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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。
The spectral inversion of soil salinity in cotton soils may provide the potential for remote sensing monitoring of soil salinization. The spectrum of soil salinization was measured by using ASD spectrophotometer and the sensitive band reflecting the degree of soil salinization in cotton field was determined by analyzing soil chemistry parameters. The optimal salt index was constructed to monitor soil salinity in cotton field. The results showed that with the increase of salinization degree (0.084 ~ 1.659 g · kg-1), the spectral reflectance of soil showed an upward trend, especially in the near infrared region (1350 ~ 1850 nm). The spectral reflectance in this band ranged from Soil salinity was significantly correlated (r = 0.880 **) and sensitive to soil salinity, which was a sensitive band for identifying salinized soils. Salinity indices SI1, BI, SI2, NDSI, SI3 monitoring soil salinization model, in which SI1 and BI RMSE were 0.151 and 0.149, RE 7.5% and 6.3%, the ability to predict strong, it can be recommended as the best soil salt monitoring in cotton field model.