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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Retrieving crop parameters based on tandem ERS 1/2 interferometric coherence images
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Retrieving crop parameters based on tandem ERS 1/2 interferometric coherence images

机译:基于串联ERS 1/2干涉相干图像检索作物参数

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摘要

One-day interval coherence images derived from pairs of ERS SAR tandem acquisitions are suitable for crop monitoring. Coherence images were analyzed and compared to field measurements of four crops, i.e., winter wheat, sugar beet, potato and maize, taken during the satellite overpass. First, the sensitivity of the coherence to the plant height and the canopy cover was statistically investigated. Regression analyses were computed and the coefficients of determination (R{sup}2) ranged from 0.64 to 0.92. The shape of these relationships varied according to the geometric factors which are crop-type dependent. A prediction model of the wheat height was calculated and was able to estimate the plant height with a mean absolute error of approximately 1 cm. While this high performance obtained on the average matched the observed range of the field height for a given date, it was not sufficient for monitoring at the field level. However, such a performance level may meet the information requirements for an operational crop monitoring system at the regional level, which includes a much larger diversity of growing conditions. Moreover, the soil roughness change associated with the sowing practices that occurred between the two tandem acquisitions strongly decreased the coherence signal. This dataset also indicated that variation in the soil moisture influenced the backscattering coefficient more than it influenced the coherence signal. This result enhanced the InSAR coherence potentialities to estimate the crop parameters during the growing season.
机译:从成对的ERS SAR串联获取的一日间隔相干图像适用于作物监测。分析了相干图像,并将其与在卫星立交桥期间拍摄的四种农作物(即冬小麦,甜菜,马铃薯和玉米)的田间测量结果进行了比较。首先,统计研究了对植物高度和冠层覆盖的一致性的敏感性。计算回归分析,并且确定系数(R {sup} 2)在0.64至0.92的范围内。这些关系的形状根据取决于作物类型的几何因素而变化。计算了小麦高度的预测模型,该模型能够估计植物高度,且平均绝对误差约为1 cm。虽然平均而言获得的这种高性能与给定日期的观测到的场高范围相匹配,但不足以在场级进行监视。但是,这样的绩效水平可能满足区域一级业务作物监测系统的信息要求,该系统包括更大范围的生长条件。此外,在两次串联采集之间发生的与播种实践相关的土壤粗糙度变化大大降低了相干信号。该数据集还表明,土壤水分的变化对反向散射系数的影响大于对相干信号的影响。该结果增强了InSAR相干性,以估计生长季节中的作物参数。

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