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通过研究铅污染胁迫下水稻的光谱高频组份的分维数来诊断水稻铅污染胁迫水平。根据实验区水稻冠层实测ASD高光谱数据和同步获取的农田土壤重金属含量数据,利用Daubechies小波系中的“Db5”母小波对水稻的350—1300nm波段范围进行小波分解得到第5层高频组份(d5),并采用盒维法计算d5的分维数,最后采用模糊数学建立d5的分维数与污染胁迫水平的数学模型。结果表明:d5能有效地探测到铅污染胁迫的光谱弱信息,并实现不同污染水平水稻高光谱信号的分离;d5分维数在同一污染水平的年际相对变化率小于4%,不同污染水平的区分度大于75%,即高、中和低污染水平水稻高光谱d5分维数的86.7%、75%和91.7%分别集中在1.160—1.200,1.220—1.275和1.280—1.320三个区间;采用升(降)半梯形分布的隶属度函数建立水稻高光谱d5分维数与其污染胁迫水平的数学模型,并进行了模型精度检验,其判别精度大于90%。小波变换、分形分析和模糊数学三者相结合有效地实现了光谱弱信息提取、度量及建模,达到水稻重金属污染胁迫状况监测的目的,也为作物其他环境胁迫弱信息的动态识别与精确度量提供借鉴意义。
The lead pollution level in rice was diagnosed by studying the fractal dimension of high frequency spectral components of rice under Pb stress. According to the data of ASD hyperspectral data obtained from rice canopy in the experimental area and the data of heavy metal contents obtained from the soil simultaneously, the “Db5” mother wavelet in Daubechies wavelet series was used to decompose the rice in the range of 350-1300 nm to obtain the fifth layer height Frequency component (d5). The fractal dimension of d5 was calculated by box-dimensional method. Finally, a mathematical model of fractal dimension of d5 and pollution stress level was established by fuzzy mathematics. The results showed that: d5 can effectively detect the weak spectral information of lead pollution stress and achieve the separation of hyperspectral signals at different levels of pollution; the relative interannual change rate of d5 fractal dimension at the same pollution level is less than 4%; different pollution levels The discrimination degree of rice is 86%, 75% and 91.7%, respectively, in the three intervals of 1.160-1.200, 1.220-1.275 and 1.280-1.320, respectively. The mathematical model of d5 fractal dimension of hyperspectral rice and its pollution stress level was constructed by membership function of half trapezoidal distribution of ascending (descending). The accuracy of the model was tested and the accuracy of the model was more than 90%. The combination of wavelet transform, fractal analysis and fuzzy mathematics can effectively extract, measure and model the spectral weak information, and achieve the purpose of monitoring heavy metal pollution in rice. It also provides a dynamic identification and precise measure of weak information of other environmental stresses in crops Provide reference.