本文選題：土壤　切入點：模型　出處：《農(nóng)業(yè)工程學報》2017年06期

【摘要】：土壤有機質含量可見-近紅外光譜反演過程中校正集的構建策略對模型的預測精度有重要影響。以江漢平原洪湖地區(qū)水稻土為研究對象,采用Kennard-Stone(KS)法,Rank-KS(RKS)和Sample set Partitioning based on joint X-Y distance(SPXY)法,構建樣本數(shù)占總校正集不同比例的子校正集,通過偏最小二乘回歸,建立土壤有機質含量的可見—近紅外光譜反演模型。結果表明:KS法無法提高模型預測精度,但可以在保證標準差與預測均方根誤差比(ratio of performance to standard deviation,RPD)2.0的前提下減少30%的校正樣本;基于SPXY法的模型,當子校正集樣本比例為總校正集的50%時達到最佳的模型預測精度,RPD為2.557;RKS法能夠在保證預測精度的情況下(RPD2.0),最多減少總校正集70%的樣本,對應模型RPD為2.212。當校正集與驗證集的有機質含量分布相近時,能夠以較少的建模樣本達到與總校正集相近甚至更高的模型預測精度,提升土壤有機質光譜反演模型的實用性。
[Abstract]:The construction strategy of correction set in the process of visible and near infrared spectral inversion of soil organic matter content has an important influence on the prediction accuracy of the model. Taking paddy soil in Honghu area of Jianghan Plain as an object of study, the Rank-KSn RKS method and the Sample set Partitioning based on joint X-Y distance method (SPXY) are used to study the soil organic matter content in the Honghu area of Jianghan Plain. The subcorrection set with different proportion of sample number to total correction set is constructed. By partial least square regression, the visible near infrared spectral inversion model of soil organic matter content is established. The results show that the prediction accuracy of the model can not be improved by using the method of: KS. However, the calibration samples can be reduced by 30% on the premise of ensuring the ratio of standard deviation to standard deviation / RPD2.0.Based on the model of SPXY method, When the sample ratio of the subcorrection set is 50% of the total correction set, the best model prediction accuracy (RPD) is 2.557% RKS method, which can reduce the total corrected set sample by 70% under the condition that the prediction accuracy is guaranteed. The RPD of the corresponding model is 2.212. When the distribution of organic matter content between the calibration set and the verification set is similar, the model prediction accuracy can be achieved with less modeling samples and even higher than the total correction set, and the practicability of the soil organic matter spectral inversion model can be improved.
【作者單位】： 武漢大學資源與環(huán)境科學學院;土壤與農(nóng)業(yè)可持續(xù)發(fā)展國家重點實驗室;武漢大學蘇州研究院;武漢大學地球空間信息技術協(xié)同創(chuàng)新中心;武漢大學教育部地理信息系統(tǒng)重點實驗室;湖泊與環(huán)境國家重點實驗室(中國科學院南京地理與湖泊研究所);湖北師范大學 城市與環(huán)境學院;浙江大學農(nóng)業(yè)遙感與信息技術應用研究所;中國科學院地理科學與資源研究所;
【基金】：國家自然科學基金項目(41501444) 蘇州市應用基礎農(nóng)業(yè)項目(SYN201422,SYN201309)
【分類號】：O657.33;S153.6

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