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Heterogeneity in forest vegetation monitoring with remote sensing
Kolešová, Petra ; Kolář, Jan (advisor) ; Potůčková, Markéta (referee)
Heterogeneity in forest vegetation monitoring with remote sensing Abtract The main aim of this diploma thesis is to examine the suitability of various classification approaches for forest vegetation categorization using Landsat 8 satellite imagery. Two satellite images acquired during vegetative period (8th March, 27th July 2013) were chosen. The overall goal of the study is to explore the potential of using statistical methods to obtain information about forest heterogeneity in a given territory. Chosen study sites are defined by administrative boundaries of selected municipalities from South and Central Bohemia located within following municipalities with extended powers - Blatná, Milevsko, Písek, Příbram and Sedlčany. Supervised and unsupervised classifications were used based on obtained training areas and orthophoto. The definition of chosen classes (coniferous forests, mixed forests, ecotones, structurally homogeneous deciduous forests and structurally heterogeneous deciduous forests) was identical with the categories used in "Project MT 11425-5/2010 The Mapping of Natural Zoonoses Focal Points, Transferable on Humans in the Czech Republic and Their Changes Affected by the Modification of Climate". Due to large amount of training datasets obtained from field survey, ortophoto and spectral analysis,...
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Utilization of additional information on the pulse for ALS data classification in rugged terrain
Poláková, Tereza ; Lysák, Jakub (advisor) ; Potůčková, Markéta (referee)
Utilization of additional information of the pulse for ALS data classification in ragged terrain Abstract The diploma thesis deals with airborne laser scanning filtering problem in sandstone landscape which is characterized by ragged terrain and in our country also by dense vegetation that makes difficult to transit laser pulse to terrain that can lead to lower accuracy of created DTM. In the first part the basic filtering algorithm that are systematic divided into several groups are described. The emphasis is also put on theoretic problems which we have to deal with during the filtering of laser scanner data acquired in sandstone landscape. The main goal of the thesis is to suggest changes in one of the existing algorithm to additional information of the pulse (mainly amplitude and width of the pulse) be used, and to test this method over the real data. At the end the results of the method and its implementation are critically evaluated. Keywords: airborne laser scanning, point cloud segmentation, point cloud classification, sandstone landscape, DTM
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Topographic mapping of rock formations with the use of airborne laser scanning data
Lysák, Jakub ; Potůčková, Markéta (advisor) ; Brázdil, Karel (referee) ; Šíma, Jiří (referee)
Abstract This thesis focuses on topographic mapping of rock formations with the use of new technologies in a comprehensive manner, from airborne laser scanning (ALS) data acquisition and processing in rocky terrains, followed by their processing to the content of topographic databases and their cartographic processing in maps. The introduction discusses issues of importance for practice, and the relation between topographic mapping of rocks and other fields of human activity. The ALS section describes products for topographic mapping of rocks derived from ALS data, and discusses the specifics of ALS data acquisition and processing in wooded rugged terrain. Existing solutions of this problem are explained and their limitations are identified. Author's own approaches to solving this task are presented as case studies, including three made a further three designed experiments with ALS data processing and evaluation of their results. Recommendation regarding mapping of sandstone landscapes in Czechia have been also addressed. The topographic section describes the current representation of rocks and related objects in the ZABAGED database (Czech national digital topographic database), explains the historical context, analyzes this data and identifies their shortcomings in relation to the ALS. Research...
