干旱地区农业研究
榦旱地區農業研究
간한지구농업연구
AGRICULTURAL RESEARCH IN THE ARID AREAS
2013年
4期
187-192,199
,共7页
龟裂碱土%光谱特征%碱化信息
龜裂堿土%光譜特徵%堿化信息
구렬감토%광보특정%감화신식
Takyr Solonetzs%characteristic reflectance%alkalization information
以宁夏银北地区典型龟裂碱土为研究对象,表层土壤光谱反射率选择平滑、倒数等7种数据处理方式,采用全回归、逐步回归和偏最小二乘三种回归方法,分析龟裂碱土光谱特征,筛选对土壤pH值和ESP的敏感波段,建立龟裂碱土碱化信息的预测模型。结果表明:龟裂碱土的光谱反射曲线属于缓斜型;土壤表层反射率与土壤pH值和ESP在研究波段内均呈极显著正相关关系;反射率倒数对数的一阶微分和反射率的一阶微分在特征波段范围表现较好;反射率与土壤pH值的相关性优于与土壤ESP的相关性。从拟合度和选用敏感波段的多少整体考虑,采用偏最小二乘回归来拟合土壤pH值和ESP的方程最佳,拟合度分别达到0.93和0.8367。
以寧夏銀北地區典型龜裂堿土為研究對象,錶層土壤光譜反射率選擇平滑、倒數等7種數據處理方式,採用全迴歸、逐步迴歸和偏最小二乘三種迴歸方法,分析龜裂堿土光譜特徵,篩選對土壤pH值和ESP的敏感波段,建立龜裂堿土堿化信息的預測模型。結果錶明:龜裂堿土的光譜反射麯線屬于緩斜型;土壤錶層反射率與土壤pH值和ESP在研究波段內均呈極顯著正相關關繫;反射率倒數對數的一階微分和反射率的一階微分在特徵波段範圍錶現較好;反射率與土壤pH值的相關性優于與土壤ESP的相關性。從擬閤度和選用敏感波段的多少整體攷慮,採用偏最小二乘迴歸來擬閤土壤pH值和ESP的方程最佳,擬閤度分彆達到0.93和0.8367。
이저하은북지구전형구렬감토위연구대상,표층토양광보반사솔선택평활、도수등7충수거처리방식,채용전회귀、축보회귀화편최소이승삼충회귀방법,분석구렬감토광보특정,사선대토양pH치화ESP적민감파단,건립구렬감토감화신식적예측모형。결과표명:구렬감토적광보반사곡선속우완사형;토양표층반사솔여토양pH치화ESP재연구파단내균정겁현저정상관관계;반사솔도수대수적일계미분화반사솔적일계미분재특정파단범위표현교호;반사솔여토양pH치적상관성우우여토양ESP적상관성。종의합도화선용민감파단적다소정체고필,채용편최소이승회귀래의합토양pH치화ESP적방정최가,의합도분별체도0.93화0.8367。
By using the typical Takyr Solonetzs in northern Yinchuan as research object ,seven methods were select-ed to process the reflectance data of surface soil ,and total regression ,stepwise regression and partial least squares regres-sion were adopted to analyze the spectral characteristics of Takyr Solonetzs ,with the purpose of determining the sensitive wavelengths to pH and ESP of surface soil and establishing the prediction model of alkalization information .The results show that :the reflectance curve of Takyr Solonetzs belonged to slow-oblique type ;there were significant positive correla-tions between the reflectance and pH as well as ESP of surface soil ;the methods of reciprocal ,first-order differential of reciprocal logarithmic and first-order differential of reflectance were relatively good in the characteristic wavelength range ;and the relativity between reflectance to pH was higher than that to ESP .Considering both the fitting degree and the quantity of sensitive wavelengths ,partial least squares regression was the best method to estimate pH and ESP of surface soil ,whose fitting degree were 0 .93 and 0 .8367 respectively .