Miller Magazine Issue: 130 October 2020

77 ARTICLE MILLER / OCtOber 2020 and poor execution of crop insurance schemes. With technological advancements and availability, crop growth monitoring and productivity assessment can not only be more accurate and efficient but also less resource-inten- sive. Readily available data and technology, such as detailed weather data, remote sensing, modeling and big data anal- ytics can be instrumental in further improving crop insuran- ce mechanisms. The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) has develo- ped a Crop-loss Assessment Monitor (CAM) tool as an integ- rated solution that uses technologies to improve loss assess- ment and make crop insurance more efficient. The CAM tool integrates multiple input data and methods for crop loss assessment at multiple times in the season. It uses diffe- rent models for loss assessment depending on the time or stage in the season. To ensure user-friendliness, the tool was develo- ped with a simple, easy-to-use interface and produces outputs customized for policy and risk management agencies. It uses freely available R libraries and does not require specific software installations and high-power processing engines, which in gene- ral are a prerequisite to process large gridded satellite data. CAM provides a form-based user-interface to carry out the analysis. The user can log in and undertake analysis using multiple methods for a specified region and time. The tool allows users to choose between area-based yield insurance and weather-based index insurance. For insu- rance analysis, scheme details like sum insured and ca- lamity years can be specified for calculation of threshold yields, premiums and claims. CAM also includes tabs that provide ‘deviation in the weat- her’ and ‘deviation in satellite vegetation indices’ to help mo- nitor crop conditions every fortnight. The tool also allows users to identify the model agreement between the four different methods for loss assessment, which strengthens the confidence levels in loss assessments, and related insurance analytics. A SINGLE INTEGRATED FRAMEWORK The tool combines agro-meteorological statistical analy- sis, crop simulation modelling and optimization tech- niques, and employs near real-time monitoring by using publicly available satellite products. It is also equipped to capture yield variability. Highlighting the importance of this tool Dr. Pramod Ag- garwal, lead author of the paper and CCAFS Asia Program Leader, notes that “assimilating relevant technologies into a single integrated framework is a good way to determine crop losses. Its deployment can assist in multi-stage loss as- sessment and thus provide farmers with immediate relief for sowing failure, prevented sowing and mid-season adversity apart from final crop loss assessment.” The tool addresses three major challenges faced by exis- ting crop insurance schemes; more efficient weather indices, timely estimate of loss assessment and improved contract de- sign. As the tool readily uses freely available technology and data, it requires less capital and human resource compared to crop cutting experiments for crop loss assessment. This tool offers a robust mechanism that further reduces the chances of human errors, and makes the process more transparent, robust and reliable. Therefore, it enables timely relief for farmers facing challenges such as sowing failure, prevented sowing and mid-season adversity. *This article by Sakshi Saini and Paresh B Shirsath was origi- nally published on the The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) website.