Xu Zhang-Hua, Liu Jian, Yu Kun-Yong, Gong Cong-Hong, Xie Wan-Jun, Tang Meng-Ya, Lai Ri-Wen, Li Zeng-Lu
Institute of Geomatics Application, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Feb;33(2):428-33.
Taking 51 field measured hyperspectral data with different pest levels in Yanping, Fujian Province as objects, the spectral reflectance and first derivative features of 4 levels of healthy, mild, moderate and severe insect pest were analyzed. On the basis of 7 detecting parameters construction, the pest level detecting models were built. The results showed that (1) the spectral reflectance of Pinus massoniana with pests were significantly lower than that of healthy state, and the higher the pest level, the lower the reflectance; (2) with the increase in pest level, the spectral reflectance curves' "green peak" and "red valley" of Pinus massoniana gradually disappeared, and the red edge was leveleds (3) the pest led to spectral "green peak" red shift, red edge position blue shift, but the changes in "red valley" and near-infrared position were complicated; (4) CARI, RES, REA and REDVI were highly relevant to pest levels, and the correlations between REP, RERVI, RENDVI and pest level were weak; (5) the multiple linear regression model with the variables of the 7 detection parameters could effectively detect the pest levels of Dendrolimus punctatus Walker, with both the estimation rate and accuracy above 0.85.
以福建省延平区51组不同虫害程度的实地测量高光谱数据为对象,分析了健康、轻度、中度和重度4级虫害的光谱反射率及一阶导数特征。在构建7个检测参数的基础上,建立了虫害程度检测模型。结果表明:(1)受虫害马尾松的光谱反射率显著低于健康状态,虫害程度越高,反射率越低;(2)随着虫害程度的增加,马尾松光谱反射率曲线的“绿峰”和“红谷”逐渐消失,红边变平;(3)虫害导致光谱“绿峰”红移、红边位置蓝移,但“红谷”和近红外位置的变化较为复杂;(4)CARI、RES、REA和REDVI与虫害程度高度相关,REP、RERVI、RENDVI与虫害程度的相关性较弱;(5)以7个检测参数为变量的多元线性回归模型能够有效检测马尾松毛虫的虫害程度,估计率和准确率均在0.85以上。