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Tropical Forest Height Retrieval Based on P-Band Multibaseline SAR Data

机译:基于P波段多元化的热带森林高度检索SAR数据

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In this letter, we present an experimental assessment of vegetation height retrieval in tropical forests based on P-band synthetic aperture radar (SAR) acquisitions. Two approaches are implemented and compared: 1) parametric height estimation by minimizing the least-square problem between random volume over ground (RVoG) model predictions and multibaseline SAR data and 2) thresholding the vertical backscattering profiles that are focused by SAR Beam-forming tomography. The data set under analysis is from the ESA AfriSAR campaign that was flown over Gabon in 2016. Results show that at a resolution of which corresponds to about 80 independent looks, both of the two approaches are able to retrieve forest height to within an accuracy of about 3 m or better over the interval of forest height between 30 and 50 m when compared to Light Detection and Ranging (LiDAR) measurements.
机译:在这封信中,基于P波段合成孔径雷达(SAR)采集,对热带林植被高度检索的实验评估。 实现和比较了两种方法:1)参数高度估计通过最小化随机体积在地面(Rvog)模型预测和多元线SAR数据之间的最小方形问题,并且2)阈值,该垂直反向散射轮廓由SAR光束形成断层扫描 。 正在分析的数据集是来自2016年加蓬飞越的ESA Afrisar活动。结果表明,在该决议中,这对应于约80个独立的外观,这两种方法都能够在准确性内检索森林高度 与光检测和测距(LIDAR)测量相比,在30和50米之间的间隔约3米或更高。

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