Language
This program will be in English. Dit programma is alleen in het Engels.
Summary
The way currently remote sensing images, derived products and data is provided has changed the way how this information is being processed. Traditionally a stand-alone system was used with several graphical user interface-based software tools to process and analyse the data. For efficient processing nowadays, information from the cloud can be accessed, and processing is done using capabilities, like the use of a virtual research environment (VRE), provided by these cloud-based service providers. Once the analysis has been completed in these cloud VRE’s, the final products are downloaded to be integrated with existing local data sources for final analysis and visualization.
The course starts with an overview of the various operational EO satellite data and information access services and catalogues. This is followed by an overview of how ILWISPy operations can be used for interactive data science and scientific computing in conjunction with other relevant Python packages. Data applicable for various application domains will be covered. Finally, an assignment based on a topic of interest, applying the knowledge gained and tools introduced, will complete the course.
Learning outcomes
During the course participants will be familiarized with ample opportunities to apply ILWISPy functionality using a wide and readily available range of Earth Observation (EO) images and products provided in open and online data repositories.
The course objectives are both having a focus on the use of Python and ILWISPy for interactive data science and scientific computing, to be conducted locally as well as through a cloud-based virtual research environment next to the current capabilities offered by open cloud-based data repositories containing time series Earth Observation images and analysis-ready products.
With regard to the use of Python and ILWISPy for interactive data science and scientific computing, upon completion of this course, your can:
- Use Python scripting in combination with Jupyter Notebooks and required packages for Remote Sensing and GIS data (pre-) processing in the cloud;
- Use of ILWISPy scripting for interactive data science and scientific computing;
- Retrieve the results obtained to their local processing system and conduct further single or time series analysis in conjunction with local datasets;
- Import and pre-process time-series geospatial data having different data formats and conduct data conversions to numpy arrays/panda data frames and their use in advanced machine learning tools, e.g. like those offered by scikit-learn;
- Process EO data and products from online catalogues into relevant information.
With regard to open cloud-based data repositories, upon completion of this course, you can:
- Select a number of relevant open image and data repositories for their application domain;
- Retrieve the Meta Data relevant for the products of interest and derive the required information for image or data scaling, coordinate and projection information;
- Access the Earth Observation (EO) images and data products from a suite of online repositories, using Application Programming Interfaces (API);
- Retrieve selected data for use in the allocated virtual research environment or local system.
Duration
The course has been designed for 8 weeks. Each week you complete one module of the course, which consists of lectures, demo’s and exercises to bring into practice what was learnt. The study load of the entire course is 70 hours distributed in a way that you need to spend a minimum of 8 hours per week during the first seven weeks of the course. In the final week, an individual assignment having a study load of 14 hours, has to be completed and submitted online.
Entry requirements
Applicants for an online course should have a Bachelor’s degree or equivalent from a recognised university in a discipline related to the course, preferably combined with working experience in a relevant field.
Proficiency in instruction language is assumed.
Who is this offered to?
This course is intended for professionals and researchers/lecturers with a background in hydrology, meteorology or water resources and environmental sciences in general, who would like to know more about the available Earth Observations data and products while simultaneously upgrading their multi-temporal data acquisitions and processing/analysis skills, using open Python based geo-information processing software tools like ILWISPy to supplement their Graphical User Interface (GUI) based GIS and EO software skills. The course offers possibilities to change from local data processing to cloud-based data processing and visualization of the results using common GUI software tools. Also, professionals already familiar with a GUI-based version of ILWIS are welcome and will experience the seamless transition to the new scripting-based geo-processing capabilities offered. The use of the open and free tools, in combination with course materials provided are a good starting point for lecturers at centres of higher learning to introduce these within their own curricula.