Spatial averages of in situ measurements versus remote sensing observations: a soil moisture analysis

被引：2

作者：

Sanchez, Nilda ^{[1
,2
]}

Almendra, Laura ^{[1
]}

Plaza, Javier ^{[2
]}

Gonzalez-Zamora, Angel ^{[1
]}

Martinez-Fernandez, Jose ^{[1
]}

机构：

[1] Univ Salamanca, Inst Hispano Luso Invest Agr CIALE, Salamanca, Villamayor, Spain

[2] Univ Salamanca, Fac Environm & Agrarian Sci, Salamanca, Spain

来源：

JOURNAL OF SPATIAL SCIENCE | 2022年 / 67卷 / 03期

关键词：

Soil moisture; SMOS; geostatistics; spatial resolution; validation; DUERO BASIN; TEMPORAL STABILITY; VALIDATION; SURFACE; PRODUCTS; RESOLUTION; NETWORK; SCALE;

D O I：

10.1080/14498596.2020.1833769

中图分类号：

P9 [自然地理学];

学科分类号：

0705 ; 070501 ;

摘要：

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.

引用

页码：439 / 454

页数：16

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