不同植被覆盖下土壤水分遥感监测方法的比较研究

Comparative Study on the Methods of Estimating Soil Moisture by Remote Sensing Under Different Vegetation Cover

为了研究不同植被覆盖程度下多种土壤水分遥感监测模型的适用性，提高大面积土壤水分遥感监测的可行性和精度，利用辽宁省52个气象站2008—2010年土壤相对湿度人工观测资料以及对应时段的卫星遥感资料，采用热惯量、能量指数、植被供水指数法进行土壤水分的遥感监测，在低、中、高植被覆盖条件下对比3种定量反演土壤水分的遥感模型，并与人工观测资料建立线性、指数、对数拟合。结果表明：在中低植被覆盖期，热惯量法最适合，与0～20cm的平均土壤相对湿度的对数相关最好；高植被覆盖期。能量指数法稍好于植被供水指数法，与0～10cm的平均土壤湿度的对数相关最好。

In order to research a variety of soil moisture remote sensing monitoring models under different vegetation coverage, improve the feasibility and accuracy of large area soil moisture monitoring by remote sensing, the author used the soil relative humidity artificial observation data and satellite remote sensing data in the corresponding period from 52 meteorological stations in Liaoning Province from 2008 to 2010, conducted remote sensing monitoring of soil moisture with the thermal inertia index, energy, water and vegetation index, and remote sensing model at low, medium, high vegetation cover conditions in contrast to the three quantitative retrieval of soil moisture, established linear, exponential, logarithmic and artificial observation data. The results showed that： in the low vegetation coverage period, thermal inertia method was most suitable for soil 0-20 cm, and has the best logarithmic correlation to average relative humidity; for high vegetation coverage period, energy index method was slightly better than water vegetation index method, andthe average soil moisture 0-10 cm has the best logarithmic correlation.