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Využití bezpilotního průzkumu pro cílenou aplikaci herbicidních látek
Panteleev, Evgeny
The thesis "the use of unmanned Exploration for targeted application of herbicides" is focused on the analysis of land data using unmanned Exploration for the following application of herbicides. The theoretical part of the thesis contains a description of common methods for assessing the state of stands in the form of remote sensing. And then it deals with sub-methods, herbicides and drones. The practical part deals with a semi-operational field experiment in the locality of Letkovice. The content includes the results of field and remote sensing, analyzed data from GIS and results of field experiments focused on variable applications of herbicides. And gave an economic comparison of uniform and variable methods of management.
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Prostorová analýza heterogenity pozemků z družicových dat
Kouřil, Jiří
Field heterogeneity is one of the prerequisites for many methods of precision agriculture, like for example variable sowing or variable application of fertilizers. One method of determining heterogeneity is an analysis of multispectral satellite images. The main aim of this thesis is to verify the hypothesis that there is at least a medium positive correlation between values of vegetation indices calculated from multispectral images and yields measured on four fields of a total area of approximately 75 ha during seasons 2019–2021. All fields are managed by the company Spearhead Czech s.r.o. which also provided data for preparing yield maps. These were statistically compared with three vegetation indices NDVI, EVI, and NDRE, which were calculated from Sentinel-2 satellite images. Results of correlation analysis show a medium correlation between vegetation indices and yields on two of four fields, whereas only weak positive and in some cases weak negative correlation can be observed on the other two. This was probably caused by droughts that influenced vegetation in these fields in 2019 and 2021. The thesis shows the potential of satellite images to determine field heterogeneity despite the comparison of vegetation indices and yields of different crops.
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Možnosti využití technologií precizního zemědělství pro aplikaci hnojiv
Sedláčková, Marie
The aim of the bachelor's thesis was to describe modern methods of precision agriculture using remote sensing implemented in the technology of variable applications of nitrogen fertilizers in the operating conditions of the agricultural company and subsequently analyze their economic efficiency. The research took place in the company RenoFarma Troubky, a.s. at two selected sites of interest, DPB 0102 ("Býčí kout") and DPB 9103 ("Klínka"). For production fertilization were used seven composite images from 2014 – 2020 taken by the Landsat 7 satellite. For qualitative fertilization was used an image from the UAV Trinity F90 drone with a multispectral camera, from which were subsequently generated application maps using QGIS software. Fertilization attributes were based on NDVI categorization. The model of technological processing of variable nitrogen application using remote sensing was described and schematized. UREAstabil® fertilizer was used for production and quality fertilization. Zones of fertilizer doses (kg.ha-1) were divided and correlations with average yields (t.ha-1) were monitored. Most of the zones appeared to be economically inefficient during the monitored period. The low profitability was influenced by low yields, caused by an insufficient amount of fertilizer, the late application of the quality dose and the daily rainfall (mm) monitored at the meteorogical station Amet.
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Supraglacial lakes detection and volume estimation from remote sensing data
Rusnák, Samo ; Brodský, Lukáš (advisor) ; Šobr, Miroslav (referee)
Supraglacial lakes detection and volume estimation from remote sensing data Abstract Supraglacial lakes play an important role in understanding glacier dynamics, including their response to climate change. This thesis explores the problematics of estimating lake depth and volume using a physical model. This brings challenges in considering the influence of various factors, such as cryoconite on glacier surface and suspended particular matter, which influences physical model, which is in research mostly neglected. Regression analysis of the g parameter of a physical model, representing light attenuation coefficient, and supervised classification of supraglacial lakes is applied in this thesis. The results reveal the variability of parameter Ad, representing lake bottom albedo reflectance, and its impact on predicted supraglacial lakes depth and volume. The results highlight the problem of global parameterisation of the physical model of supraglacial lakes and the need for further research to improve its accuracy and explore future possibilities in this field. Keywords: supraglacial lake, remote sensing, machine learning, physical model, depth estimation, regression analysis
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Status of implementation of the National Inventory of Contaminated Sites project
Suchánek, Zdeněk ; Řeřicha, Jaroslav ; Krhovský, Jan
By mid-April 2021, the inventory of contaminated sites in 52 districts out of the 77 districts of the Czech Republic was completed. 6403 records are already stored in the SEKM, ie 70.7 % of the planned parameter (target number of at least 9053 records). The inventory already covers 68.5 % of the inventory area. The inventory in the regions has already been completed with reports for the Jihočeský, Liberecký, Karlovarský, Královéhradecký and Pardubický regions. Monitoring and control of the “yield” of individual sources (SEKM, indications obtained by remote sensing, new sites) resulted in ongoing methodological guidance of inventory teams (control days, training, consultations, manuals and methodological recommendations). The project management gradually adopted 18 adjustments to the work schedule, ie. without affecting the project completion date. Linear extrapolation of the number of existing approved SEKM records on the entire territory of the Czech Republic makes it possible to assume that the prescribed parameter - 9053 records of contaminated sites with evaluated priority - will be achieved on time. The project will be completed by 31 December 2021.
