This study focuses on evaluating the potential and limitations of earth observation data in the context of likely climate change and beekeeping support. The study area for the first part of the analysis is the European continent, where the pattern of likely climate change is investigated and visualized using multidimensional raster data of temperature and precipitation obtained from Earth observations. Trend analysis was applied to both annual average temperature and yearly total precipitation from 1950 to 2021 in Europe. The spatial pattern of the changing trend of these two variables is visualized, which not only gives an overview of where and how the climate has changed in Europe but also offers bee experts and beekeepers valuable reference information in the decision-making process that can benefit beekeeping and bee conservation. A before-after comparison for the annual average temperature over the 72 years has also been visualized based on the results from the multidimensional principal components analysis. The relation between likely climate change and the survival of bees is explored at a regional scale (in this case, the national territory of the Czech Republic) as a case study due to the limitations in bee data availability. Regression analysis was carried out between bee colony winter losses and the slope value of trend lines for both temperature and precipitation, respectively. Although the current study design did not reveal statistically relevant correlations, the methodology applied in the analysis can still provide a new perspective for the research of likely climate change impacts on beekeeping. Moreover, similar patterns of fluctuation were observed from the evolution of bee colony winter loss and temperature anomalies over time, which indicates that high bee colony winter loss might be related to high temperature anomalies. In addition to the analysis mentioned above, a web application "EO4BEE" powered by Google Earth Engine was developed to facilitate the visualization of earth observation variables that are crucial to bee health.
Anotace v angličtině
This study focuses on evaluating the potential and limitations of earth observation data in the context of likely climate change and beekeeping support. The study area for the first part of the analysis is the European continent, where the pattern of likely climate change is investigated and visualized using multidimensional raster data of temperature and precipitation obtained from Earth observations. Trend analysis was applied to both annual average temperature and yearly total precipitation from 1950 to 2021 in Europe. The spatial pattern of the changing trend of these two variables is visualized, which not only gives an overview of where and how the climate has changed in Europe but also offers bee experts and beekeepers valuable reference information in the decision-making process that can benefit beekeeping and bee conservation. A before-after comparison for the annual average temperature over the 72 years has also been visualized based on the results from the multidimensional principal components analysis. The relation between likely climate change and the survival of bees is explored at a regional scale (in this case, the national territory of the Czech Republic) as a case study due to the limitations in bee data availability. Regression analysis was carried out between bee colony winter losses and the slope value of trend lines for both temperature and precipitation, respectively. Although the current study design did not reveal statistically relevant correlations, the methodology applied in the analysis can still provide a new perspective for the research of likely climate change impacts on beekeeping. Moreover, similar patterns of fluctuation were observed from the evolution of bee colony winter loss and temperature anomalies over time, which indicates that high bee colony winter loss might be related to high temperature anomalies. In addition to the analysis mentioned above, a web application "EO4BEE" powered by Google Earth Engine was developed to facilitate the visualization of earth observation variables that are crucial to bee health.
This study focuses on evaluating the potential and limitations of earth observation data in the context of likely climate change and beekeeping support. The study area for the first part of the analysis is the European continent, where the pattern of likely climate change is investigated and visualized using multidimensional raster data of temperature and precipitation obtained from Earth observations. Trend analysis was applied to both annual average temperature and yearly total precipitation from 1950 to 2021 in Europe. The spatial pattern of the changing trend of these two variables is visualized, which not only gives an overview of where and how the climate has changed in Europe but also offers bee experts and beekeepers valuable reference information in the decision-making process that can benefit beekeeping and bee conservation. A before-after comparison for the annual average temperature over the 72 years has also been visualized based on the results from the multidimensional principal components analysis. The relation between likely climate change and the survival of bees is explored at a regional scale (in this case, the national territory of the Czech Republic) as a case study due to the limitations in bee data availability. Regression analysis was carried out between bee colony winter losses and the slope value of trend lines for both temperature and precipitation, respectively. Although the current study design did not reveal statistically relevant correlations, the methodology applied in the analysis can still provide a new perspective for the research of likely climate change impacts on beekeeping. Moreover, similar patterns of fluctuation were observed from the evolution of bee colony winter loss and temperature anomalies over time, which indicates that high bee colony winter loss might be related to high temperature anomalies. In addition to the analysis mentioned above, a web application "EO4BEE" powered by Google Earth Engine was developed to facilitate the visualization of earth observation variables that are crucial to bee health.
Anotace v angličtině
This study focuses on evaluating the potential and limitations of earth observation data in the context of likely climate change and beekeeping support. The study area for the first part of the analysis is the European continent, where the pattern of likely climate change is investigated and visualized using multidimensional raster data of temperature and precipitation obtained from Earth observations. Trend analysis was applied to both annual average temperature and yearly total precipitation from 1950 to 2021 in Europe. The spatial pattern of the changing trend of these two variables is visualized, which not only gives an overview of where and how the climate has changed in Europe but also offers bee experts and beekeepers valuable reference information in the decision-making process that can benefit beekeeping and bee conservation. A before-after comparison for the annual average temperature over the 72 years has also been visualized based on the results from the multidimensional principal components analysis. The relation between likely climate change and the survival of bees is explored at a regional scale (in this case, the national territory of the Czech Republic) as a case study due to the limitations in bee data availability. Regression analysis was carried out between bee colony winter losses and the slope value of trend lines for both temperature and precipitation, respectively. Although the current study design did not reveal statistically relevant correlations, the methodology applied in the analysis can still provide a new perspective for the research of likely climate change impacts on beekeeping. Moreover, similar patterns of fluctuation were observed from the evolution of bee colony winter loss and temperature anomalies over time, which indicates that high bee colony winter loss might be related to high temperature anomalies. In addition to the analysis mentioned above, a web application "EO4BEE" powered by Google Earth Engine was developed to facilitate the visualization of earth observation variables that are crucial to bee health.
