GeoCourseHub Browser | Dataset | itc_courses | Resource | http://gch.utwente.nl/data/course/2d08cd46-00fb-488a-97d3-36e6524c5a71 | Category

Description

In this course, the student learns to develop algorithmic solutions to geospatial problems. Turn-key software systems for Geo-information Science and Earth Observation are functionally powerful but have no instant solution to each geospatial problem that may arise. The ability to construct custom solutions is an essential capability of the Geoinformatics specialist, who should have competence in addressing geospatial problems by algorithmic solutions. 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.

English

ITC course number

GFM_001

Number of credits

Course duration in hours

196

Course duration in weeks

End date

2023-02-02T23:00:00Z

Delivery mode

f2f

Didactical approach description

The student should expect a course that aims to bring professional and scientific skills in computational work with geospatial data. Short but intensive lectures bring the theoretical background, which is separately examined. Extensive practicals aim for the student to learn alone but also together and to share with peers in what is learned; students will be asked to explain their problems and solutions in the practical sessions. These practicals prepare for a batch of skills tests that each student executes individually during the course. A final skills test is executed at course end. In the post-covid19 era, we may continue to see specific requirements and conditions for education. These may impact opportunities for face-to-face exchange, which appears especially relevant for practicals supervision. We will try find ways that allow optimal exchange and discussion between supervisors and students.

English

Prerequisite knowledge description

The course is likely to see entrants with different levels of understanding and skills in the computational (scripting/coding) domain. Its design assumes no previous scripting/coding experience, but having such will generally help. ,Sufficient understanding of the spatial data models (simple vector features, raster images) and their elements and spatial data operations as covered in the Core courses Geo-information Science and Modelling, Earth Observation and Data Integration. The course is likely to see entrants with different levels of understanding and skills in the computational (scripting/coding) domain. Its design assumes no previous scripting/coding experience, but having such will generally help.

English