The anthracnose disease index (DI) of Chinese fir and the corresponding hyper-spectral remote sensing data of the disease different severity were collected through the field investigation. The correlation between DI and the first derivative data of the canopy spectral was analyzed. Inversion models were built by selecting correlation coefficients higher than 0. 7 , and their precision was tested. The result showed that there was high correlation between DI and the first derivative data in the regions of 431-485 nm, 549 -616 nm and 700 -754 ran; and the linear model contained SDy, SDr, SDg/SDb, (SDg- SDb)/( SDg + SDb) and ( SDr - SDy)/( SDr + SDy) was the best one, with the RMS ( Croot mean square) error ranged from 0.094 to 0. 119. This study showed hyper-spectral derivative data could estimate the disease severity of Chinese fir with a high the precision. This study has a high practical application value.%通过实地调查,获取杉木炭疽病病情指数以及各级病情梯度的高光谱遥感数据,将冠层光谱一阶微分数据与相应的病情指数进行相关性分析,选取相关系数大于0.7的高光谱微分指数构建反演模型,并对模型进行精度检验.结果表明:病情指数与冠层光谱一阶微分值在431～485 nm,549 ～ 616 nm和700～754 nm 3个波段达到极显著相关；以微分指数SDy,SDr,SDg/SDb,(SDg-SDb)/(SDg+SDb)和(SDr-SDy)/(SDr+SDy)为变量反演病情指数的最佳模型均为线性模型,均方根差在0.094 ～0.119之间.该研究结果表明,利用高光谱微分指数估测杉木炭疽病病情指数精度较高,且具有较高的实际应用价值.
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