Scientific geocomputing  

You specifically learn about solution strategies, high-level solution descriptions and translations of these into an implementation in some programming language. The course’s programming language will be Python, but throughout the Geoinformatics specialization, you will learn to implement your algorithms using also other programming/scripting languages/environments. Dissemination of code output is important and so we will make an excursion into the visualization of scientific outputs such as charts and maps, and web programming also. We will discuss the scientific side of programming by an introduction into literate programming, which emphasizes documentation of code and the FAIR principles of scientific data management, which apply to data and code. We emphasize the role of data in geospatial algorithms, as these are often data-intensive. By reviewing and developing (high-level) code, you will increase your understanding of basic concepts in Geo-information Science and Earth Observation.; "You specifically learn about solution strategies, high-level solution descriptions and translations of these into an implementation in some programming language. The course’s programming language will be Python, but throughout the Geoinformatics specialization, you will learn to implement your algorithms using also other programming/scripting languages/environments. Dissemination of code output is important and so we will make an excursion into the visualization of scientific outputs such as charts and maps, and web programming also. We will discuss the scientific side of programming by an introduction into literate programming, which emphasizes documentation of code and the FAIR principles of scientific data management, which apply to data and code. We emphasize the role of data in geospatial algorithms, as these are often data-intensive. By reviewing and developing (high-level) code, you will increase your understanding of basic concepts in Geo-information Science and Earth Observation; LO 1 Explain mathematical notions in algorithmics and literate programming, and apply in code development. LO 2 Understand and apply the fundamentals of programming, and express programs in properly documented code. Use of geospatial data in algorithms, amongst others, through dedicated libraries. LO 3 Critically evaluate program logic and correctness through read, test and debug cycles. LO 4 Programmatically manipulate data containers such as plain text files, vector data sets and raster images, and program-internal containers such as arrays. LO 5 Use spatial databases to load, curate and otherwise manipulate data in a vector database. LO 6 Explain and use in code the fundamental notions of scientific data visualization. LO 7 Explain and use principles of web programming. LO 8 Develop independent learning, critical thinking through portfolio building.
Presential
English
Scientific geocomputing
English

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or HaDEA. Neither the European Union nor the granting authority can be held responsible for them. The statements made herein do not necessarily have the consent or agreement of the ASTRAIOS Consortium. These represent the opinion and findings of the author(s).