利用光谱-盐分指数监测棉田土壤盐分  

Cotton Soil Salinity Monitoring Based on a Spectrum-Salt Index

作　　者：李静[1,2] 王克如[1,2] 李少昆[1,2] 陈兵[3] 肖春花[1] 王琼[3] 王方永[3] 李栓明[1,2] 赖军臣[4] 孙亚玲[1,2] 张国强[1,2] 

机构地区：[1]石河子大学绿洲生态农业重点实验室,新疆石河子832003 [2]中国农业科学院作物科学研究所/农业部作物生理生态重点实验室,北京100081 [3]新疆农垦科学院棉花研究所,新疆石河子832003 [4]新疆生产建设兵团第六师农业局,新疆五家渠市831300

出　　处：《棉花学报》2014年第6期555-562,共8页Cotton Science

基　　金：科技支撑计划(2012BAH27B04);国家自然科学基金(41161068)

摘　　要：通过对棉田土壤盐分的光谱反演研究,为土壤盐渍化遥感动态监测提供可能。利用ASD地物光谱仪测定新疆兵团第六师共青团农场盐渍化棉田土壤光谱,结合土壤化学参数分析确定反映棉田土壤盐渍化程度的敏感波段,构建最佳盐分指数对棉田土壤盐分进行监测。结果表明,随盐渍化程度（0.084~1.659 g·kg^-1）的加重,土壤光谱反射率呈上升趋势,在近红外区（1350~1850 nm）差异尤为显著,该波段范围光谱反射率与土壤盐分呈极显著相关（r=0.880^＊＊）,且对土壤盐分响应敏感,为识别盐渍化土壤的敏感波段;选择盐渍化光谱敏感波段建立了盐分指数SI1,BI,SI2,NDSI,SI3监测棉田土壤盐渍化的模型,其中SI1和BI的RMSE分别为0.151和0.149、RE为7.5%和6.3%,预测能力强,可推荐为棉田土壤盐分监测的最佳模型。We conducted remote sensing dynamic monitoring of soil salinization by soil salt-spectrum inversion in cotton fields.An ASD spectrometer was used to measure the cotton soil spectra in the Communist Youth League farm of the sixth division of the Xinjiang Production and Construction Corps.The most sensitive wave band for measuring the soil salinization degree was determined by combined analysis of spectral and soil chemistry parameters,and the best salt index for monitoring soil salt content in cotton fields was determined.The results showed that soil spectral reflectance increased（0.084-1.659 g· kg^-1） with increasing salinization degree,and the difference was more obvious in the near infrared region （1350-1850 nm）.This band range of spectral reflectance was the most sensitive wavelength for identifying salinized soil and was significantly correlated with soil salt （r =0.880^＊＊）.By selecting sensitive bands,salt index models including SI1,BI,SI2, NDSI and SI3 were constructed to monitor soil salinization.Among the models,the SI 1 and B1 salt indexes were the most accurate,with a minimum RMSE of 0.151 and 0.149,and RE of 7.5% and 6.3%,respectively.We recommend these as the best models to monitor soil salinity in cotton fields.

关 键 词：棉田 光谱-盐分指数 土壤盐渍化 监测 

分 类 号：S562[农业科学—作物学]