The aim of this PhD thesis was an objective assessment of application of VNIR spectroscopy for predicting properties of forest soils. For each soil property were found the most appropriate combination of statistical methods for pre-processing (continuum removal, 1. derivation, 2. derivation) and processing (PLSR, PCR, SVM) of certain spectral bands. As generally successful shows a combination of methods 1. derivation and support vector machine throughout the VNIR spectral range (400-2500 nm). In some cases, however, they proved to other models. Among the best predictable features include pH, content of oxidizable carbon, aluminum, iron, silicon, or calcium (at higher concentrations). Not very high success rate prediction was found in indicators that take low values (sodium, manganese, aluminum or ferrous complexes). The results show that VNIR spectroscopy method is applicable for predicting properties of forest soils. It can not completely replace traditional analysis, but it can very well complement, especially in practice. For example, when the soil mapping can help thicken network data and refine the information better than other methods of spatial estimation. It is applicable in cases where it is required large amounts of data in a short timeframe and at minimal cost. It is suitable for monitoring trends over time, or for a quick survey of an area.

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The subject of this research is a level of aberration of soil on selected sites in the land register of Vlkov u Osové Bítýšky village. During a Complex soil survey (1967/1968) were collected three samples In 1966 and 1967, in this territory. From these samples were selected data from texture analysis pH and humus. The old soil sampling sites were re-localized and from the very spots, new samples were taken from the depth of approximately 75 cm in order to gain current results. These new samples were analyzed in a laboratory and these results were compared with the 50 years old ones. This allowed us to evaluate changes in soil on the selected sites.

This work has aimed to implement an easy-to-use application which can be used to navigate through aerial imagery, assign sections of this image for different classes. Based on these category assignments the application can autonomously assign categories to so-far unknown fields, hence it helps the user in further classification. The output of the application is an index file, which can serve as underlying dataset for further analysis of a given area from geographic or economic point-of-view. To fulfil this task the program uses standard MPEG-7 descriptors to perform the feature extraction upon which the classification relies.

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The problems with microplastics, small plastic particles contaminating the environment, is a subject of heated discussions today. It has been recognized that the microplastics are not inert, but instead they have an impact on all enviromnental compartments. There are studies describing the negative effects of microplastics, for example on fauna and flora or on human health, but the effects on soil quality have not been sufficiently described. The aim of this thesis was to assess the short and medium term effects that microplastics could have on the soil. In this work, a series of experiments were performed to elucidate the fate of microplastics in the soil. Changes in soil organic matter thermal properties, soil respiration, amount of water and soil aggregation depending on the incubation time were monitored. Three types of agricultural land (chernozem, cambisol and phaeozem), which were contaminated with different concentrations od PET and tyre rubber, were tested. The results confirmed the specific effects of microplastics on soil properties, which were observed in non-incubated samples (i.e. at the time of incubation 0 months), microplastics did not behave inertly in the soil and affected, for example, soil properties, texture and respiration.