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Using Sentinel-1 data for creating a digital terrain model by means of radar interferometry
Karvánek, Matouš ; Potůčková, Markéta (advisor) ; Hlaváčová, Ivana (referee)
Using of Sentinel-1 data for radar interferometry Abstract The diploma thesis deals with extraction of a digital surface model (DSM) using synthetic aperture radar interferometry (InSAR) and Sentinel-1 data in selected locations of the Czech Republic. The InSAR technique, the Sentinel-1 data, their parameters and possibilities of their usage are described in the theoretical part of the thesis. The specification of the model areas and used data follows. The practical part is focused on creating a methodology of deriving a digital surface model and its extracting in the three tested locations. These locations differ from each other in their geomorphological features and land cover. At the end of this part the comparison of the extracted model with the reference model DMP 1G using statistical methods is carried out. At the end of this thesis the results are evaluated and discussed. Key words: InSAR, Sentinel-1, SAR, DSM
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Classification of meadow vegetation in the Krkonoše Mts. using aerial hyperspectral data and support vector machines classifier
Hromádková, Lucie ; Kupková, Lucie (advisor) ; Potůčková, Markéta (referee)
Meadow vegetation in the Krkonoše Mountains National Park is classified in this master thesis using aerial hyperspectral data from sensor AISA and Support Vector Machines (SVM) and Neural Networks (NN) classification algorithms. The main goals of the master thesis are to determine the best settings of SVM parameters and to propose an ideal design for a training dataset for this classification algorithm and mapping of the meadows in the Krkonoše mountains. The criterion of the tests will be the result of classification accuracy (confusion matrices and kappa coefficient). The additional goal of the master thesis is to compare performances of both utilized classifiers, especially regarding the amount of training pixels necessary for successful classification of the mountainous meadow vegetation. Classification maps of the area of interest and Python scripts are the main outputs of the master thesis. These outputs will be handed over to the Administration of the Krkonoše Mountains National Park for further utilization in the monitoring and protecting these valuable meadow vegetation communities. Key words: hyperspectral data, AISA, Support Vector Machines, Neural Networks, training dataset, mountainous meadow vegetation
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THE USE OF IMAGE MATCHING METHODS IN GEOMORPHOLOGICAL ANALYSIS
Šiková, Zuzana ; Potůčková, Markéta (advisor) ; Hodač, Jindřich (referee)
The use of optical scanning methods in geomorpho-analysis Abstract Main goal of this thesis is to find out if it is possible to use Structure from motion (SfM) method for analyzing geomorphological objects. Four geomorphological features in three different places within Pilsen-North region was used for testing this method. These objects with very dissimilar dimensions and shapes was scanned for this testing in various light conditions. All used data-sets was entirely created by author of this thesis. The data was initially processed by Agisoft Photoscan Professional Ediditon v1.1.6 and VisualSFM v0.5.26 to create spatial models. These models was afterwards processed in CloudCompare v2.6.1 and MeshLab v1.3.3. This software was used for clipping and merging of 3D models and for converting 3D models in to real dimensions. These real sized spatial models was then contrasted together by creating comparing entities. Outcomes are evaluated in the thesis conclusion. Keywords: Structure from motion (SfM), SIFT, RANSAC
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Detection of Equilibrium Line Altitude (ELA) Changes from Remote Sensing Data; Case Study from the Cordillera Blanca, Peru
Paraj, Zsolt ; Potůčková, Markéta (advisor) ; Kropáček, Jan (referee)
The aim of this diploma thesis is to monitor glacier change in the Cordillera Blanca in the period from 1987 to 2014. This diploma thesis focuses on three mountains and eleven glaciers in the northern part of the Cordillera Blanca. The input data consist of 29 Landsat scenes (Landsat 4,5,7 and 8) and the ASTER global digital elevation model version 2. Semi-automatic classification algorithm is created based on threshold values detected by spectral analyses of selected land cover types in the Cordillera Blanca. Additionally, the mean snowline (equilibrium line) altitude change is computed for all of the three mountains and eleven glaciers. Besides, glacier change depending on slope and aspect is evaluated. The results of this diploma thesis are presented in maps, tables and charts. The results of the classification are compared with the GLIMS Glacier Database and the field measurements provided by Adam Emmer, MSc. Finally, the advantages and disadvantages of the new Landsat 8 satellite sensor are discussed. Key words: Remote sensing, Landsat, classification, ice and snow detection, ELA, Cordillera Blanca
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Detection options of drenage and ameliorate channels using remote sensing data
Čermák, Jan ; Potůčková, Markéta (advisor) ; Štych, Přemysl (referee)
The purpose of this work is to explore detection options of subsurface drainage systems using remote sensing data. Drainage drains soggy soil and increases its fertility, but also allows transport of nutrients such as nitrogen and phosporus into waterways. Location of drainage systems is often unknown because of missing or inacurrate project documentation. Theoretical part is mostly devoted to the description of remote and ground methods of drainage detection. Then objectives of the work are solved. Drainage indications are described in specialized aerial photographs of visible and infrared part of the spectrum. These indications are compared with historical project plans. Methods aimed to improve indication of drainage including Laplacian filter and NDVI are applied and evaluated. Main output is binary raster expressing location of drains. Accuracy of results is evaluated in relation to vectorized indication of drainage from the source images.
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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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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
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