{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T20:57:25Z","timestamp":1774990645030,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,9]],"date-time":"2015-09-09T00:00:00Z","timestamp":1441756800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An index-based insurance solution was developed to estimate and monitor near real-time forage production using the indicator Forage Production Index (FPI) as a surrogate of the grassland production. The FPI corresponds to the integral of the fraction of green vegetation cover derived from moderate spatial resolution time series images and was calculated at the 6 km \u00d7 6 km scale. An upscaled approach based on direct validation was used that compared FPI with field-collected biomass data and high spatial resolution (HR) time series images. The experimental site was located in the Lot and Aveyron departments of southwestern France. Data collected included biomass ground measurements from grassland plots at 28 farms for the years 2012, 2013 and 2014 and HR images covering the Lot department in 2013 (n = 26) and 2014 (n = 22). Direct comparison with ground-measured yield led to good accuracy (R2 = 0.71 and RMSE = 14.5%). With indirect comparison, the relationship was still strong (R2 ranging from 0.78 to 0.93) and informative. These results highlight the effect of disaggregation, the grassland sampling rate, and irregularity of image acquisition in the HR time series. In advance of Sentinel-2, this study provides valuable information on the strengths and weaknesses of a potential index-based insurance product from HR time series images.<\/jats:p>","DOI":"10.3390\/rs70911525","type":"journal-article","created":{"date-parts":[[2015,9,9]],"date-time":"2015-09-09T13:16:18Z","timestamp":1441804578000},"page":"11525-11550","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Validation of a Forage Production Index (FPI) Derived from MODIS fCover Time-Series Using High-Resolution Satellite Imagery: Methodology, Results and Opportunities"],"prefix":"10.3390","volume":"7","author":[{"given":"Antoine","family":"Roumigui\u00e9","sequence":"first","affiliation":[{"name":"Universit\u00e9 de Toulouse, Institut National Polytechnique de Toulouse, Ecole d'Ing\u00e9nieurs de Purpan, UMR 1201 DYNAFOR, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anne","family":"Jacquin","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Toulouse, Institut National Polytechnique de Toulouse, Ecole d'Ing\u00e9nieurs de Purpan, UMR 1201 DYNAFOR, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gr\u00e9goire","family":"Sigel","sequence":"additional","affiliation":[{"name":"Airbus Defence and Space, 5, rue des Satellites, 31400 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Herv\u00e9","family":"Poilv\u00e9","sequence":"additional","affiliation":[{"name":"Airbus Defence and Space, 5, rue des Satellites, 31400 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olivier","family":"Hagolle","sequence":"additional","affiliation":[{"name":"CESBIO UMR 5126 CNES-UPS-CNRS-IRD, 31400 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean","family":"Dayd\u00e9","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Toulouse, Institut National Polytechnique de Toulouse, Ecole d'Ing\u00e9nieurs de Purpan, UMR 1201 DYNAFOR, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,9]]},"reference":[{"key":"ref_1","unstructured":"Suttie, J.M., Reynolds, S.G., and Batello, C. 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