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PARTNERSHIPS FOR ENHANCED ENGAGEMENT IN RESEARCH (PEER)
Cycle 8 (2019 Deadline)


Application of partitioned woody and herbaceous forage estimates in index-based livestock insurance, a better alternative to NDVI as a proxy for forage index

PI: Milkah Kahiu (n.kahiu@cgiar.org), International Livestock Research Institute, in partnership with Jomo Kenyatta University of Agriculture and Technology
U.S. Partner: Niall Hanan, New Mexico State University
Project dates: January 2020 - March 2022

Project Overview:

8-56 Field Exploration
The project team surveys the land (photo courtesy of Dr. Kahiu).
Pastoralists inhabiting African rangelands primarily depend on livestock for their livelihoods but remain extremely vulnerable to droughts, the single largest cause of livestock mortality in the region. To mitigate the devastating impacts of drought, the International Livestock Research Institute initiated Index-Based Livestock Insurance (IBLI) to cushion pastoralists against the adverse impacts of drought. In 2015, the Kenyan government adopted IBLI through the Kenya Livestock Insurance Programme (KLIP), as part of a larger national social protection program. As of 2019, it provides coverage to nearly 20,000 households in eight Kenyan counties, with expansion plans including an additional six counties targeting more than 100,000 households by 2020. Due to the program’s success in Kenya, further expansion plans have focused on Ethiopia, where successful implementation is ongoing in Borana Region and a feasibility analysis in Somali Region has opened doors for further expansion. Other countries where feasibility analysis has promising results are Niger, Uganda, and Somalia, with further plans to cover the larger horn of Africa. Current IBLI contracts are based on an independent index derived from the Normalized Difference Vegetation Index (NDVI) as a proxy for forage scarcity, thus making it immune to manipulations by insurance clients or companies. NDVI is an indicator of vegetation vigor/greenness for all vegetation in a landscape. However, livestock in pastoral systems largely feed on herbaceous foliage, hence limiting the precision of aggregate NDVI for estimating forage availability, especially in areas with significant tree and tall shrub cover. Moreover, intended IBLI expansion into agrosilvopastoral systems poses a challenge in the current insurance contract design due to the mixture of woody cover, crops, and rangeland vegetation. These considerations necessitate review of the current index variables. It is noteworthy that the NDVI data used in the current IBLI is based on eMODIS, and with the MODIS Terra and Aqua instrument lifespans coming to an end, there is a need to explore alternative data sources for IBLI. Thus, the PI Dr. Kahiu and his team will carry out PEER-supported research exploring use of new satellite products for estimating forage index, contract design, and feasibility analysis. Their research will focus on expanding the analysis to include both LAI and NDVI data from the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) to ensure continuity in data flows for IBLI.

IBLI is a tool that that addresses the devastating impacts of drought and fosters economic development and growth in the marginalized pastoral areas in Africa. In Kenya and Ethiopia, where a significant portion of the population still lives in poverty with limited access to basic services, affected by chronic droughts and food insecurity, IBLI is a welcome innovation. It has the potential to increase household food security and resilience for the pastoral communities, attract private sector investment and increased public and private capital flows, and improve financial institutions and infrastructures. The planned PEER project facilitates an improved forage index and better contract design, consequently fostering IBLI expansion toward broader impacts on pastoral livelihoods and sustainability across Africa. IBLI is fully operational in Kenya and Ethiopia, with government support contributing to livestock insurance policy in ongoing agricultural sector reforms towards smart agricultural practices. The current PEER-supported research will focus on Kenya and, if successful, could be replicated elsewhere in Africa. 

Summary of Recent Activities

In this reporting period, the project team continued to do the analysis for livestock mortality and forage availability models using NDVI and partitioned LAI. Different regression models were tested, and reviews done. They also continued to review literature on models in preparation of the analysis and production of a publication. The results were reviewed and discussed and due to the poor performance, improvements were made including:

1. Livestock data analysis done at household level using 20km buffers as extent of grazing areas to allow extraction of forage and other environmental variables.
2. Match NDVI data for use in the models with the LAI data – at the initial stages of the model development, the analysis was based the eMODIS NDVI data, available at 10-days with a spatial resolution of 250m. This was replaced by a combination of the 16-day Aqua (MYD13A1) and Terra (MYD13A1) products combined to produce an 8-day product at 500m spatial resolution to match the MODIS LAI data (MCD15A2H) available every 8 days at 500m resolution used for the partitioning. Similar pre-processing steps to smooth and cleaning out the data were implemented. The results generated above will be presented during the IGC/IRC virtual conference in October 2021. A scientific publication is in preparation

The team continues to work with the Kenya’s state department of livestock on how best to implement the R scripts for processing in IBLI which will later be later developed into sharable R-Programming packages

Regular virtual meetings with the US collaborators to deliberate on necessary processing chains and field data collection.

In the next quarter, the team plans to carry out the below:

• Review of the partitioned LAI products
• Finalize and submit the paper on livestock mortality using partitioned LAI data
• Fieldwork for collecting insitu LAI measurements for the short rain season in Kenya and Ethiopia for improved partitioning algorithms and product validation
• Analysis for VIIRS NDVI as continuity to MODIS NDVI
• Recruitment of research assistants for field work and data processing and short-term consultant to develop some of the IBLI tools for index computation and forage monitoring (awaiting approval from the grant manager)
• Automation of partitioning processing within Google Earth Engine
• National stakeholder feedback workshop
• Attend two Conferences and present papers during the Joint International Grassland & International Rangeland Kenya 2021 Virtual Congress in October and Africa GIS in November 2021


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