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Mesoscale soil moisture patterns derived from ERS data

机译:Mescale土壤湿度模式源自ERS数据

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A new approach for calculating mesoscale soil moisture maps from coarse resolution (500 m - 1 km) SAR data utilising spatially reduced ERS data is presented. The processing of the radar data is described which includes a correction for the impact ofsurface roughness, plant water content and soil texture upon of the backscatter intensity. First, the portion of the pixel which does not provide soil moisture information (forest, built-up areas, water) is corrected, then the corrected backscatter intensity is normalised to a reference landuse (cereals). The required landuse map was derived from LANDSAT data. However, these landuse classes which must be distinguished to account for differences in surface roughness and plant water content, may also bederived from AVHRR spectro-temporal unmixing. Using model results and measurements together with the landuse map, the impact of the plant water content was corrected. Finally, the soil texture was taken into account to calculate the mesoscale surface soil moisture. The resulting soil moisture was validated quantitatively using ground truth measurements. A qualitative validation of the spatial patterns was carried out through by comparison of the calculated soil moisture with precipitation patterns. A good agreement was found between ground based and satellite derived soil moisture (RMSQ < 5 VOL percent).
机译:提出了一种新方法,用于计算粗糙分辨率(500 m - 1 km)SAR数据的MESCHELE土壤湿度图利用空间减小的ERS数据。描述了雷达数据的处理,其包括对反向散射强度的影响,植物水含量和土壤纹理的冲击的校正。首先,不提供土壤湿度信息(森林,内置区域,水)的像素的部分,然后将校正的反向散射强度标准化为参考土地使用(谷物)。所需的土地利用地图来自Landsat数据。然而,必须区分的这些土地使用类别,以解释表面粗糙度和植物含水量的差异,也可以从AVHRR Spectro-Temporal Imbixing掌握。使用模型结果和测量与土地使用贴图,矫正植物水含量的影响。最后,考虑了土壤纹理以计算迈尺度表面土壤水分。使用地面真理测量定量验证所得土壤水分。通过与沉淀图案的计算出的土壤水分进行比较来进行空间模式的定性验证。基于地面和卫星衍生的土壤水分(RMSQ <5 Vol%)之间发现了一个良好的一致。

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