A F2F course of the EO AFRICA R&D Facility will take place in Kigali, Rwanda, in close collaboration with the African Association of Remote Sensing of the Environment (AARSE) 2022.
The course will provide participants with the necessary theoretical and practical knowledge for getting started on monitoring agroecosystems (croplands + rangelands) with satellite EO data. It will introduce the general concept of EO-based vegetation/drought monitoring, the distinct types of potentially useful EO data, relevant sensors, and derived data products, as well as different analysis techniques that can be employed to derive information from the satellite observations. The key dataset used for benchmark mapping and for change and performance monitoring as can be influenced by droughts, will be the 20 years low-resolution NDVI-images from Copernicus (CGLS). Methods will apply to agricultural areas, rangelands, and natural areas alike. An actual application for drought-insurance, that focuses on detecting the occurrence of extreme low NDVI-values, will be presented. Various techniques will be practiced by using Jupyter notebooks. In addition, participants will have the opportunity to apply knowledge gained on monitoring agroecosystems by completing two hands-on (1-day) practical exercises; one focused on estimating carrying capacity in rangelands and the second one on crop yield anomaly detection in the Cornbelt of Kenya.
It’s a 5-day course (6h per day), covering:
- Types of droughts – Droughts from a historical perspective.
- Time and Space – Setting the Scene.
- HyperTemporal-Mapping of Ecological Systems.
- Experiences gained when mapping the Masai Mara rangelands.
- Intros on “drought detection to support crop insurance models”.
- Logic behind the NDVI-based Micro-Insurance Scheme to address the peril “Drought”.
- Jupyter Notebook exercises.
- Integration of Copernicus dry matter productivity and land cover products to arrive at available forage, livestock requirements, and carrying capacity.
- Analysis of interannual changes in biophysical indicators and their standardized anomalies in relation to district-level crop yield estimates.
Upon completion of this course, the participant will:
- Recognise the different types of drought, contrast the differences between types of drought, and describe how EO information can be used to characterize droughts.
- List sources plus specifics of Hyper-Temporal (HT) NDVI-imagery, describe required pre-processing steps, explain and defend: (i) why HT NDVI-data are functional to map at country level “What is Where and to define When it is There”, and (ii) how we capture “Climatology aspects” (long-term averages) of “Crop Production Systems Zones” (CPSZs).
- Implode an NDVI data-cube to the required “information”, that is, create a map that specifies: (i) what is where (for monitoring changes; inter-annually), (ii) when is it there (intra-annually), (iii) what is its extent and density, and (iv) what is its temporal annual behaviour.
- Evaluate available forage and livestock requirements (carrying capacity) on a pixel basis using Copernicus products and other geospatial datasets.
- Identify a drought and other crop yield anomalies and assess their impact on agricultural production.
ABOUT THE COURSE
CAN I APPLY?
Who can participate?
Space is limited to max. 25 Participants. Participants will be selected on the basis of their academic background, work experience and motivation to participate. If you are selected you will receive a confirmation e-mail with further information by September 29, 2022.
Participants should reside in one of the African countries, should have an academic background related to Geoinformation/Earth Observation Science in combination with knowledge on Water Resources Management, Irrigation, Agriculture, or similar. Young researchers in this field are encouraged to apply!
On day 1, participants will be presented with webinars on the time and space aspects of monitoring with remote sensing and drought monitoring. This will be followed by a practical on generating normalized difference vegetation index (NDVI) data cubes. Day 2 and 3 are dedicated to rangeland mapping and weather-based index crop insurance payout triggers using the NDVI data cubes. In day 4, participants will calculate carrying capacity with rangeland maps and other remote sensing data. In day 5, participants will relate NDVI and other biophysical indices to corn yield anomalies.
- Morning session: 9:30 – 12:00, 2.5 hours
- Lunch break: 12:00 – 13:00
- Afternoon session: 13:00 – 16:30, 3.5 hours
Certificate of completion
All participants who will complete the course and present their individual case study will receive a Certificate of completion issued by the EO Africa R&D Facility.
Participants are requested to bring their own (updated) laptop.
It is strongly advised that the participants follow the first 2 On-line courses of the EO AFRICA R&D Space Academy ("Cloud Computing and Algorithms for EO Analyses" and "Principles of and advances in Earth Observation"). The courses are currently closed but participants will get access upon acceptance for this Face to Face course.
Attendance to the training course is free of charge.
Participants will need to arrange and pay their own travel, subsistence and accommodation. Lunch will be provided during the workshop. The Facility can sponsor up to EUR 200 to cover such expenses. Should you want to apply for this funding, please indicate it in the application form.