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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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Analýza energetické bilance intravilánu města pomocí metod dálkového průzkumu Země
ŠOUREK, David
The energy balance of each urban area depends on the specifics of active surface and other complex phenomena. In general, compared to the surrounding rural landscape, dry and impermeable surfaces predominate in urban areas. Different types of built-up areas have various properties determining how distributed solar radiation is. Overall, it is through energy fluxes defined by the sensible heat flux, the latent heat flux of evaporation, and the soil heat flux. Besides, vegetation plays a significant role in the proportions of fluxes. Plants can effectively transform the obtained solar radiation and thus influence the microclimatic situation through the cooling effect of evapotranspiration or other ecosystem services. Nevertheless, the efficiency depends on the state of vegetation and other prevailing conditions (weather, etc.). As the study area was selected the town of Písek. The research took place on two summer and two autumn days using remote sensing and statistical evaluation. The results showed the growing dependence of the latent heat flux of evaporation in localities with a higher vegetation density and a sufficient water supply. High values of surface temperature and sensible heat flux occurred in built-up areas with predominant materials with a large specific heat capacity, i.e. concrete, asphalt, sheet metal, stone etc. These indicators thus defined some problematic types of built-up areas, especially in terms of surface overheating or of the occurrence of local heat islands. Specifically, it was the historic centre, industrial zones and shopping centres. A better microclimatic situation prevailed in the park with a water surface, suburbs and built-up areas of family houses.
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Časové změny vlivu vegetačního krytu na místní klima intravilánu obce pomocí metod dálkového průzkumu Země
NÁROVEC, Václav
The diploma thesis deals with changes in vegetation indices and surface temperatures of previously undeveloped peripheral areas of České Budějovice and its immediate surroundings, which were built up after 1990. Areas that were undeveloped before 1990 and spread over either permanent grassland or arable land with agricultural crops. These areas are divided into four types - industrial areas, service areas, residential areas of multiapartment houses and residential areas of solitary family houses. The work uses Landsat satellite images for the years 1990, 1993, 1999, 2006, 2010, 2015 and 2020. The studied areas were examined in the period before construction, just after construction and with a distance after construction. In the period before the transformation (1990), there were high values of vegetation indices NDVI (Normalized Difference Vegetation Index), SAVI (Soil Adjusted Vegetation Index) a NDMI (Normalized Difference Moisture Index) and low values of surface temperatures in most of the studied areas. However, during the construction, the vegetation decreased and thus the values of vegetation indices decreased and the surface temperatures increased. Subsequent improvements were observed in areas with multi-apartment and family houses, where the vegetation of parks and residential gardens grew after a certain time. In the vicinity of the industrial area and service areas, where vegetation did not grow, the values of the monitored indices remained low.
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Land cover changes in Bohemian Switzerland using remote sensing data
Lihanová, Kristýna ; Štych, Přemysl (advisor) ; Součková, Jana (referee)
Land cover changes in Bohemian Switzerland using remote sensing data Abstract The purpose of this project was to classify land cover in The National Park Bohemian Schwitzerland from LAMDSAT data (1999, 2002, 2009), FORMOSAT data (2006) and QuickBird data (2009). Data used in this paper are described in details. The method used for images classification was method of unsupervised classification in Geomatica program. Created classes were merged into the final five classes. An Assessment of accuracy of classification showed that results don't reflect reality. Mixed forests are the biggest problem because they can be mistaken for coniferous or deciduous forests. Classification results were smoothed low pass filer and converted into a vector formats in ArcGIS program. For the years 2006 and 2009 was counted the vegetation indexes NDVI and LAI. Results showed that the densest vegetation is in deciduous forests. Changes in land cover were assessed in two ways. Shares of each class were calculated for all years. Overlays layers are created in ArcGIS. Overlap was conducted between 1999 and 2002 and between 1999 and 2009. Most changes were found between the coniferous and mixed forests. These changes are caused by the inaccuracies in classification. Key words: land cover, Bohemian Switzerland, forest, Landsat,...
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Tick-borne encephalitis risk assessment based on classification of vegetation from remote sensing data
Červená, Lucie ; Potůčková, Markéta (advisor) ; Pavelka, Karel (referee)
Tick-borne encephalitis risk assessment based on classification of vegetation from remote sensing data Abstract The main aim of this thesis has been to find out how to classify various categories of forest vegetation with a different risk of exposure to the tick-borne encephalitis based on the Landsat imagery. The legend used here is derived from the one used in the projects by Daniel, Kolář, Zeman (1995) and Daniel, Kolář, Beneš (1999) but has been reduced to only five classses with no overlaps in their definitions (I. coniferous stands, II. mixed stands, III. young deciduous stands and stand ecotones with a highly heterogeneous structure, IV. deciduous stands with a homogeneous structure, V. deciduous stands with a heterogeneous structure). The supervised classification with the Maximum Likelihood Classifier has been used on the Landsat imagery from various seasons. Difficulties concerned with the presence of clouds and varying Sun elevation across the imagery had to be adressed in the course of the work. The training sites and the control points have been defined by the field research and interpretation of the relevant orthophotomaps and Landsat imagery in 5-4-3 RGB composite. The mask of the forest has been created on the ZABAGED data basis. The time horizon of 2006 - 2010 has been the primary focus....
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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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Classification of land cover change in Ethiopia using Landsat and Sentinel-2 data
Zadražil, Filip ; Laštovička, Josef (advisor) ; Svoboda, Jan (referee)
This bachelor thesis is focused on the comparison of Random Forest (RF) and CART classifiers on the example of the Ethiopian region of Sidama. An analysis of land cover change between 2014 and 2020 was performed for this region. The cloud-based platform Google Earth Engine (GEE) was used for classifications. Supervised classifications were performed on images from Landsat 8 and Sentinel-2 missions, which were retrieved from the Earth Engine data catalogue. Data from in-situ measurement was used for training polygons, variability of input data over time was verified with Google Earth Pro. In the research part, the work deals with the methods and results of research that were conducted in a topic close to this work. In the empirical part, the work deals with the analysis of Landsat 8 and Sentinel-2 data. The temporal, spatial and spectral resolution were compared. In terms of temporal resolution, it has been shown that Sentinel-2 data allows up to three times more images for the same area thanks to the two satellites scanning in parallel. Spectral and spatial resolution of Sentinel-2 allows better observation of smaller and less distinguishable elements. The data was then used for land cover classifications using RF and CART classifiers in the cloud-based GEE environment. The RF classifier made it...
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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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