The significance of soil properties to the estimation of soil moisture from C-band synthetic aperture radar
The significance of soil properties to the estimation of soil moisture from C-band synthetic aperture radar
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DOI：
10.5194/hess-2019-294
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发表时间：
2019-06
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影响因子：
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通讯作者：
J. Beale;Boris Snapir;T. Waine;Jonathan G. Evans;R. Corstanje
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文献类型：
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作者：
J. Beale;Boris Snapir;T. Waine;Jonathan G. Evans;R. Corstanje
摘要。土壤湿度是水文、天气和气候模型中的一个关键变量。研究的方向是通过建模、就地测量和遥感相结合来估计广大地区的土壤湿度，以提高水文和气象预报的准确性。为了监测和控制灌溉和其他农业目的，还需要捕捉当地的变化。由于土地利用、土壤性质、排水、耕作、植被、太阳辐射、气温、风、雨等因素的影响，田间和田内土壤湿度存在显著差异。以英国为例，农业用地的平均面积约为12公顷，需要的制图分辨率小于100米。基于卫星的遥感，包括使用c波段SAR（例如Sentinel-1），有可能满足这一要求，但许多当前的数据产品汇总到至少1公里的空间分辨率和/或提供相对单位或指数的土壤湿度。这两种策略都减轻了土壤水文和植被特性的野外尺度变化带来的不确定性。土壤性质和土地利用的地理空间数据集、作物建模和其他遥感技术可以提供一种替代方法，以减轻这种可变性，并允许在可接受的误差范围内生产更精细的产品。本文研究了土壤性质在c波段SAR估算土壤水分中的作用。研究表明，土壤质地、有机质含量、地表温度、土地利用和作物模型等信息是在田间尺度上成功获取土壤水分的重要输入。以前公布的数据为根据土壤性质设置土壤粗糙度参数提供了指导，随后进行了初级耕作等农业操作。除了土壤水分的反演，SAR遥感数据在提高某些土壤属性的空间分辨率和制图精度方面具有令人兴奋的潜力。
Abstract. Soil Moisture is a key variable in hydrology, weather and climate modelling. Research has been directed to the estimation of soil moisture over wide areas through a combination of modelling, in-situ measurement and remote sensing to improve the accuracy of hydrological and meteorological forecasting. For monitoring and controlling irrigation and other agricultural purposes, there is also a need to capture local variability. Significant soil moisture differences are observed between and within fields due to land use, soil properties, drainage, tillage, vegetation, solar radiation, air temperature, wind, rain and other factors. Taking the United Kingdom as an example, the average area of agricultural fields is about 12 hectares, requiring a mapping resolution of less than 100 m. Satellite-based remote sensing, including the use of C-band SAR (such as on Sentinel-1), has the potential to satisfy this requirement, but many current data products are aggregated to a spatial resolution of at least 1km and/or provide soil moisture in relative units or indices. Both strategies mitigate the uncertainties introduced by field-scale variability in soil hydrological and vegetation properties. Geospatial datasets of soil properties and land use, crop modelling and other remote sensing techniques may provide an alternative approach to mitigating this variability and allow finer scale products to be produced with acceptable errors. This paper looks at the role of soil properties in the estimation of soil moisture from C-band SAR. We show that information on the soil texture, organic matter content, surface temperature, land use and crop modelling should be important inputs to the success of retrieving soil moisture at the field scale. Previously published data provides guidance in setting soil roughness parameters, based on soil properties, following farming operations such as primary tillage. Beyond soil moisture retrieval, there is exciting potential in SAR remote sensing data to improve the spatial resolution and mapping accuracy of some soil properties.