Treffer: SPATIAL DATA ANALYSIS USING MACHINE LEARNING TREE-BASED ALGORITHMS BASED ON SELECTED CASE STUDIES.

Machine learning algorithms are gaining more and more popularity in various analytics fields. This is due to their precision, speed, and versatility. Using them to build models, we can analyze complex relationships, often challenging to capture in standard statistical analyses. By additionally using tools for analyzing large data sets, we can process complicated issues. The limit can only be the computational power and ingenuity of the researcher. This paper presents three case studies using tree-based machine learning algorithms and Python data science stack tools for spatial data analysis. They concern three different issues, the first is the detection of water surface in a satellite image, the second is crop prediction, and the third is real estate valuation. Various spatial data sets were used in the research, including raster satellite images, vector data, and databases with field measurement results. All presented case studies are developed based on the results of scientific works and projects in which the author participated. [ABSTRACT FROM AUTHOR]

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