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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland
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ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation Over Cropland

机译：Scatsat-1叶面积指数产品：模型比较，开发和农田验证

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摘要

The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (ISRO), provides data at a higher temporal and spatial resolution for various applications. Due to its all-weather operational capability, it could be used as an alternative to the optical/IR sensors for the LAI estimation. In the technical literature domain, no testing has been done to estimate the LAI using ScatSat-1 scatterometer data. Therefore, the objective of this study is to retrieve the LAI using the ScatSat-1 backscattering by modifications of two different models viz. water cloud model (WCM) and the recently developed Oveisgharan et al. model and compared against the PROBA-V, MODIS, and ground-based LAI products. To assess the performance of these models, coefficient of determination ( $R<^>{2}$ ), root-mean-squared error (RMSE) and bias are computed. For Oveisgharan et al., the values of $R<^>{2}$ , RMSE and bias were obtained as 0.87, 0.57 m(2)m(-2), and 0.05 m(2)m(-2) respectively, whereas for WCM model, the values were found as 0.82, 0.67 m(2)m(-2), and 0.32 m(2)m(-2) respectively. This investigation showed that the modifications in Oveisgharan et al. model provide marginally better results in the retrieval of LAI using ScatSat-1 data than the WCM model. The models' limitation may be less serious for crop management studies because the majority of crops attains its maturity at LAI values less than 6 m(2)/m(2).
机译：叶面积指数（LAI）是治理植物檐篷的物理和生物物理过程，并作为陆地表面和土壤水分建模中的输入变量。 Scatsat-1是印度空间研究组织（ISRO）的最新微波Ku带散射计，为各种应用提供了更高的时间和空间分辨率的数据。由于其全天候操作能力，它可以用作LAI估计的光/红外传感器的替代品。在技​​术文献域中，没有进行任何测试来估计使用Scatsat-1散射计数器数据来估算LAI。因此，本研究的目的是通过两个不同型号的修改来使用SCATSAT-1反向散射来检索LAI。水云模型（WCM）和最近开发的Oveisgharan等人。模型并与Proba-V，MODIS和基于地面赖产品进行比较。为了评估这些模型的性能，计算统计系数（$ r <^> {2} $），计算根均平方误差（RMSE）和偏置。对于Oveisgharan等，获得$ R <^> {2} $，RMSE和偏差的值，分别获得0.87,0.57m（2）m（-2）和0.05 m（2）m（-2） ，而对于WCM型号，发现该值分别为0.82,0.67m（2）m（-2）和0.32m（2）m（-2）。这项调查显示，Oveisgharan等人的修改。模型在使用Scatsat-1数据的检索方面提供了比WCM模型的Scatsat-1数据更好的结果。对于作物管理研究，模型的限制可能不太严重，因为大多数作物在小于6米（2）/ m（2）的LAI值中达到其成熟度。

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