the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Satellite-based data for agricultural index insurance: a systematic quantitative literature review
Abstract. Index-based insurance (IBI) is an effective tool for managing climate risk and promoting sustainable development. It provides payouts based on a measurable index. Remote sensing data obtained from satellites, planes, UAVs, or drones can be used to design index-based insurance products. However, the extent to which satellite-based data has been used for different crop types and geographical regions has not been systematically explored. To bridge this gap, a systematic quantitative literature review was conducted to examine the use of satellite-based datasets in designing index-based insurance products. The review analyzed 86 global studies and found that NDVI was the most commonly used satellite-based index, accounting for approximately 77 % of all studies using satellite data. The number of studies conducted after 2010 has sharply increased and almost doubled between 2016 and 2021. The studies have shown that satellite-based vegetation indices are effective in designing and developing index-based insurance for various crops. They have also found that satellite-based vegetation health indices outperform weather indices. Most studies have focused on cereal crops, with fewer studies focusing on perennial crops. The number of studies conducted in Africa, Asia and Europe is balanced. However, the research has focused on specific countries and has not been adequately spread across different regions, especially developing countries. The review suggests that satellite-based datasets will become increasingly important in designing crop index-based insurance products. This is due to their potential to reduce basis risk by providing high-resolution with adequately long and consistent datasets for data-sparse environments. The review recommends using high spatial and temporal resolution satellite datasets to further assess their capability to reduce basis risk.
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Status: open (until 23 Oct 2024)
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RC1: 'Comment on egusphere-2024-1527', Anonymous Referee #1, 04 Sep 2024
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The manuscript aims at reviewing existing studies on usage of satellite data for designing index insurance products. Overall, it is very interesting and may attract large attention from various disciplines. However, the manuscript needs little more effort in few issues, in order to publish it in a high level journal. Especially analytical discussions in the manuscript needs to be improved. Below I provide more specific suggestions for further improvements.
Specific suggestions
- It in not clear in the abstract if the study explores usage of satellite data for crops insurance or also for livestock. That needs to be specified.
- I did not conduct counting number of studies, but 86 studies seem to be not complete for me. I am sure the authors should find few more if they could conduct little more research on those studies.
- When authors cite importance and principles of index insurance, they should cite pioneers in index insurance research and not Carter et al., 2016 (Line 34). There are few earlies scientists have initiated the discussion on importance of index insurance at the onset where Prof. Carter also contributes on this topic largely following the early studies. Having nothing against this citation, earlier scientists should get valuation for their work which they initiated.
- (What are the different types of “crop” index insurance?, 2024), seems to be wrongly cited.
- In classification of indices (lines 135-140), the authors need to be cautious in weather index insurance since climate data could be also take from satellite based sources.
- When mentioning about studies on basis risk reduction, it would be useful if authors provide some number (e.g. percentage of reduction).
- I found missing discussion on interpretation of results. For example authors need to try to interpret results why studies are coming from certain parts of the word and why mainly cereals are considered. Interpreting such results may create some more specific directions for further research.
Citation: https://doi.org/10.5194/egusphere-2024-1527-RC1
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