Satellite-based vegetation health indices as a criteria for insuring against drought-related yield losses

•Vegetation health (VH) indices are used to detect wheat yield losses.•Copula approach is applied to model dependence of crop yields on VH indices.•We design and evaluate insurance contracts based on VH indices.•Remote-sensing data can be used for management of drought-related yield losses.•Insuranc...

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Veröffentlicht in:Agricultural and forest meteorology 2016-04, Vol.220, p.200-206
Hauptverfasser: Bokusheva, R., Kogan, F., Vitkovskaya, I., Conradt, S., Batyrbayeva, M.
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Sprache:eng
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Zusammenfassung:•Vegetation health (VH) indices are used to detect wheat yield losses.•Copula approach is applied to model dependence of crop yields on VH indices.•We design and evaluate insurance contracts based on VH indices.•Remote-sensing data can be used for management of drought-related yield losses.•Insurance performance can be improved using satellite data of a higher resolution. This paper considers the use of indices built on the basis of remote-sensing data for crop insurance purposes. In our analysis, we compare the capacity of two satellite-based vegetation health (VH) indices, the vegetation condition index (VCI) and the temperature condition index (TCI), measured for important periods of the crop vegetation to predict farmers’ wheat yields in two main grain producing regions of Kazakhstan. The selected indices are used for the design of index-based insurance contracts. The dependence of wheat yields on vegetation conditions as measured by VCI and TCI, is modeled by applying the copula approach. Our empirical results for 47 grain-producing farms in the Northern Kazakhstan show that insurance contracts built on VH indices can provide substantial risk reductions for a group of farms, though on average for the whole sample, risk reductions were found to be moderate. The study results suggest that the effectiveness of insurance contracts can be improved using satellite data of higher resolutions and measuring indices at more disaggregated levels.
ISSN:0168-1923
1873-2240
DOI:10.1016/j.agrformet.2015.12.066