基于PolInSAR森林高度反演研究

Forest Height Inversion based on Polarimetric Interferometry SAR

以仿真的全极化雷达L波段为数据源进行了复相干DEM差分算法和复相干幅度算法的森林树高反演研究,并采用星载全极化微波遥感数据ALOS PALSAR数据进行实例检验。结果表明:仿真试验中DEM差分算法严重低估了森林树高,复相干幅度算法则估测精度较高;ALOS PALSAR数据时间由于去相干和配准精度低等原因,难以有效估测森林树高。

Based on the L-band simulated full-polarimetric data, forest height inversion by coherent DEM difference algorithm and amplitude coherent complex algorithms were conducted, and full-polarimetric spaceborne microwave remote sensing data ALOS PALSAR has been verified by an instance. The results show： under simulated data, DEM difference algorithm seriously underestimated the forest height, the complex coherent amplitude estimation algorithm represented high accuracy. Due to temporal decorrelation and low registration accuracy, ALOS PAL- SAR data was difficult to estimate the forest tree height effectively.