森林叶绿素含量的高光谱遥感估算模型的建立

Establishment of Hyperspectral Remote Sensing Model for Estimating Forest Chlorophyll Content in Daxing'anling Mountain

高光谱遥感提供一个通过窄波段的地物光谱反射率、诊断和检测植被叶绿素光谱特征波段的手段,为精确反演森林叶绿素含量提供更高光谱分辨率的数据。利用Epp-2000地物光谱仪测量叶片的反射光谱,并用SPAD-502对观测叶片进行叶绿素含量的同步测量;采用统计相关分析方法,分析叶片反射光谱、光谱特征参数及其各种植被指数与叶片叶绿素含量的相关关系,并建立相应的估算模型。结果表明:叶绿素含量的敏感性参数分别为Diff(R749)、Log(R466)、红边参数RVP以及比值叶绿素指数PSSR。通过多元统计回归分析,剔除不相关和存在共线性的参数后,得到叶绿素含量的估算模型为:SPAD=54.559-0.865×PSSR+65.146×Diff(R749)-6.030×Log(R466)-0.238×Rvp,模型及其参数均通过统计检验,模型的决定系数R2达到0.812,均方根误差RMSE=13.35379,模型精度为88.743258%。

The hyperspectral remote sensing has provided a method of diagnosing and examining chlorophyll spectral characteristics by detecting the spectral reflectance of surface features in narrow band, and the data with higher spectral resolution can be obtained for reflecting the forest chlorophyll content more accurately. The reflectance spectra of leaves was measured by Epp - 2000 spectrometer, meanwhile the chlorophyll contents of leaves were measured by SPAD - 502. Then the correlations between leaf spectrum, leaf spectral characteristic parameters, various vegetation indices and leaf chlorophyll content were analyzed with statistical correlation method, and the corresponding estimation model was established. The results showed that the sensitive parameters of chlorophyll content were Diff （ R749 ） , Log （ R466 ）, red edge Rw and chlorophyll ratio PSSR. After eliminating uncorrelated and colinear parameters with multivariate statistical regression analysis, the obtained estimation model of chlorophyll content was SPAD = 54. 559 - 0. 865PSSR ＋ 65. 146D/ff （ R749 ） - 6. 030Log （R466） -0. 238Rye. The model and its parameters all passed the statistical tests, its determination coefficient R2 was up to 0. 812, the root mean square error （RMSE） was 13. 35379, and the model accuracy was 88. 743258%.