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Estimation of crop ground cover and leaf area index (LAI) of wheat using RapidEye satellite data: Prelimary study

机译:利用RapidEye卫星数据估算小麦的作物地被植物和叶面积指数(LAI):初步研究

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摘要

Leaf area index (LAI) is an important indicator of plant growth and biomass accumulation. LAI is often required as an input parameter in many models, especially for crop yield predication and soil moisture retrieval. With recently due to the increasing demand on large-scale monitoring, optical satellite sensors capable of providing frequent LAI estimation over large coverage are favored. This paper reports the results from a study over an agriculture site with spring wheat in western Canada using data acquired from RapidEye and in situ measurements using LAI analyzer and hemispherical photos during the 2011 growing season. The prediction of crop ground cover fraction has yield a coefficient of determination of 0.66. Even better result was achieved for LAI prediction with a coefficient of determination of 0.82. Results suggest that RapdiEye optical satellite data can be a valuable data source for crop ground cover fraction and LAI retrieval.
机译:叶面积指数(LAI)是植物生长和生物量积累的重要指标。在许多模型中,通常需要LAI作为输入参数,尤其是对于作物产量的预测和土壤水分的获取。随着近来由于对大规模监视的需求的增加,能够在大覆盖范围上提供频繁的LAI估计的光学卫星传感器受到青睐。本文报告了从加拿大Rapidaye采集的数据,使用LAI分析仪和2011年生长期的半球照片进行实地测量的加拿大西部春小麦农业基地的研究结果。对农作物地被植物覆盖率的预测得出的确定系数为0.66。对于LAI预测,甚至达到了更好的结果,确定系数为0.82。结果表明,RapdiEye光学卫星数据可以为作物地面覆盖率和LAI检索提供有价值的数据源。

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