Digital Earth Africa process openly accessible and freely available data to produce decision-ready products. The Australian-government funded organization is leveraging existing capacity to enable the use of earth observations to address critical challenges across Africa.
In late August, DEA launched a six-week training program as part of the transition to Digital Earth Africa’s continental-wide infrastructure from the Africa Regional Data Cube (ARDC) currently supporting Ghana, Senegal, Sierra Leone, and Tanzania. After the program’s first run, the organization is seeking to grow its capacity development initiative by inviting more users to the platform
The training program was developed as part of the ARCD transition process. The training material helps users learn about the Earth Observations, Python Programming, the DEA Africa Sandbox environment and the use of Jupiter Notebooks.
The program was developed after interviewing users to provide fit-for-purpose training.
Similarly, the development was guided by the DEA Capacity Development Strategy, which outlines principles for the training program. Among its fundamental principles include; that all capacity building be demand-driven and impact-oriented, and be co-created with users and have sustainable outcomes. Further, the program is designed to be socially inclusive and for a diverse range of audiences through multiple stakeholder engagement.
The program, which launched in August, is structured as a six- weeks training program designed by the DE Africa Transition team. The program was built to ensure that users can work autonomously on the DE Africa platform.
The training materials include modules made up of videos and recorded tutorials, manuals with hands-on exercises, live workshops and time with experts accord help when needed. The program engages the technical team and user engagement managers for a personalized experience.
- Introduction – This session introduces the DE Training program and shows users how to sign up on the Sandbox, the data analysis platform. It is not required to have experience in Earth Observation or Python Coding Skills.
- Datasets – This session covers the datasets available through DEA. The datasets can be visualized through the DEA Map, or sorted by availability in the DEA Metadata Explorer. The session makes us of the Sandbox to load datasets for a given area of interest and make a colour image.
- Composites – This session explores the advantages of having satellite data over a long period. The session introduces cloud-free composites and geo-median composites.
- Indices – This session explores combining multiple bands into various indices to classify and measure terrain features.
- Vegetation Analyses – This session focusses on case study building in relation to vegetation analysis
- Water Analyses – This session introduces learners to water analyses, covering Water Observation from Space (WOfS). Learners are also introduced to case studies to monitor water extent over time.
- Course Conclusion & Wrap-up – At the end of the course, learners are encouraged to venture out of the introductory course and modify case studies for their areas of interest, and exploring real-world examples.
After launch, the program was developed iteratively based on feedback from each week’s outcomes. At the end of the training, users are expected to:
- Access the sandbox
- Understand the notebook folder structure
- Understand how to copy example notebooks
- Can run coped notebooks
- Can change the location and re-run an analysis
- Understands the type of satellite imagery on the Sandbox
- Understand the basic layout of a real-world notebook
With the completion of the pilot program, DEA is seeking to grow its capacity development initiatives. The training program can be accessed here
Njeri graduated with a bachelor’s degree in Finance, from the University of Nairobi and is a CFA Level II Candidate. Currently an analyst at Space in Africa, her experience spans across Project Finance, and the analysis of Venture Capital & Private Equity Ecosystems in sub-Sahara Africa, with a particular interest in Sustainable Sciences.
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