Yao Yuan, Ding Jian-Li, Kelimul Ardak, Zhang Fang, Lei Lei
College of Resource and Environmental Science, Xinjiang University, Urumqi 830046, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Jul;33(7):1917-21.
In the present study, the delta oasis between the Weigan River and the Kuqa River was selected as our study area. Firstly, the measured hyperspectral data related to different soil salinization extent was combined with electromagnetic induction instrument (EM38) in order to establish a soil salinization monitoring model; Secondly, by using the scaling transformation method, the model was adopted to calibrate the soil salinity index calculated from Landsat-TM images. Thirdly, the calibrated Landsat-TM images were used for the retrieval of regional soil salinity, and the retrieved data was verified based on the measured data. We found that at wavelengths of 456, 533, 686 and 1 373 nm, the interpretated data of EM38 were highly correlated with soil spectral reflectance (obtained via first order differentiation transformation of the spectra). Additionally, the soil salinity index model constructed from the combination of 456, 686 and 1 373 nm waveband was the best model among the different saliniza tion monitoring models. The authors' conclusion is that with R2 = 0.799 3 (p < 0.01), extracting the salinity information at regional scale by combining the electromagnetic and multispectral data performed better than those monitoring models with only salinity index extracted from multispectral remote sensing method (R2 = 0.587 4, p < 0 01). Our findings provides scientific bases for the future studies related to more accurate monitoring and prediction of soil salinization.
在本研究中，选取渭干河与库车河之间的三角洲绿洲作为研究区域。首先，将与不同土壤盐渍化程度相关的实测高光谱数据与电磁感应仪（EM38）相结合，以建立土壤盐渍化监测模型；其次，采用尺度变换方法，利用该模型对由Landsat-TM影像计算得到的土壤盐分指数进行校准。第三，利用校准后的Landsat-TM影像反演区域土壤盐分，并基于实测数据对反演结果进行验证。我们发现，在456、533、686和1373nm波长处，EM38的解译数据与土壤光谱反射率（通过光谱一阶微分变换获得）高度相关。此外，由456、686和1373nm波段组合构建的土壤盐分指数模型是不同盐渍化监测模型中最优的模型。作者的结论是，结合电磁和多光谱数据提取区域尺度的盐分信息，其效果（R2 = 0.799 3，p < 0.01）优于仅从多光谱遥感方法提取盐分指数的监测模型（R2 = 0.587 4，p < 0.01）。我们的研究结果为今后更准确地监测和预测土壤盐渍化的相关研究提供了科学依据。
