. . . "Use or modify algorithms written in Python, C++, Matlab, R or Spatial SQL as part of acquisition and exploration of geospatial data tasks."@en . . "Use or modify algorithms written in Python, C++, Matlab, R or Spatial SQL as part of acquisition and exploration of geospatial data tasks."@en . . . "Apply cartographic design principles in either exploration or presentation of geospatial data."@en . . "Apply cartographic design principles in either exploration or presentation of geospatial data."@en . . . "Make informed decisions on: the appropriate sensor or source, and methods for data acquisition, including field surveys, Web Services available through Spatial Data Infrastructures, crowdsourcing and Web-scraping."@en . . "Make informed decisions on: the appropriate sensor or source, and methods for data acquisition, including field surveys, Web Services available through Spatial Data Infrastructures, crowdsourcing and Web-scraping."@en . . . "Design basic database structures for the storage of geospatial data using model-driven architecture principles."@en . . "Design basic database structures for the storage of geospatial data using model-driven architecture principles."@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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "The Master’s Programme Geo-Information Science and Earth Observation (M-GEO) is a two-year academic curriculum at MSc level, taught fully in English, dedicated to understanding the earth’s systems from a geographic and spatial perspective. The field of Geo-information Science and Earth Observation has, in recent years, witnessed fast scientific and technological developments. As a result, geographic information has become a vital asset to society and part of our daily life. The ubiquitous production and availability of spatial data require cloud computing and new technology to turn the increasing volume of ‘big data’ to good use. The growing range of global challenges, from climate change and resource depletion to environmental pollution and pandemic diseases, that our society and in particular the more vulnerable populations on our planet are facing, increases the demand for academic professionals who have the ability, attitudes and skills to design solutions that are sustainable, transdisciplinary and innovative with positive societal impacts. Our education focuses on addressing these global problems by means of advanced geo-information and earth observation applications."@en . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . "Master’s Programme Geo-Information Science and Earth Observation (M-GEO)"@en . . . . . . . . . . . . . . "Geoinformatics"@en . "GFM"@en . . . "Course"@en . "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