洪河自然保护区乌拉苔草生物量高光谱遥感估算模型

Hyperspectral Remote Sensing Estimation Models for the Biomass of Carex meyeriana in Honghe Nature Reserve

尝试用不同方法构建洪河自然保护区湿地植被乌拉苔草（Carex meyeriana）的高光谱植被指数，建立水上鲜／干生物量高光谱估算模型，并比较了不同模型的反演精度。通过实测不同覆盖度和水深状况下乌拉苔草的冠层高光谱反射率与水上生物量的数据，采用高光谱可见光-近红外波段及其微分光谱波段（350—1050nm）逐波段构建FNDVI、FRVI、FDVI、FDNDVI、FDRVI、FDDVI植被指数，分别找出与水上鲜生物量和干生物量具有最佳相关性波段组合的植被指数，建立乌拉苔草水上生物量的最佳估算模型，并对比分析了反射率光谱植被指数（FNDVI、FRVI、FDVI）模型和微分光谱植被指数（FDNDVI、FDRVI、FDDVI）模型的反演精度。结果显示，微分光谱与乌拉苔草水上生物量的相关性比反射率光谱好；微分光谱植被指数与乌拉苔草水上生物量的相关性比反射率光谱植被指数好，尤其以微分光谱植被指数FDRVI与FDNDVI建立的二次函数模型反演乌拉苔草的水上鲜生物量和干生物量的效果最好，精度分别达74．9％、71．4％，其均方根误差分别为0．0744和0．0262，通过了P〈0．01极显著验证。这表明，采用微分光谱植被指数FDRVI、FDNDVI对乌拉苔草水上鲜生物量和干生物量的估算可以取得较高的预测精度。

To construct the hyperspectral Vegetation Indices ture Reserve, different methods were used to compare the of of wetland vegetation Carex meyeriana in Honghe Nahyperspectral models, which were set up the vegetation indices and above - water fresh biomass and dry biomass of Carex meyeriana. Carex meyeriana was planted under the condition of different vegetation coverage and water depth, and Carex meyeriana canopy reflectance data was collected with ASD spectroradiometer （350 - 1 050 nm）. Firstly, to adopt hyperspectral visible light - near infrared spectral and derivative spectral bands（350 -1 050 mm） to construct the vegetation indices of FNDVI, FRVI, FDVI, FDNDVI, FDRVI and FDDVI one by one; secondly, to find out respectively the best band for each kind of vegetation indices which have the best correlated with above - water fresh biomass and dry biomass, and to construct the optimum estimation model of Carex meyeriana biomass; finally, to compare and analyze the prediction precision between reflectance vegetation indices models and derivative vegetation indices mod- els respectively. It was shown that, correlation between Carex meyeriana above - water biomass and derivative spectra was better than those of reflectance spectra, and Carex meyeriana above - water biomass and derivative vegetation indices were better than those of reflectance vegetation indices. Especially, The best Carex meyeriana above- water biomass model retrieved by derivative vegetation indices of FDRVI and FDNDVI was quadratic function, and the accuracy of estimation quadratic function of above - water fresh biomass and dry biomass with the best wave went up to 74.9%, 71.4%, the Root Mean Square Error were 0.074 4, 0.026 2 respectively, which was qualified at 0.01 level. The FDRVI and FDNDVI indices established by hyperspectral data can highly prediction the Carex meyeriana above - water fresh biomass and dry biomass.