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| Titel |
NDVI statistical distribution of pasture areas at different times in the Community of Madrid (Spain) |
| VerfasserIn |
Juan J. Martín-Sotoca, Antonio Saá-Requejo, Carlos G. H. Díaz-Ambrona, Ana M. Tarquis |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250113467
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| Publikation (Nr.) |
 EGU/EGU2015-14943.pdf |
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| Zusammenfassung |
| The severity of drought has many implications for society, including its impacts on the water
supply, water pollution, reservoir management and ecosystem. However, its impacts on
rain-fed agriculture are especially direct. Because of the importance of drought, there have
been many attempts to characterize its severity, resulting in the numerous drought indices that
have been developed (Niemeyer 2008). ‘Biomass index’ based on satellite image derived
Normalized Difference Vegetation Index (NDVI) has been used in countries like United
States of America, Canada and Spain for pasture and forage crops for some years (Rao,
2010). This type of agricultural insurance is named as “index-based insurance”
(IBI).
IBI is perceived to be substantially less costly to operate and manage than multiple peril
insurance. IBI contracts pay indemnities based not on the actual yield (or revenue) losses
experienced by the insurance purchaser but rather based on realized NDVI values (historical
data) that is correlated with farm-level losses (Xiaohui Deng et al., 2008). Definition of when
drought event occurs is defined on NDVI threshold values mainly based in statistical
parameters, average and standard deviation that characterize a normal distribution. In
this work a pasture area at the north of Community of Madrid (Spain) has been
delimited. Then, NDVI historical data was reconstructed based on remote sensing
imaging MODIS, with 500x500m2 resolution. A statistical analysis of the NDVI
histograms at consecutives 46 intervals of that area was applied to search for the best
statistical distribution based on the maximum likelihood criteria. The results show that
the normal distribution is not the optimal representation when IBI is available;
the implications in the context of crop insurance are discussed (Martín-Sotoca,
2014).
References
Kolli N Rao. 2010. Index based Crop Insurance. Agriculture and Agricultural Science
Procedia 1, 193–203.
Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones
en el Seguro Agrario. Master Thesis, UPM (In Spanish).
Niemeyer, S., 2008: New drought indices. First Int. Conf. on Drought
Management: Scientific and Technological Innovations, Zaragoza, Spain,
Joint Research Centre of the European Commission. [Available online at
http://www.iamz.ciheam.org/medroplan/zaragoza2008/Sequia2008/Session3/S.Niemeyer.pdf.]
Xiaohui Deng, Barry J. Barnett, Gerrit Hoogenboom, Yingzhuo Yu and Axel Garcia y
Garcia 2008. Alternative Crop Insurance Indexes. Journal of Agricultural and Applied
Economics, 40(1), 223–237.
Acknowledgements
First author acknowledges the Research Grant obtained from CEIGRAM in 2014 |
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