基于MODIS短波红外光谱特征的土壤含水量反演

Retrieval of soil moisture based on MODIS shortwave infrared spectral feature

土壤含水量是地表干旱信息最重要的表征参量,也是定量遥感反演面临的一个挑战性课题.作者在分析MODIS短波红外第6波段和第7波段对水分变化敏感的基础上,构建了MODIS短波红外光谱特征空间,根据土壤水分在光谱特征空间中的变化规律,提出了简单实用的MODIS短波红外土壤湿度指数(Shortwave Infrared Soil Moisture Index,SIMI),并利用宁夏平原实测0～10cm平均土壤含水量数据验证了该指数.结果表明:它们之间的相关性较好,R2变化范围为0.39～0.58.此外,与TVX相比,该指数具有更高的土壤水分监测精度,证明了该方法反演区域土壤含水量的可靠性.然而,该指数没有消除混合像元的影响,仍需进一步改进与完善.

Soil moisture was one of the most important parameters characterizing surface dryness conditions.Its retrieval by quantitative remote sensing methods had been a challenging problem.By analyzing the sensitivity of shortwave infrared MODIS band 6 and band 7 to the changes of water,the MODIS shortwave infrared spectral feature space was constructed.According to the soil moisture variation in spectral feature space,a simple and practical MODIS shortwave infrared soil moisture index（SIMI） was put forward and validated using ground-measured 0～10cm averaged soil moisture of Ningxia plain.The results show that the coefficient of determination（R2） of both them varies from 0.39 to 0.58,and SIMI has higher accuracy than temperature-vegetation index（TVX） for soil moisture retrieval.These results support the reliability of this index for regional soil moisture retrieval.However,SIMI does not eliminate the impact of mixed-pixels and still needs further improvement and perfection.