Journal article
North American Actuarial Journal · 2020-04-02 · Volume 24 · Issue 2 · pp. 333-354
DOI: 10.1080/10920277.2020.1717345
Published online: 2020-02-10 · Download citation (BibTeX)
Abstract
Index insurance for crops is still at a relatively infant stage, and more research and development is needed in order to address a main limitation, which is referred to as basis risk (the mismatch between the loss indicated by the index and the actual loss suffered by the insured). Traditionally ground weather station measurements have been the most common approach used in weather indices, and this approach has often led to high levels of basis risk. Recent advances in satellite-based remote sensing provides new opportunities to use publicly available and transparent “big data”, to potentially make index-based insurance policies more relevant by reducing basis risk. This is the first paper to provide a comprehensive comparison of thirteen Pasture Production Indices (PPI's), including those developed based on satellite-derived vegetation and biophysical parameter indices using data products from the Moderate Resolution Imaging Spectroradiometer - MODIS. A validation protocol is established, and a unique dataset covering the period from 2002 to 2016 from a network of pasture clip sites in the province of Alberta, Canada is used to demonstrate new applications for insurance based on remote sensing derived data.
Keywords: Crop Yield Prediction; Forage Insurance; Remote Sensing; Index-Based Insurance; Principal Component Analysis; Predictive Analytics