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首页> 外文期刊>International journal of remote sensing >Validation of the collection 5 MODIS FPAR product in a heterogeneous agricultural landscape in arid Uzbekistan using multitemporal RapidEye imagery
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Validation of the collection 5 MODIS FPAR product in a heterogeneous agricultural landscape in arid Uzbekistan using multitemporal RapidEye imagery

机译：使用多时相RapidEye影像验证乌兹别克斯坦干旱地区异质农业景观中的5种MODIS FPAR产品

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摘要

The fraction of photosynthetically active radiation (FPAR) absorbed by a vegetation canopy is an important variable for global vegetation modelling and is operationally available from data of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor starting from the year 2000. Product validation is ongoing and important for constant product improvement, but few studies have investigated the specific accuracy of MODIS FPAR using in situ measurements and none have focused on agricultural areas. This study therefore presents a validation of the collection 5 MODIS FPAR product in a heterogeneous agricultural landscape in western Uzbekistan. High-resolution FPAR maps were compiled via linear regression between in situ FPAR measurements and the RapidEye normalized difference vegetation index (NDVI) for the 2009 season. The data were aggregated to the MODIS scale for comparison. Data on the percentage cover of agricultural crops per MODIS pixel allowed investigation of the impact of spatial heterogeneity on MODIS FPAR accuracy. Overall, the collection 5 MODIS FPAR overestimated RapidEye FPAR between approximately 6% and 15%. MODIS quality flags, the underlying biome classification and spatial heterogeneity were investigated as potential sources of error. MODIS data quality was very good in all cases. A comparison of the MODIS land-cover product with high-resolution land-use classification revealed a significant misclassification by MODIS. Yet, we found that the overestimation of MODIS FPAR is independent of classification accuracy. The results indicate that the amount of background information, present even in the most homogeneous pixels (～70% crop cover), is most likely the reason for the overestimation. The behaviour of pure pixels could not be investigated due to a lack of appropriate pixels.
机译：植被冠层吸收的光合有效辐射（FPAR）比例对于全球植被建模而言是一个重要变量，可从2000年开始从Terra中等分辨率成像光谱仪（MODIS）卫星传感器的数据中获得操作数据。虽然对于持续改进产品非常重要，但是很少有研究使用现场测量研究MODIS FPAR的特定精度，而且没有一个研究集中在农业领域。因此，本研究提出了在乌兹别克斯坦西部异质农业景观中收集5 MODIS FPAR产品的验证。通过就地FPAR测量值与RapidEye归一化植被指数（NDVI）对2009年季节进行线性回归，编制了高分辨率FPAR图。将数据汇总到MODIS规模以进行比较。关于每个MODIS像素的农作物覆盖率的数据可以研究空间异质性对MODIS FPAR精度的影响。总体而言，集合5 MODIS FPAR高估了RapidEye FPAR在大约6％和15％之间。 MODIS质量标志，潜在的生物群落分类和空间异质性被研究为潜在的误差来源。在所有情况下，MODIS数据质量都非常好。 MODIS土地覆盖产品与高分辨率土地利用分类的比较显示，MODIS进行了严重的分类错误。但是，我们发现MODIS FPAR的高估与分类精度无关。结果表明，即使在最均匀的像素（约70％作物覆盖率）中也存在背景信息量，这很可能是高估的原因。由于缺乏适当的像素，无法研究纯像素的行为。

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  • 来源
    《International journal of remote sensing》 |2012年第22期|p.6818-6837|共20页
  • 作者

    SEBASTIAN FRITSCH; MIRIAM MACHWITZ; ANDREA EHAMMER; CHRISTOPHER CONRAD; STEFAN DECH;

  • 作者单位

    Department of Remote Sensing, University of Wuerzburg, 97074 Wuerzburg, Germany;

    Department of Environment and Agro-Biotechnologies (EVA), Centre de Recherche Public - Gabriel Lippmann, 4422 Belvaux, Luxembourg;

    Institute of Geography, University of Innsbruck, 6020 Innsbruck, Austria;

    Department of Remote Sensing, University of Wuerzburg, 97074 Wuerzburg, Germany;

    Department of Remote Sensing, University of Wuerzburg, 97074 Wuerzburg, Germany,German Remote Sensing Data Centre (DFD), German Aerospace Agency (DLR), 82234 Wessling, Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
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