Face to Face course on Mapping and Performance Monitoring of Agroecosystems from Space

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.