RIICE Training Report: Building Capacity for Satellite-Based Rice Monitoring in Kenya

Raviz, Jeny; Quicho, Emma; Mathieu, Renaud

RIICE Training Report: Building Capacity for Satellite-Based Rice Monitoring in Kenya

Autores

Raviz, Jeny

Quicho, Emma

Mathieu, Renaud

Editor

International Rice Research Institute

Descripción

"The Training Course on “Remote Sensing-based Information and Insurance for Crops in Emerging Economies (RIICE)” was held on 1–5 December 2025 at the KALRO Food Crops Research Centre, Kabete, in Nairobi, Kenya, with the primary purpose of building practical expertise in satellite-based rice monitoring system and initiating the training of a national core team capable of operating RIICE. RIICE is a digital platform that integrates Synthetic Aperture Radar (SAR) satellite imagery with crop growth models to generate near real-time information on rice area, phenology, yields, and climate-driven production losses, thereby enhancing decision-making for governments, insurers, and development stakeholders. The five-day capacity-building program was organized by the International Rice Research Institute (IRRI) in partnership with Kenya Agricultural and Livestock Research Organization (KALRO). The training was participated by scientists and technical staff from KALRO, the National Irrigation Authority (NIA), universities, and the Regional Centre for Mapping of Resources for Development (RCMRD), and covered the full workflow from Synthetic Aperture Radar (SAR) data preprocessing through rice area mapping, yield estimation, and validation, using data from the Mwea Irrigation Scheme’s 2024 main season. Key takeaways were centered on three primary areas. First, participants gained a solid conceptual understanding of the RIICE framework and how SAR imagery overcomes cloud-cover limitations to provide reliable rice areas and phenology information. Second, they developed practical skills in using MAPscape-RICE to pre-process Sentinel‑1 SAR data, generate rice area and start-of-season maps, and conduct accuracy assessments and area estimation at different administrative scales. Third, they learned to operate the Rice-Yield Estimation System (Rice-YES), integrating SAR-derived indicators with the ORYZA crop model to produce spatially explicit yield estimates and aggregated statistics relevant for production monitoring, food security planning, and potential insurance applications. Participant feedback highlighted the high relevance and applicability of the training to Kenya’s rice sector, particularly for improving transparency in production statistics and supporting climate risk management in irrigated schemes such as Mwea. They appreciated the strongly hands-on design, noting that working with Kenyan datasets and real-case workflows made it easier to see how RIICE could be embedded in existing institutional mandates and seasonal routines. They also emphasized the value of the multi-institutional cohort, which fostered a clearer understanding of complementary roles, and benefits of multi-institution collaboration for operating such a system: KALRO for agronomy and agricultural geospatial research and applications, NIA for scheme-level operational data and water management, RCMRD for advanced geospatial processing and data dissemination, and universities for research and training. Feedback pointed to a demand for follow-up advanced modules—particularly on SAR data and ORYZA calibration—as well as continued mentorship to strengthen skills. Overall, participants expressed strong interest in contributing to a coordinated national RIICE system and saw the training as a crucial step toward national ownership and long-term sustainability of satellite-based rice monitoring in Kenya."

Palabras clave

rice, remote sensing, synthetic aperture radar, satellite imagery, crop monitoring, crop growth, decision-support systems, capacity building, agricultural insurance