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Evaluation of BIAS reduction in cross-calibration of NDVI based on soil isoline equations: Comparison with error estimated from signal-to-noise ratio

机译:基于土壤等值线方程式的NDVI交叉校准中的BIAS降低评估:与信噪比估计的误差进行比较

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Intercalibration among remotely-sensed data products such as spectral vegetation indices (VIs) from sensors onboard different satellites has been investigated for integrational use of multiple datasets. To facilitate intercalibration technique of VIs, the relationships among the VI values from different sensors need to be fully understood. This study evaluated the accuracies of NDVI translation technique based on soil iso-line equations. The evaluation was performed by comparing the errors in intersensor relationships of NDVI simulated by radiative transfer model and propagted error in NDVI from the sensor specific signal-to-noise ratio (SNR) of each band. The numerical results indicated that the translation equation showed enough accuracy relative to the propagated error originated from SNR, if the soil brightness underneath the canopy layer can be estimated prior to the translation.
机译:已经研究了遥感数据产品(例如来自不同卫星上的传感器的光谱植被指数(VI))之间的相互校准,以整合使用多个数据集。为了促进VI的相互校准技术,需要充分理解来自不同传感器的VI值之间的关系。这项研究评估了基于土壤等值线方程的NDVI转换技术的准确性。通过比较辐射传递模型模拟的NDVI的传感器间关系误差和NDVI从每个频带的传感器特定信噪比(SNR)传播的误差来进行评估。数值结果表明,如果可以在平移之前估算冠层下的土壤亮度,则平移方程相对于源自SNR的传播误差具有足够的精度。

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