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Hodnocení míry znečištění vodních nádrží sinicemi metodami dálkového průzkumu Země
NOVÁK, Matěj
The thesis deals with evaluating the pollution of selected water reservoirs by cyanobacteria and algae using their spectral characteristics. The thesis compares data measured by a spectroradiometer ASD Fieldspec 4 with laboratory-evaluated data collected in situ. Spectral algorithms 709/620 and 709/665 were chosen to evaluate the degree of pollution by cyanobacteria and algae. The values of the spectral algorithms 709/620 and 709/665 showed a close linear relationship with the laboratory-evaluated concentrations of phycocyanin and chlorophyll-a (709/620 with PC and 709/665 with Chl-a) and the regression models achieved considerable accuracy (R2PC = 0.7339; R2Chl-a = 0.7899). In the case of the relationship of the spectral algorithm 709/665 with TP, PP and PN, a close linear dependence was also achieved. And the regression models again achieved considerable accuracy (R2TP = 0.7273, R2PP = 0.7466, R2PN = 0.7491). This indicates that the use of the ASD Fieldspec spectrometer, and thus other DPZ methods using spectral reflectance for evaluation, offers in practice a suitable alternative to evaluating surface water status through laboratory evaluation of samples.
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Predictability of yields of the main crops in Macedonia (FYROM)
Trajchevski, Hristijan
The objective of this thesis is to investigate yield predictability of the selected crops at national, regional and municipality level in Republic of North Macedonia. Emphasis is placed on wheat, maize, tobacco and grape, due to their significance for the economy of the country, both as exporting goods and for internal use. Specifically, the aim of the thesis is to investigate if there are possibilities for predicting the yield of the selected crops early in the season. The methods used in this thesis are yield estimation model based on linear regression using one variable and yield predicting model based on Artificial Neural Network (ANN) using meteorological data and remotely sensed data, individually. From the obtained results it is possible to conclude that the model based on linear regression indicates more accurate estimations for the yield of wheat and maize, than for the grape or tobacco. However, this model is not suitable for yield forecasting, whereas ANN is more suitable, because it manages to work with non-linear and very complex relationships. From the results of the yield predicting model it is possible to conclude that the model based on ANN using meteorological data showed more accurate results compared with the model based on ANN using remotely sensed data. Both of these model types generated highly accurate predictions, proving that ANN is powerful tool for yield prediction and forecast, even several months before the harvest.
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Carbon dynamics in the chernozem region after half a century of intensive cultivation
Juřicová, Anna ; Chuman, Tomáš (advisor) ; Dostál, Tomáš (referee) ; Maerker, Michael (referee)
Soils are vital for global food security and recently they have also received attention as a tool potentially mitigating climate change due to their ability to store large amounts of carbon (C) and provide other vital non-productive functions. However, several forms of degradation threat these functions. In agricultural soils, the decline of soil organic carbon (SOC) and soil erosion are two of the degradation processes. Soil erosion laterally redistributes large amounts of SOC in hilly agricultural landscapes. Lateral fluxes further impact the SOC storage in soils and indirectly modulate the vertical C fluxes between the terrestrial sphere and the atmosphere. The aim of this thesis is to investigate the long-term (> 50 years) regional SOC changes and analyze the impacts of soil redistribution in C dynamics in a hilly agricultural landscape. We consider soil redistribution via water and tillage as the main erosion agents. The study uses a comparison of recently resampled and legacy data from historical monitoring (the 1960s) together with coupled erosion and C dynamics modelling using the SPEROC-C model. The study is conducted in the chernozem region, south Moravia, the Czech Republic. Our results showed that the change in SOC content tends to be positive after more than 50 years. Moreover,...
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Vliv vegetace na letní teplotní extrémy ve městech hodnocené z pozemních a leteckých dat
ROHÁČ, Václav
This thesis examines the effect of surface types and vegetation types on ambient temperature during summer temperature extremes. The theoretical part targets the topics of remote sensing, electromagnetic radiation, urban and global climate. Within the practical part, 3 areas of interest were selected from aerial hyperspectral data from the territory of the statutory city of České Budějovice, each representing a different part of the city in terms of land use. By means of data analysis, graphs showing the influence of the relative representation of the variant surfaces on the temperature were created using the linear regression method. From the maps of tree species occurring in the parks of the first two areas, the most abundant species were selected and the average temperature within 2 meters of them was examined. The thesis also includes an evaluation of a questionnaire answered by city residents on the topic of preferences and knowledge about the urban green space.
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