基于干涉相位-相干幅度法和基线选择的森林冠层高度反演
收稿日期: 2022-05-24
修回日期: 2022-07-06
网络出版日期: 2022-10-13
基金资助
国家自然科学基金项目(42061072);云南省科技厅重大科技专项(202002AA100007-015);云南省教育厅科学研究基金项目(2022Y579)
Forest canopy height inversion based on interferometric phase-coherence amplitude method and baseline selection
Received date: 2022-05-24
Revised date: 2022-07-06
Online published: 2022-10-13
森林冠层高度是重要的森林计测参数,以中非西岸加蓬共和国境内获取的机载多基线PolInSAR数据为基础,采用相位-相干幅度法作为森林高度反演模型,使用RVoG三阶段方法来计算差分部分的森林冠层高度,并比较了PROD,LINE,ECC和VAR 4种基线选择方法下的森林冠层高度反演结果差异。结果表明:在4种不同基线选择下反演结果中,采用LINE方法选择基线的反演结果最佳,R2为0.746,RMSE为7.715m,BIAS为-3.412m,反演结果较为理想;使用PROD方法和ECC方法基线选择的反演精度略低于LINE方法,且两者之间的差异并不明显,其中,采用ECC方法选择基线反演结果的R2为0.732,RMSE为7.918m,BIAS为0.139m,反演结果中低估和高估较为明显,使用PROD方法选择基线的反演结果R2为0.720,RMSE为8.099m,BIAS为-4.056m,总体呈现略微高估;VAR方法基线选择的反演结果在所有方法中精度最低,R2为-0.245,RMSE为17.079m,BIAS为12.945m,整体的低估较为严重,而且森林冠层高度大于10m以后就出现严重的低值高估现象。研究结论说明多基线PolInSAR能精确高效反演森林冠层高度,但基线选择方法对结果有显著的影响。
罗洪斌 , 岳彩荣 , 王宁 . 基于干涉相位-相干幅度法和基线选择的森林冠层高度反演[J]. 林草资源研究, 2022 , 0(4) : 119 -125 . DOI: 10.13466/j.cnki.lyzygl.2022.04.015
Forest canopy height is an important parameter.In this paper,the phase-coherence amplitude method as the forest height inversion model based on airborne multi-baseline PolInSAR data acquired in the Gabonese Republic on the west coast of Central Africa,the RVoG three-stage method is used to calculate the forest canopy height in the phase difference part,and compared the differences of forest canopy height inversion results under four baseline selection methods of PROD,LINE,ECC and VAR.The results show that among the inversion results with four different baseline selections,the best inversion results are obtained using the LINE method for baseline selection with R2 of 0.746,RMSE with 7.715m,and BIAS with -3.412m,which are more satisfactory.The inversion accuracy of baseline selection using the PROD and ECC methods is slightly lower than that of the LINE method,and the difference between them is not significant.The R2 of the baseline selection inversion results using the ECC method is 0.732,RMSE is 7.918m,and BIAS is 0.139m,and the underestimation and overestimation in the inversion results are more obvious.The inversion results of baseline selection using the PROD method have an R2 of 0.720,RMSE of 8.099m,and BIAS of -4.056m,showing a slight overestimation overall.The inversion results of baseline selection by VAR method had the lowest accuracy among all methods,with R2 of -0.245,RMSE of 17.079m,and BIAS of 12.945m,and the overall underestimation was more serious,and serious underestimation occurred after the forest canopy height was greater than 10m.The findings suggest that multi-baseline PolInSAR can accurately and efficiently invert forest canopy height,but the baseline selection method has a significant effect on the results.
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