Based on the monitored data of soil pH and measured Vis-NIR reflectance on spot in Qitai oasis alkalinized area in Xinjiang, as well as comparison of the relationship between measured reflectance and soil pH and the relationship between TM reflectance and soil pH, both of the reflectance multivariate linear regression models were built to evaluate soil alkalinization level,and the model accuracy of pH fitting was discussed with error inspection of post-sample. The results showed that there is a significant positive correlation between soil pH and reflectance. With pH rising the reflectance increased concurrently. So the alkalinization soil characterized by hardening had good spectral response characteristics. Both measured reflectance and TM image reflectance had good potential ability for change detection of the alkalinization soil The pH predicting model of measured reflectance had higher accuracy and the major error was from different hardening state. If building model by TM reflectance directly,the accuracy of fitting was lower because of the vegetation information in image spectrum. With the vegetation factor removed with NDVI, the accuracy of TM predicting model was near the accuracy of measured reflectance predicting model, and both of the model levels were good.%以新疆奇台绿洲碱化土壤及其可见光/近红外光谱反射率为研究对象,通过实地定点土壤取样和光谱测量,将碱化土壤的实测反射率与同期获取的TM影像反射率相对照,分析二者与土壤pH值的关系,分别建立对土壤pH值的多元线性回归预测模型并对模型精度进行后验差检验.结果表明:研究区土壤pH值与反射率呈极显著的正相关关系,pH值增加,反射率随之增加,以板结为特征的碱化土壤对光谱具有良好的响应特性.实测反射率与影像反射率对研究区碱化土壤均具有良好的监测潜力.实测反射率预测pH值的模型精度较高,其预测精度主要受地表板结程度的影响.植被对TM反射率预测精度的影响较大,直接用TM反射率预测pH值精度较低,去除植被影响后,其预测模型等级与实测反射率预测模型等级接近,均达到良.
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