Abstract
A challenge in addressing climate risk in developing countries is that many regions have extremely limited formal data sets, so for these regions, people must rely on technologies like remote sensing for solutions. However, this means the necessary formal weather data to design and validate remote sensing solutions do not exist. Therefore, many projects use farmers’ reported perceptions and recollections of climate risk events, such as drought. However, if these are used to design risk management interventions such as insurance, there may be biases and limitations which could potentially lead to a problematic product. To better understand the value and validity of farmer perceptions, this paper explores two related questions: (1) Is there evidence that farmers reporting data have any information about actual drought events, and (2) is there evidence that it is valuable to address recollection and perception issues when using farmer-reported data? We investigated these questions by analyzing index insurance, in which remote sensing products trigger payments to farmers during loss years. Our case study is perhaps the largest participatory farmer remote sensing insurance project in Ethiopia. We tested the cross-consistency of farmer-reported seasonal vulnerabilities against the years reported as droughts by independent satellite data sources. We found evidence that farmer-reported events are independently reflected in multiple remote sensing datasets, suggesting that there is legitimate information in farmer reporting. Repeated community-based meetings over time and aggregating independent village reports over space lead to improved predictions, suggesting that it may be important to utilize methods to address potential biases.
Highlights
The increasing climate hazards and extreme weather events that affect food production and agricultural income have been the target of risk reduction strategies for smallholder farmers in the developing world [1]
In order to test if there is evidence that farmers reporting data have any information about actual drought events and if it is valuable to address recollection and perception issues when using farmer-reported data, we examined the cross-consistency of farmer-reported seasonal vulnerabilities against the years reported as having anomalously low rainfall in independent satellite data sources
We explored whether potential bias in farmer reporting was filtered through aggregation by discussing regressions across temporal aggregation, i.e., repeated discussions, and spatial aggregation, i.e., using information from nearby villages
Summary
The increasing climate hazards and extreme weather events that affect food production and agricultural income have been the target of risk reduction strategies for smallholder farmers in the developing world [1]. A key challenge in these risk reduction strategies is that there is very little information from in-situ observations for the design of solutions in the lowest income regions, where tools may be needed the most. In these situations, farmer recollections may be the most important source of information. There is a substantial body of literature on the biases in reporting due to gender issues, when important information known by women is not represented, or is suppressed by gender dynamics in the reporting process [5,6,7]. It is important to test the validity of information on farmer reporting because of these many sources of potential biases in perceptions, recollections, and reporting
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
