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Evaluation of forest vegetation based on time series of remote sensing data
Laštovička, Josef ; Štych, Přemysl (advisor) ; Brom, Jakub (referee) ; Bucha, Tomáš (referee)
Příloha k disertační práci: Abstrakt v AJ (Mgr. Josef Laštovička) Abstract This dissertation thesis deals with the study of forest ecosystems in the central Europe with the time series of multispectral optical satellite data. These forest ecosystems have been influenced by biotic and abiotic disturbances for the last decade. The time series of the satellite data with high spatial resolution allow the detection and analysis of forest disturbances. This thesis is mainly focused primally on free available Landsat and Sentinel-2 data, these two data types were compared. From methods, the difference time series analyses / algorithms were used. The whole thesis can be divided into two main parts. The first one analyses usability of classifiers for detection of forest ecosystems with per-pixel and sub-pixel methods. Specifically, the Neural Network, the Support Vector Machine and the Maximum Likelihood per-pixel classifiers were used and compared for different types of data (for data with high spatial resolution - Landsat or Sentinel-2; very high spatial resolution - WorldView-2) and for classification of protected forest areas. The Support Vector Machine were selected as the most suitable method for forest classifications (with most accurate outputs) from the list of selected per-pixel classifiers. Also, Spectral...
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Use of separate spectra records and interpretation possibilities of multispectral data in the context of protohistory of the middle Thaya region
Komoróczy, Balázs ; Vlach, Marek ; Zelíková, Michaela ; Sedláček, J.
The significant expansion of analytical and interpretive possibilities within remote sensing methods in archaeology over the last three decades brings especially the increasing availability of qualitatively adequate satellite multispectral data together with the development of multispectral sensors used on unmanned aerial vehicles. The results of multispectral imaging mediate an important analytical dimension for the identification and interpretation of signs of archaeological contexts in agricultural monocultures. As part of the prospecting activities of the Research Centre for Roman and Great Migration Period of the Institute of Archaeology of the Academy of Sciences of the Czech Republic, Brno, current goals also include exploiting the potential of this specific segment of remote sensing (in cooperation with the Institute of Landscape Planning at Mendel University in Brno) and with use of the wide array of prospection methods to broaden the information base of archaeological components, especially the protohistoric segment of the development of the middle and lower Thaya region.
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Evaluation of forest vegetation based on time series of remote sensing data
Laštovička, Josef
Příloha k disertační práci: Abstrakt v AJ (Mgr. Josef Laštovička) Abstract This dissertation thesis deals with the study of forest ecosystems in the central Europe with the time series of multispectral optical satellite data. These forest ecosystems have been influenced by biotic and abiotic disturbances for the last decade. The time series of the satellite data with high spatial resolution allow the detection and analysis of forest disturbances. This thesis is mainly focused primally on free available Landsat and Sentinel-2 data, these two data types were compared. From methods, the difference time series analyses / algorithms were used. The whole thesis can be divided into two main parts. The first one analyses usability of classifiers for detection of forest ecosystems with per-pixel and sub-pixel methods. Specifically, the Neural Network, the Support Vector Machine and the Maximum Likelihood per-pixel classifiers were used and compared for different types of data (for data with high spatial resolution - Landsat or Sentinel-2; very high spatial resolution - WorldView-2) and for classification of protected forest areas. The Support Vector Machine were selected as the most suitable method for forest classifications (with most accurate outputs) from the list of selected per-pixel classifiers. Also, Spectral...
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Evaluation of forest vegetation based on time series of remote sensing data
Laštovička, Josef ; Štych, Přemysl (advisor) ; Brom, Jakub (referee) ; Bucha, Tomáš (referee)
Příloha k disertační práci: Abstrakt v AJ (Mgr. Josef Laštovička) Abstract This dissertation thesis deals with the study of forest ecosystems in the central Europe with the time series of multispectral optical satellite data. These forest ecosystems have been influenced by biotic and abiotic disturbances for the last decade. The time series of the satellite data with high spatial resolution allow the detection and analysis of forest disturbances. This thesis is mainly focused primally on free available Landsat and Sentinel-2 data, these two data types were compared. From methods, the difference time series analyses / algorithms were used. The whole thesis can be divided into two main parts. The first one analyses usability of classifiers for detection of forest ecosystems with per-pixel and sub-pixel methods. Specifically, the Neural Network, the Support Vector Machine and the Maximum Likelihood per-pixel classifiers were used and compared for different types of data (for data with high spatial resolution - Landsat or Sentinel-2; very high spatial resolution - WorldView-2) and for classification of protected forest areas. The Support Vector Machine were selected as the most suitable method for forest classifications (with most accurate outputs) from the list of selected per-pixel classifiers. Also, Spectral...
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Using satellite data of the Landsat program for environmental research with a case study focused on assessment of vegetation indexes in the area of Sokolovsko
Mosoriaková, Gabriela ; Matějíček, Luboš (advisor) ; Rojík, Petr (referee)
This thesis focuses on the use of remote sensing imagery and satellite image Landsat in the research of land during the revitalization, re-cultivation, and re-naturalization process. The area of the case study is the Sokolov dump. The dump is a typical long-term surface mining area and is a perfect model for the revitalization process. The thesis compares satellite imagery from the LandSat company during a period of time. The pictures are selected so that the land is not obscured by weather patterns and cloud cover. These pictures allow the evaluation of the Vegetation Index (NDVI, EVI, SAVI and MSAVI). Two areas are compared with different types of revitalization. The first is the natural process and the second is a controlled environment. The expected results should show that that the terrain data from the remote sensing images correspond to the actual land survey. The images are processed using ArcGIS and then evaluated in MatLab.
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Urban vegetation - temporal analysis of urban vegetation impact on local climate using remote sensing
PAVLÍČKOVÁ, Lenka
The urban heat island (UHI) is a phenomenon of noticeably higher temperatures in the cities as compared to their respective surrounding areas. This thesis aims at characterizing the influence of city expansion to the urban heat island phenomenon. The study is carried out in a city of Caceres in the Spanish province of the same name. A model input data is obtained with Landsat multispectral images. The analysis of satellite images shows that functional vegetation cover and water surfaces help in mitigating urban heat island effect. However, the Caceres city expansion does not influence the urban heat island intensity. A possible explanation for it is as the city expanded the ratio of vegetation to dry land remains constant in time.
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