Evaluating the quality of remote sensing products for agricultural index insurance.

ABSTRACT: Agricultural index insurance contracts increasingly use remote sensing data to estimate losses and determine indemnity payouts. Index insurance contracts inevitably make errors, failing to detect losses that occur and issuing payments when no losses occur. The quality of these contracts and the indices on which they are based, need to be evaluated to assess their fitness as insurance, and to provide a guide to choosing the index that best protects the insured. In the remote sensing literature, indices are often evaluated with generic model evaluation statistics such as R2 or Root Mean Square Error that do not directly consider the effect of errors on the quality of the insurance contract. Economic analysis suggests using measures that capture the impact of insurance on the expected economi

SUBMITTER: Kenduiywo BK 

PROVIDER: S-EPMC8500421 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature