基于高光谱的祁连山东段灌丛生物量估测模型构建

Construction of shrub biomass estimation modelbased on hyper-spectrum in the EasternQilian Mountains

摘要:

以青藏高原祁连山东段的优势灌丛金露梅(Potentilla fruticosa)、杜鹃(Rhododendron simsii)、高山柳(Salix cupularis)为研究对象,依据野外实地采集的植物高光谱数据和生物量数据,选取特征波段构建高光谱植被指数,利用单因素回归法分别建立了5种植被指数(NDVI、RVI、DVI、GNDVI、PRI)与生物量的4种估测模型(线性、指数、对数、多项式),并对模型的拟合效果进行精度验证。结果表明:灌丛生物量与NDVI和GNDVI的相关性较高(R²＞0.8),多项式模型拟合效果优于线性模型、指数模型、对数模型。利用GNDVI构建的高寒灌丛生物量的多项式拟合估测模型模拟精度最高,拟合效果最好,复相关系数R²=0.884 9,为最优模型。构建高寒灌丛生物量估测模型,对准确估测青藏高原高寒灌丛的生物量具有重要的现实意义,同时可为青藏高原其他植物生物量的估测以及青藏高原的保护提供理论参考。

Abstract:

Taking the dominant shrubs,Potentillafruticosa L,Rhododendron ,and Salix cupularis,in the Eastern Qilian Mountains of the Qinghai-Tibet Plateau as the research objects and based on field hyperspectral data and biomass data collected in the field,we selected the characteristic bands to form the hyperspectral vegetation index,four estimation models of biomass (linear,exponential,logarithmic,and polynomial) and five vegetation index (NDVI,RVI,DVI,GNDVI,and PRI) were constructed by single factor regression method,and the accuracy of the model's fitting effect was verified.The results showed that shrub biomass was highly correlated with NDVI and GNDVI (R²＞0.8),and the fitting effect of polynomial model was better than that of the linear model,exponential model,and logarithmic model.The polynomial fitting estimation model of alpine shrub biomass constructed by GNDVI was the optimal model,which has the highest simulation accuracy and the best fitting effect (R²=0.884 9).The establishment of the biomass estimation model of alpine shrub had important practical significance for accurate estimation of the alpine shrub biomass on the Qinghai-Tibet Plateau,and can provide a theoretical reference for the estimation of other plant biomass and protection of the Qinghai-Tibet Plateau.