ABSTRACT

Remote sensing soil moisture (SM) has a low spatial resolution. By contrast, to validate remote SM maps, point measurements gathered from scattered in situ stations are typically used. Therefore, a single representative SM value for the entire domain is required. The simplest approach is the arithmetic mean. Here, eight upscaling methods for in situ SM based in geostatistical interpolations and physical characteristics were tested and used to validate the Soil Moisture and Ocean Salinity mission observations. Comparisons showed that the simple mean performs well and is similar to the proposed upscaling methods, while overcoming the need for ancillary data.

摘要

遥感土壤水分（SM）具有较低的空间分辨率。相比之下，为了验证远程 SM 地图，通常使用从分散的现场站收集的点测量值。因此，需要整个域的单个代表性 SM 值。最简单的方法是算术平均值。在这里，基于地质统计插值和物理特征的 8 种原位SM升级方法进行了测试，并用于验证土壤水分和海洋盐度任务观测。比较表明，简单均值表现良好，类似于提出的升级方法，同时克服了对辅助数据的需求。