基于热红外光谱的干旱区土壤盐分监测研究

土壤盐渍化是新疆最常见的土地退化过程，已经严重威胁到了当地的农业生产、生态稳定和经济发展。通过对渭库绿洲土壤含盐量和土壤热红外光谱分析，探讨了土壤含盐量与热红外发射率之间的定量关系。结果表明：（1）盐渍化土壤的发射率随着含盐量的变化而发生变化，当土壤盐分增加时，发射率也随之增大。（2）土壤含盐量与热红外发射率光谱数据相关性在8.5～9.5 μm波段范围内表现尤为显著，相关系数超过0.8，最高为0.90，对应波段范围9.259～9.271 μm。（3）运用回归模型一阶导数变换形式下建模效果和预测精度都是最优的，R²达到了0.899，RMSE最小为1.734。热红外光谱技术可以反演土壤含盐量，为利用热红外遥感识别土壤盐分信息提供技术支撑。

Salt content monitoring on thermal infrared emissivity in arid area

Soil salinity is a critical problem in many arid and irrigated agricultural areas. It reduces soil quality and limits the growing of crops. Monitoring soil salinity is important for controlling this problem. During the last decades, many researches aim to develop methods for assessing, mapping, and monitoring salt-affected soils using remote sensing data in combination with field measurements. The methods were classified as visual interpretation of satellite imagery, digital analysis of multispectral remote sensing data, quantitative analysis of hyperspectral imagery and integrated modeling. The main objective of this study is to assess the usefulness of the thermal infrared (TIR)emissivity for predicting salt content. For this purpose, soil samples were collected from the field for laboratory determination in this study. And spectral data was acquired from Fourier Transform spectrometer (102F), predicting model was developed using a Regression Model. The spectral results show that different salt contents in soil exhibited different emissivity. The emissivity were extremely sensitive to salt content in the 8.5-9.5 μm region, with a high correlation value (0.8 in the 9.259-9.271 μm region), holding a great promise for prediction of salt content; the Stepwise Multiple Regression Mode performed well (R²=0.899, RMSE=1.734) based on the first derivative spectral pre-treatment. The results of this study indicate that infrared thermal data provide a useful tool for predicting salt content in soil that commonly occurs in aid region.