet HAS corrections saved in the ASCII files by the BKG Ntrip Client software. The Galileo HAS corrections quality using SISRE parameter equal to 8.6 cm and 13.0 cm for GPS and Galileo respectively. The experiment with Precise Point Positioning reveal sub-decimeter and centimeters accuracy in kinematic and static approach, respectively. In terms of timing precision Galileo HAS ensure precision of single nanosecond. Zenith Tropospheric Delay estimation with the use of evaluated corrections meet the requirement of troposphere monitoring and coseismic vibrations detection was also possible.
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Mathematical Methods of Image Segmentation for Remote Sensing Applications
Novotný, Jan ; Klimánek, Martin (referee) ; Štarha, Pavel (referee) ; Martišek, Dalibor (advisor)
Segmentation of an image into individual tree crowns is a key step in the processing of remotely sensed data for forestry practice. The doctoral thesis gives a broad overview of this topic. It comprehends theoretical context from mathematical point of view and defines basic terms from airborne imaging and laser scanning. Mathematical methods of tree detection are focused on a robust adaptation to the actual conditions in a region of interest. A novel approach of crown area delineation is introduced, it combines a seeded region growing technique with an active contour as a crown boundary representation. The parametrisation of all algorithms is analysed in a practical half of the thesis and more application-oriented issues are mentioned. Executable computer programs are attached.
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Forest Detection in Image
Kyjovský, Marek ; Španěl, Michal (referee) ; Šilhavá, Jana (advisor)
This bachelor's thesis deals with studying methods and procedures, which are used to detect forests in aerial and satellite images. This thesis sums up and describes methods of digital image processing. Furthermore, the thesis is focused on an implementation of a demo application which uses these methods. It deals with the design of this application and describes its implementation. Finally the thesis evaluates success of output from this application.
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Normalization of hyperspectral image data
Grísa, Tomáš ; Druckmüller, Miloslav (referee) ; Martišek, Dalibor (advisor)
The airborne hyperspectral remote sensing is used as an approach to monitor and analyse actual state of environmental components. This thesis deals with hyperspectral image data, especially it is focused on normalization with respect to scanning angle. The thesis proposes specific algorithm, which is based on the statistical analysis of spectral lines across the scan line and on a physical models describing the process of spectral reflectance. An important part of this thesis is software implementation of proposed algorithm, that allows to calculate required normalization for real datasets.
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Multispectral Analyse of Image Data
Novotný, Jan ; Druckmüller, Miloslav (referee) ; Martišek, Dalibor (advisor)
The airborne hyperspectral remote sensing is used as an approach to monitor actual state of environmental components. This thesis covers priority treatment to analyse of hyperspectral data with the aim of a tree crowns delineation. Specific algorithm applying adaptive equalization and the Voronoi diagrams is designed to subdivide a forest area into individual trees. A computer program executes the algorithm and allows testing it on real data, checking and analyzing the results.
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Water Object Detection in Image
Čeloud, David ; Španěl, Michal (referee) ; Šilhavá, Jana (advisor)
Bachelor's thesis describes history of remote sensing, image data structure, their processing and analyzing. It defines mulstispectral space and explains basics of quantitative analysis and differences between supervised and unsupervised classification. Implementation section describes designing and developing of program, which will be able to open and process image data and detect water objects in him.
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New Approaches in Airborne Thermal Image Processing for Landscape Assessment
Pivovarník, Marek ; Pokorný,, Jan (referee) ; Štarha, Pavel (referee) ; Zemek, František (advisor)
Letecká termální hyperspektrální data přinášejí řadu informací o teplotě a emisivitě zemského povrchu. Při odhadování těchto parametrů z dálkového snímání tepelného záření je třeba řešit nedourčený systém rovnic. Bylo navrhnuto několik přístupů jak tento problém vyřešit, přičemž nejrozšířenější je algoritmus označovaný jako Temperature and Emissivity Separation (TES). Tato práce má dva hlavní cíle: 1) zlepšení algoritmu TES a 2) jeho implementaci do procesingového řetězce pro zpracování obrazových dat získaných senzorem TASI. Zlepšení algoritmu TES je možné dosáhnout nahrazením používaného modulu normalizování emisivity (tzv. Normalized Emissivity Module) částí, která je založena na vyhlazení spektrálních charakteristik nasnímané radiance. Nový modul je pak označen jako Optimized Smoothing for Temperature Emissivity Separation (OSTES). Algoritmus OSTES je připojen k procesingovému řetězci pro zpracování obrazových dat ze senzoru TASI. Testování na simulovaných datech ukázalo, že použití algoritmu OSTES vede k přesnějším odhadům teploty a emisivity. OSTES byl dále testován na datech získaných ze senzorů ASTER a TASI. V těchto případech však není možné pozorovat výrazné zlepšení z důvodu nedokonalých atmosférických korekcí. Nicméně hodnoty emisivity získané algoritmem OSTES vykazují více homogenní vlastnosti než hodnoty ze standardního produktu senzoru ASTER.
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Standardization of Remote Sensing Usage for Forensic Ecotechnique: forest and trees
Introvičová, Sabina ; Čermák, Jan (referee) ; Ulrich, Radomír (referee) ; Alexandr, Pavel (advisor)
The thesis presents the main points of standardization of remote sensing (RS) usage for Forensic Ecotechnique: forest and trees (FEft). Based on the study FEft expertise database, the types of expertise, which remote sensing data have already been used and the types where the use of remote sensing increases the exactness of solutions were analyzed. RS data are essential in a problematic situation when an examined object does not exist or has been changed at the time of the assignment. This situation may be solved by obtaining information about the investigated object via retrospective image data, as described in the model example. There are chosen categories of image data relevant to the needs of experts in this thesis. These categories of RS data and their products are described with an indication of their possible use in the expertise processing, including freely available or paid resources and archives of image data.
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Využití smart farming technologií při hospodaření na zemědělské půdě
Kovaříková, Jana
The bachelor thesis deals with the basic theoretical description of smart farming technologies or precision farming methods in agricultural land management. Precision farming is a trend that has been developing since the early 1990s. One of the elements of precision farming is locally targeted farming that works with soil heterogeneity and tillage using new technologies. Optimizing soil inputs (mineral fertilizers, pesticides, etc.) and applying them according to the current plant requirements is one of the goals of smart farming. Through precision farming agronomic practices, we can increase the efficiency of crop production, reduce the amount of mineral fertilizer inputs and improve both economic and environmental status. The aim of the presented work was to evaluate the variable application of essential nutrients (P and K) on selected plots managed in a conventional way using PREFARM. The experiment itself was carried out in the agricultural company AGROSUMAK a.s., The practical part includes a comparison of lump and variable application of potassium salt (K2O source) and triple superphosphate (P2O5 source) on three experimental plots. Data on plot heterogeneity were provided by AGROSUMAK a.s., which uses the PREFARM system. In the conclusion of the present work, the results are discussed and compared from economic, environmental and agronomic points of view.
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