冬小麦典型多参量冠层高光谱反演的光谱指标敏感性研究

发布时间：2018-05-11 19:10

本文选题：高光谱反演 + 冬小麦　；参考：《科学技术与工程》2017年25期

【摘要】：高光谱遥感反演作物参量多集中在单一参量研究上,缺乏多参量综合反演研究。因此,面向多参量反演,需要对传感器参数的有效设置,以及同一指标对不同参量的适宜程度进行综合研究。以冬小麦为例,通过实测冠层光谱反射率和LAI、叶绿素、氮素含量数据,分析了中心波长、波段宽度、信噪比等指标的变化对各参量定量模型的影响,及光谱指标对LAI、叶绿素和氮素定量模型反演的敏感性和有效性,以及对冬小麦典型参量高光谱遥感反演的光谱指标进行了综合性分析。结果表明:反演冬小麦LAI的最佳植被指数为DVI(R~2=0.457,RMSE=0.614%),对应的最佳指标为:中心波长为768 nm和732 nm,波段宽度在5 nm以内,信噪比大于70 d B;反演冬小麦叶绿素的最佳植被指数为MSR(R2=0.554,RMSE=0.548%),对应的最佳指标为:中心波长为768 nm和736 nm,波段宽度在5 nm以内,信噪比大于70 d B;反演冬小麦氮素的最佳植被指数为NDVI_(g_b)(R~2=0.733,RMSE=0.600%),对应的最佳指标为:中心波长为500 nm和454 nm,波段宽度为5 nm以内,信噪比大于70d B。植被指数SAVI在一定波段范围内可同时反演LAI、叶绿素和氮素;MSAVI、DVI、RDVI和NDVI均可在一定波段范围内同时反演LAI和叶绿素含量,而反演LAI和氮素含量的适宜波段以及反演叶绿素和氮素的适宜波段存在差异。利用高光谱植被指数可实现作物参量的有效反演,且作物参量的定量反演对不同的光谱指标,即中心波长、波段宽度和信噪比具有较强的敏感性。
[Abstract]:Hyperspectral remote sensing inversion of crop parameters is mostly focused on a single parameter, lacking of multi-parameter integrated inversion. Therefore, for multi-parameter inversion, it is necessary to comprehensively study the effective setting of sensor parameters and the suitability of the same parameter to different parameters. Taking winter wheat as an example, the effects of the changes of central wavelength, band width and signal-to-noise ratio on the quantitative models were analyzed by measuring the canopy spectral reflectance and Lai, chlorophyll and nitrogen content data. The sensitivity and validity of spectral indices to inversion of Lai chlorophyll and nitrogen quantitative models and the spectral indices of hyperspectral remote sensing inversion of typical parameters of winter wheat were comprehensively analyzed. The results showed that the best vegetation index for winter wheat LAI inversion was DVI RJ20.457RMSE 0.614, corresponding to which the center wavelength was 768nm and 732nm, and the band width was less than 5 nm. The signal to noise ratio (SNR) of winter wheat chlorophyll is more than 70 dB, and the optimum vegetation index for inversion of winter wheat chlorophyll is MSRR2O0.554 RMSE 0.548, corresponding to which the center wavelength is 768 nm and 736 nm, and the band width is less than 5 nm. The best vegetation index for the inversion of nitrogen in winter wheat is NDVI _ I _ (+) _ (0.733N) RMSE _ (0.600). The optimum indexes are as follows: the central wavelength is 500 nm and 454 nm, the band width is less than 5 nm, and the signal-to-noise ratio is more than 70 dB. The vegetation index (SAVI) can simultaneously invert Lai, and chlorophyll and nitrogen content can be simultaneously retrieved from LAI and chlorophyll content in a certain range of bands, while both chlorophyll and nitrogen content can be retrieved simultaneously by RDVI and NDVI. But the suitable bands for inversion of LAI and nitrogen content and suitable bands for inversion of chlorophyll and nitrogen content are different. The effective inversion of crop parameters can be realized by using hyperspectral vegetation index, and the quantitative inversion of crop parameters is sensitive to different spectral indexes, namely, central wavelength, band width and signal-to-noise ratio (SNR).
【作者单位】：中国地质大学地球科学与资源学院;中国科学院遥感与数字地球研究所高光谱遥感应用技术研究室;广西空间信息与测绘重点实验室;
【基金】：国家自然科学基金(41371359,41671362) 广西空间信息与测绘重点实验室开放基金(151400727) 高分辨率对地观测系统重大专项资助
【分类号】：S512.11;TP79

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