This study aims to process Earth observation data in the context of beekeeping and likely climate change within Europe and integrate the products and results into a data-powered web application. The student will explore the possibility of integrating several data sources from Earth Observation with crowdsourced information from beekeepers based on the citizen science approach. The second aim is to evaluate the benefits and limitations of available datasets for beekeeping support. The result will be a web application, maps, graphs, and animations. The student will attach all the collected datasets and all the animations to the thesis in digital form. The student will create a website about the thesis following the rules available on the department’s website and a poster about the diploma thesis in A2 format. The student will submit the entire text (text, attachments, poster, outputs, input and output data) in digital form on a storage medium and the text of the thesis in two bound copies to the department secretary.
Zásady pro vypracování
This study aims to process Earth observation data in the context of beekeeping and likely climate change within Europe and integrate the products and results into a data-powered web application. The student will explore the possibility of integrating several data sources from Earth Observation with crowdsourced information from beekeepers based on the citizen science approach. The second aim is to evaluate the benefits and limitations of available datasets for beekeeping support. The result will be a web application, maps, graphs, and animations. The student will attach all the collected datasets and all the animations to the thesis in digital form. The student will create a website about the thesis following the rules available on the department’s website and a poster about the diploma thesis in A2 format. The student will submit the entire text (text, attachments, poster, outputs, input and output data) in digital form on a storage medium and the text of the thesis in two bound copies to the department secretary.
Seznam doporučené literatury
Rapp, J. R., Lenske, V., Solomon, E., & Young, R. (2018, December). Incorporating NASA Earth Observations into an Assessment Tool to Identify Correlations Between Factors Associated with Bee Health. In AGU Fall Meeting Abstracts (Vol. 2018, pp. GC43I-1643).
Vizcarra, N. Clues in the nectar. (2010). Sensing Our Planet, 34.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote sensing of Environment, 202, 18-27.
Kumar, L., & Mutanga, O. (2018). Google Earth Engine applications since inception: Usage, trends, and potential. Remote Sensing, 10(10), 1509.
Amani, M., Ghorbanian, A., Ahmadi, S. A., Kakooei, M., Moghimi, A., Mirmazloumi, S. M., ... & Brisco, B. (2020). Google earth engine cloud computing platform for remote sensing big data applications: A comprehensive review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5326-5350.
Huntington, J. L., Hegewisch, K. C., Daudert, B., Morton, C. G., Abatzoglou, J. T., McEvoy, D. J., & Erickson, T. (2017). Climate engine: Cloud computing and visualization of climate and remote sensing data for advanced natural resource monitoring and process understanding. Bulletin of the American Meteorological Society, 98(11), 2397-2410.
Seznam doporučené literatury
Rapp, J. R., Lenske, V., Solomon, E., & Young, R. (2018, December). Incorporating NASA Earth Observations into an Assessment Tool to Identify Correlations Between Factors Associated with Bee Health. In AGU Fall Meeting Abstracts (Vol. 2018, pp. GC43I-1643).
Vizcarra, N. Clues in the nectar. (2010). Sensing Our Planet, 34.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote sensing of Environment, 202, 18-27.
Kumar, L., & Mutanga, O. (2018). Google Earth Engine applications since inception: Usage, trends, and potential. Remote Sensing, 10(10), 1509.
Amani, M., Ghorbanian, A., Ahmadi, S. A., Kakooei, M., Moghimi, A., Mirmazloumi, S. M., ... & Brisco, B. (2020). Google earth engine cloud computing platform for remote sensing big data applications: A comprehensive review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5326-5350.
Huntington, J. L., Hegewisch, K. C., Daudert, B., Morton, C. G., Abatzoglou, J. T., McEvoy, D. J., & Erickson, T. (2017). Climate engine: Cloud computing and visualization of climate and remote sensing data for advanced natural resource monitoring and process understanding. Bulletin of the American Meteorological Society, 98(11), 2397-2410.
Přílohy volně vložené
Bound attachments:
Attachment 1 Earth observation data source table
Attachment 2 Parameter table for implementation of time series visualization
Attachment 3 EO4BEE Web Application Interface
Free attachments
Attachment 2 Poster
Attachment 3 SD card
Attachment 3 Thesis website
Přílohy vázané v práci
ilustrace, tabulky
Převzato z knihovny
Ne
Plný text práce
Přílohy
Posudek(y) oponenta
Hodnocení vedoucího
Záznam průběhu obhajoby
Student presented their thesis during a 10-minute long presentation. During this time student presented the workflow of the thesis, practical results and potential limitations. After the presentation, reviews from the supervisor, co-supervisor and opponent were read. The discussion follows, and these topics were discussed:Time change impacts on beekeeping needs to be verified
How hard is it to predict impacts according to the data
User-testing possibilities
Will the research continue?
limitations of Google Engine were discussed and well described
determinating corrects methods of observation methods
limitations of different data scale were commented