土壤水分遥感监测研究进展

土壤水分是陆地表面参数化的一个关键变量。土壤水分含量随时空的转换而变化,在地-气界面间物质、能量交换中起着重要的作用,是农作物生长发育的基本条件和农作物产量预报的重要参数。遥感技术具有大面积同步观测,时效性、经济性强的特点,为大面积动态监测土壤水分提供了可能。总结了近年来国内外遥感监测土壤水分理论、方法的发展和应用,介绍了目前几种比较成熟和广泛应用的土壤水分遥感监测方法与模型,对比分析了各种监测方法的优缺点,指出了土壤水分遥感监测方法存在的不足,指明了今后发展的方向,展望了土壤水分遥感监测方法的发展趋势。

Progress of soil moisture monitoring by remote sensing

Soil moisture is a key variable of land surface parameters. Soil water content variates spatially and temporally, and plays an important role in environmental elements and energy exchanges between earth and atmosphere. It is a basic indicator of crop growing and crop yield forecast, and also an important parameter in numerical weather-prediction model that lead to efficient forecasting improvement in the physics of land surface processes on regional or global scales. However, it is very difficult to obtain the soil moisture parameter by ground measurement in both temporally and spatially, especially at large spatial scales. With the development of remote sensing techniques during the last decades, it has been gradually concerned as one of the best efficient methods to retrieve soil moisture parameter. With the features of observing large area synchronously, temporally, and economically, remote sensing technique makes dynamic soil water monitoring possible at large scales. There are four objectives within this paper about soil moisture research. Firstly, it summarized systematically development and applications of remote sensing in monitoring soil moisture, mainly including Visible, Near-Infrared, Thermal infrared remote sensing and Microwave remote sensing. Secondly, it detailedly introduced present models and methodologies that extensively used for soil moisture monitoring by remote sensing, including the following Spectrum reflectivity method, Thermal inertia model, Crop water stress index, Vegetation index, Microwave remote sensing models and Hyper-spectral remote sensing model. Next, it comparatively analyzed advantages and disadvantages of all remote sensing methods in monitoring soil moisture, and pointed out shortages with very one remote sensing method. Spectrum reflectivity method is only applied in the specific area of flat terrain, single landform and a typical composition soil; Thermal inertia method is more suitable for bare soil and low vegetation coverage, and vegetation index, crop water stress index for higher coverage region; Temperature-vegetation method can effectively overcomes the influence of soil background and more accurately quantitative retrieves soil moisture in no-completion coverage region; Microwave remote sensing has a solid physical foundation for monitoring with high precision, though it still remains a serious challenge and some difficulties on how to eliminate impacts of the vegetation cover and surface roughness to the inversion of soil moisture. Finally, the prospect of remote sensing for soil moisture retrieval is discussed with the development of remote sensing technique, as well as some research directions in the future. It is very difficult for monitoring soil moisture, because of the complexity of plant-soil-water system. At the same time, various models and methods are only used efficiently in appropriate seasons and area. Parameters of models are heavily affected by geographical restrictions, not extended to the whole country. There, there are limitations on soil moisture retrieval by use of only one single method of microwave, visible-near infrared-thermal infrared, vegetation index. It is an effective way to get higher accuracy of data by integrated use of optical/near-infrared and microwave remote sensing, and is a trend to monitoring soil moisture quickly and efficiency at large scales in the future.