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不同核函数支持向量机和可见-近红外光谱的多种植被叶片生化组分估算 被引量:13
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作者 陈方圆 周鑫 +4 位作者 陈奕云 王奕涵 刘会增 王俊杰 邬国锋 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2019年第2期428-434,共7页
氮、磷、钾元素是植物有机质的重要生化组分,准确估算其含量对监测管理植被的新陈代谢和健康状况具有重要意义。可见-近红外光谱结合多种建模方法已被用于植被生化参数的监测,其中支持向量机回归方法被证明能够较好拟合反射光谱和植被... 氮、磷、钾元素是植物有机质的重要生化组分,准确估算其含量对监测管理植被的新陈代谢和健康状况具有重要意义。可见-近红外光谱结合多种建模方法已被用于植被生化参数的监测,其中支持向量机回归方法被证明能够较好拟合反射光谱和植被生化参数之间的非线性关系,而选取适当的核函数是其成功的关键。以宜兴地区水稻、玉米、芝麻、大豆、茶叶、草地、乔木和灌木等八种植被叶片样本为研究对象,分析比较基于径向基核函数、多项式核函数和S形核函数的支持向量回归模型估算叶片氮、磷、钾元素含量的能力。利用一阶微分变换、标准正态变量变换和反对数变换对叶片可见-近红外光谱进行预处理,运用bootstrapping法生成1 000组校正集和验证集,分别建立基于三种核函数的支持向量回归估算模型,以决定系数(R2)和相对分析误差(RPD)的均值作为评价指标。结果显示,结合一阶微分和反对数变换光谱,采用径向基核函数模型对氮、钾元素估算精度最高(氮:平均R2=0.64,平均RPD=1.67;钾:平均R2=0.56,平均RPD=1.48),结合一阶微分变换光谱,采用径向基核函数模型对磷元素估算精度最高(磷:平均R2=0.68,平均RPD=1.73)。研究表明,结合不同预处理的可见-近红外光谱,基于径向基核函数的支持向量回归模型具有较好的估算多种植被叶片生化组分含量的潜力。 展开更多
关键词 核函数 支持向量机 可见-近红外光谱 生化组分
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Application of Geochemistry and VNIR Spectroscopy in Mapping Heavy Metal Pollution of Stream Sediments in the Takab Mining Area, NW of Iran
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作者 Parisa PIROOZFAR Samad ALIPOUR +1 位作者 Soroush MODABBERI David COHEN 《Acta Geologica Sinica(English Edition)》 SCIE CAS CSCD 2018年第6期2382-2394,共13页
This study considered the possibility of using visible and near infrared(VNIR) spectral absorption feature parameters(SAFPs) in predicting the concentration and mapping the distribution of heavy metals in sediments of... This study considered the possibility of using visible and near infrared(VNIR) spectral absorption feature parameters(SAFPs) in predicting the concentration and mapping the distribution of heavy metals in sediments of the Takab area. In total, 60 sediment samples were collected along main streams draining from the mining districts and tailing sites, in order to measure the concentration of As, Co, V, Cu, Cr, Ni, Hg, Ti, Pb and Zn and the reflectance spectra(350–2500 nm). The quantitative relationship between SAFPs(Depth500 nm, R610/500 nm, R1344/778 nm, Area500 nm, Depth2200 nm, Area2200 nm, Asym2200 nm) and geochemical data were assessed using stepwise multiple linear regression(SMLR) and enter multiple linear regression(EMLR) methods. The results showed a strong negative correlation between Ni and Cr with Area2200 nm, a significant positive correlation between As and Asym2200 nm, Ni and Co with Depth2200 nm, as well as Co, V and total values with Depth500 nm. The EMLR method eventuated in a significant prediction result for Ni, Cr, Co and As concentrations based on spectral parameters, whereas the prediction for Zn, V and total value was relatively weak. The spatial distribution pattern of geochemical data showed that mining activities, along with the natural weathering of base metal occurrences and rock units, has caused high concentrations of heavy metals in sediments of the Sarough River tributaries. 展开更多
关键词 heavy metals SAFPs vnir spectroscopy multiple linear regression Takab Iran
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