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Remote Sensing of Soil Moisture

机译:土壤水分遥感

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Soil moisture is an important variable in land surface hydrology as it controls the amount of water that infiltrates into the soil and replenishes the water table versus the amount that contributes to surface runoff and to channel flow. However observations of soil moisture at a point scale are very sparse and observing networks are expensive to maintain. Satellite sensors can observe large areas but the spatial resolution of these is dependent on microwave frequency, antenna dimensions, and height above the earth’s surface. The higher the sensor, the lower the spatial resolution and at low elevations the spacecraft would use more fuel. Higher spatial resolution requires larger diameter antennas that in turn require more fuel to maintain in space. Given these competing issues most passive radiometers have spatial resolutions in 10s of kilometers that are too coarse for catchment hydrology applications. Most local applications require higher-spatial-resolution soil moisture data. Downscaling of the data requires ancillary data and model products, all of which are used here to develop high-spatial-resolution soil moisture for catchment applications in hydrology. In this paper the author will outline and explain the methodology for downscaling passive microwave estimation of soil moisture.
机译:土壤水分是土地表面水文学中的一个重要变量,因为它控制着渗入土壤并补充地下水位的水量,而不是有助于地表径流和河道流量的水量。但是,在一个点尺度上对土壤水分的观测非常稀疏,并且观测网络的维护成本很高。卫星传感器可以观察到很大的区域,但是它们的空间分辨率取决于微波频率,天线尺寸和地表高度。传感器越高,空间分辨率越低,在低高度飞行器将消耗更多的燃料。更高的空间分辨率需要直径更大的天线,进而需要更多的燃料来维持空间。考虑到这些相互竞争的问题,大多数无源辐射计的空间分辨率都在10千米以内,这对于集水区水文学应用来说太粗糙了。大多数本地应用都需要更高空间分辨率的土壤湿度数据。缩小数据规模需要辅助数据和模型产品,所有这些数据和模型产品都用于开发高空间分辨率的土壤水分,以用于水文学中的集水应用。在本文中,作者将概述和解释用于降低土壤水分的无源微波估算规模的方法。

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