论文部分内容阅读
土壤水分在干旱地区生态系统中起着重要的作用,同时土壤含水量是确定土壤干旱的重要参数。通过分析野外和室内实测土壤发射率光谱特征参数与含水量之间的关系,采用光谱特征分析参数提取反演土壤含水量的最佳敏感波段,发现波长在9.480 2~9.790 1μm土壤含水量对其发射率最为敏感。根据最佳敏感波段的范围,模拟MODIS,ASTER,HJ-1B卫星的热红外波段,对波段及波段比值与土壤含水量进行回归分析,得出波段比值的线性模型可有效地反演出土壤的含水量。然后对该模型进行验证分析,确定模拟ASTER卫星传感器的12和14两个热红外波段的发射率比值与土壤含水量的线性关系,其反演精度更高。建立了适合研究区的土壤热红外发射率与含水量之间的反演模型。
Soil moisture plays an important role in arid area ecosystems, and soil moisture content is an important parameter to determine soil drought. By analyzing the relationship between spectral parameters of soil emissivity and water content in field and laboratory, the best sensitivity band of soil moisture content was extracted by using spectral characteristic analysis parameters. The results showed that the soil moisture content of 9.480 2 ~ 9.790 1μm Emissivity is the most sensitive. According to the range of the best sensitive band, the thermal infrared bands of MODIS, ASTER and HJ-1B satellites were simulated, and the regression analysis of band and band ratios and soil moisture content showed that the linear model of band ratio could effectively retrieve the content of soil Water volume. Then, the model is validated and analyzed to determine the linear relationship between the emissivity ratio of 12 and 14 thermal infrared bands simulated by ASTER satellite sensor and the soil water content, and the inversion accuracy is higher. The inversion model between soil thermal infrared emissivity and water content was established for the study area.