森林树高的反演是极化干涉合成孔径雷达(polarimetric SAR interferometry,PolInSAR)领域研究的热点。已有研究表明森林密度会对树高反演精度产生较大影响,但传统算法没有考虑森林密度的影响。针对这一现象,首先利用模拟数据分析森林密...森林树高的反演是极化干涉合成孔径雷达(polarimetric SAR interferometry,PolInSAR)领域研究的热点。已有研究表明森林密度会对树高反演精度产生较大影响,但传统算法没有考虑森林密度的影响。针对这一现象,首先利用模拟数据分析森林密度对传统森林树高反演算法的影响;然后根据影响的特点提出一种基于森林密度的相位与幅度联合反演算法;最后采用德国宇航局与瑞典国防研究局机载E-SAR系统获取的PolInSAR数据对文中所用算法进行了实验分析。结果表明,该算法比传统算法反演精度更高,验证了算法的可靠性和有效性。由此可见,森林密度是森林重要的森林物理参数,通过引入森林密度,明显提升了树高反演的效果,说明引入密度参数的重要性。展开更多
This paper proposes a joint method to simultaneously retrieve wave spectra at dif ferent scales from spaceborne Synthetic Aperture Radar(SAR) and wave spectrometer data. The method combines the output from the two dif...This paper proposes a joint method to simultaneously retrieve wave spectra at dif ferent scales from spaceborne Synthetic Aperture Radar(SAR) and wave spectrometer data. The method combines the output from the two dif ferent sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coeffi cient is estimated using an ef fective signifi cant wave height(SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coeffi cient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as fi rst guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length(PWL), and peak wave direction(PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR(ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting(ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.展开更多
文摘森林树高的反演是极化干涉合成孔径雷达(polarimetric SAR interferometry,PolInSAR)领域研究的热点。已有研究表明森林密度会对树高反演精度产生较大影响,但传统算法没有考虑森林密度的影响。针对这一现象,首先利用模拟数据分析森林密度对传统森林树高反演算法的影响;然后根据影响的特点提出一种基于森林密度的相位与幅度联合反演算法;最后采用德国宇航局与瑞典国防研究局机载E-SAR系统获取的PolInSAR数据对文中所用算法进行了实验分析。结果表明,该算法比传统算法反演精度更高,验证了算法的可靠性和有效性。由此可见,森林密度是森林重要的森林物理参数,通过引入森林密度,明显提升了树高反演的效果,说明引入密度参数的重要性。
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2013AA09A505)the National Science Foundation for Young Scientists of China(Nos.41306191,41306192,41321004,41406203)the Scientific Research Fund of the Second Institute of Oceanography,State Oceanic Administration of China(No.JG1317)
文摘This paper proposes a joint method to simultaneously retrieve wave spectra at dif ferent scales from spaceborne Synthetic Aperture Radar(SAR) and wave spectrometer data. The method combines the output from the two dif ferent sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coeffi cient is estimated using an ef fective signifi cant wave height(SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coeffi cient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as fi rst guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length(PWL), and peak wave direction(PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR(ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting(ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.
