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首页> 外文期刊>Remote Sensing >Validation of a Forage Production Index (FPI) Derived from MODIS fCover Time-Series Using High-Resolution Satellite Imagery: Methodology, Results and Opportunities
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Validation of a Forage Production Index (FPI) Derived from MODIS fCover Time-Series Using High-Resolution Satellite Imagery: Methodology, Results and Opportunities

机译:使用高分辨率卫星图像验证从MODIS fCover时间序列得出的牧草生产指数(FPI):方法,结果和机会

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摘要

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 × 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.
机译:开发了一种基于指数的保险解决方案,以使用牧草生产指数(FPI)指标作为草地生产的替代品来估算和监控近乎实时的牧草生产。 FPI对应于从中等空间分辨率时间序列图像得出的绿色植被覆盖分数的积分,并以6 km×6 km的比例进行计算。使用了基于直接验证的高级方法,该方法将FPI与现场收集的生物量数据和高空间分辨率(HR)时间序列图像进行了比较。实验地点位于法国西南部的Lot和Aveyron部门。收集的数据包括2012年,2013年和2014年从28个农场的草地上获得的生物量地面测量值,以及2013年(n = 26)和2014(n = 22)覆盖Lot部门的HR图像。与地面测得的产量直接比较可得出良好的准确性(R 2 = 0.71和RMSE = 14.5%)。通过间接比较,两者之间的关系仍然很强(R 2 介于0.78至0.93之间)并且具有信息性。这些结果突出了人力资源时间序列中的分解,草地采样率和图像采集不规则的影响。在Sentinel-2之前,这项研究通过HR时间序列图像提供了有关基于指数的潜在保险产品的优缺点的有价值的信息。

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