中文摘要：

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。

英文摘要：

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.