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單基線PolInSAR森林高度反演方法研究
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國家重點(diǎn)研發(fā)計劃項(xiàng)目(2017YFB0502700)和中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金項(xiàng)目(2572018BA02)


Comparison of Five Methods to Inverse Forest Height from Single-baseline PolInSAR Data
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    摘要:

    極化干涉SAR(Polarimetric SAR interferometry,, PolInSAR)森林高度反演是當(dāng)前雷達(dá)遙感領(lǐng)域的研究熱點(diǎn),近年來出現(xiàn)了多種單基線PolInSAR森林高度反演方法。為了給單基線PolInSAR反演森林高度的算法提供基礎(chǔ),,并探索和發(fā)展效果更優(yōu)的反演方法,,使用PolSARpro軟件模擬森林平均高度為18m的L波段(L=23cm)全極化干涉SAR 數(shù)據(jù),研究了森林高度反演算法中的DEM差分法,、RVoG法,、復(fù)相干幅度反演法、混合反演法,,并基于相干優(yōu)化法對混合反演法進(jìn)行了改進(jìn),;為了更準(zhǔn)確地對算法的性能進(jìn)行比較,給出方位向?yàn)?8bin時各算法的距離向剖面的對比圖,并選取圖像的中間區(qū)域,,對森林高度位于3~30m的1104個樣本點(diǎn),,應(yīng)用均值和均方根誤差RSME對5種方法模擬的18m森林高度進(jìn)行比較。結(jié)果表明:森林高度平均值反演結(jié)果由大到小依次為:復(fù)相干幅度反演法,、混合反演法,、改進(jìn)的混合反演法、RVoG法,、DEM差分法,,分別為19.40、18.31,、18.12,、10.55、10.05m,,均方根誤差(RMSE)由小到大依次為: 改進(jìn)的混合反演法,、混合反演法、復(fù)相干幅度反演法,、RVoG法,、DEM差分法,分別為1.06,、1.48,、3.49、7.51,、8.04m,;說明DEM差分法與RVoG法反演的森林高度存在明顯低估,復(fù)相干反演法出現(xiàn)明顯高估且其離散程度最大,,混合反演法和改進(jìn)的混合反演法與真實(shí)值的誤差分別為0.31,、0.12m,改進(jìn)的混合反演法與真實(shí)值的相差最小,,離散程度最小,,均方根誤差最小,反演結(jié)果最優(yōu),。改進(jìn)的混合反演法綜合了混合反演法與相干優(yōu)化法的優(yōu)點(diǎn),,使其估計的地形相位的均方根誤差最小(0.045rad),,森林高度與真實(shí)值的誤差最小,,均方根誤差最小,并且具有一定的魯棒性,。

    Abstract:

    To provide the basis for the methods of vegetation height inversion by using single-baseline PolInSAR SAR data and explore a more effective inversion method, the European Space Agency (ESA) Toolbox PolSARPro was used to simulate L-band (L=23cm) PolInSAR SAR data with an average vegetation height of 18m. The DEM difference, RVoG, SINC, Hybrid, and Hybrid method were studied based on coherent optimization. The vegetation height ranged from 3m to 30m was analyzed with 1104 sample points in the middle region of the image. Giving a 3D image, range profile image with azimuth of 48 and statistical image of vegetation height and topographic phase were used to compare the performance of five methods. Compared with the real value of 18m, the descending order of vegetation height means was SINC, Hybrid, improved Hybrid, RVoG and DEM difference method. The difference between the improved Hybrid inversion method and the real value was the smallest as 0.12m, smaller than Hybrid of 0.31m. RMSE of the improved Hybrid, Hybrid, SINC, RVoG and DEM difference was 1.06m, 1.48m,3.49m, 7.51m and 8.04m, respectively. The vegetation height of the improved Hybrid method had the smallest difference and RMSE. The estimated topographic phase average value of the improved Hybrid, RVoG/Hybrid and DEM difference method was -0.018rad, 0.011rad and 0.1rad;RMSE was 0.045rad, 0.054rad and 0.15rad;and mean value of absolute value was 0.03rad, 0.04rad, and 0.1rad, respectively. The topographic phase of the improved Hybrid method was approximately the closest to the simulated and had the smallest RMSE and the mean of absolute value. Improved Hybrid inversion method produced the best result among the five methods, combining the merits of Hybrid with the coherent optimization, with the smallest difference between real value and RMSE of vegetation height and topographic phase. The Hybrid method was improved based on the coherent optimization and the accuracy of vegetation height was analyzed with the ground phase estimation results to compare the five methods.

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張建雙,范文義,毛學(xué)剛,于穎.單基線PolInSAR森林高度反演方法研究[J].農(nóng)業(yè)機(jī)械學(xué)報,2018,49(10):220-229. ZHANG Jianshuang, FAN Wenyi, MAO Xuegang, YU Ying. Comparison of Five Methods to Inverse Forest Height from Single-baseline PolInSAR Data[J]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(10):220-229.

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  • 收稿日期:2018-04-20
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  • 在線發(fā)布日期: 2018-10-10
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