. . "201800281" . "GFM_002" . "7"^^ . "196"^^ . "10"^^ . "2023-02-02T23:00:00Z"^^ . "f2f" . "This course aims to bring both scientific background and practical skills with respect to the acquisition and exploration of geospatial data. Lectures bring the theoretical background and a series of tutorials prepare students for practical work and the course's individual assignment. Extensive practicals hold a big weight to this course and are intended to facilitate individual and peer learning. Students will be asked to share the findings of their practicals and solutions to problems. Finally, students will have to work on an assignment that will cover different steps of the process from data acquisition to its final visual exploration."@en . . . . . . "Basic knowledge and skills on Geo-Information Science and Modelling, Earth Observation and Data Integration: Principles, Approaches and User perspectives.\n\nStudents entering the course should have basic programming and GIS skills and be able to select, modify and apply solution strategies implemented in some programming language (e.g., Python, C++, Matlab, R and SpatialSQL)."@en . . . "7"^^ . "2" . "1B" . "2022-11-13T23:00:00Z"^^ . "The aim of this course is to equip students with theoretical and practical knowledge on methods for spatial data acquisition and exploration, while helping them to develop critical thinking for method selection. In this course, you will use algorithmic thinking and programming skills to find, retrieve, store, and explore various geospatial datasets. In scientific research, significant time and effort goes into acquiring, understanding, and cleaning the data before the actual analysis begins. Maps and diagrams are not only used to present the final results, but also to verify and explore the data during the whole data processing process phase. After this course, you will have a good overview of acquisition and exploration of geospatial data principles and methods and be able to select the most appropriate data acquisition and exploration methods as well as working environment (among R, Python, C++ etc)."@en . "Acquistion & Exploration of Geospatial Data"@en . . "Acquis. and Expl. of Geospatial Data/Acquistion & Exploration of Geo Data"@en . "Acquistion & Exploration of Geosptial Data"@en . . . "Learning outcome"@en . . "Analyse geospatial data resources and describe their usefulness in terms of spatial, temporal, and attribute quality using statistics and calculus concepts."@en . "Analyse geospatial data resources and describe their usefulness in terms of spatial, temporal, and attribute quality using statistics and calculus concepts."@en .