Temporal Variability of Uncertainty in Pixel-Wise Soil Moisture: Implications for Satellite Validation

Abstract

Abstract:In-situ soil moisture was widely used to validate and calibrate the satellite-retrieved data of different footprints. However, it contained unavoidable uncertainty when used as spatial representative. This paper examined the uncertainty in pixel-wise soil moisture designed for satellite validation in the HiWATER project. Two in-situ data sets were used for the examination, which were carefully designed to capture the spatial heterogeneity of soil moisture at different scales. Our results indicated that the pixel-wise uncertainty increased with increasing extent. At a small area, the uncertainty referred to the natural spatial variability of in-situ soil moisture. With respect to a large area, sampling error of spatial soil moisture played an important role, particularly of dry condition. Temporally, the uncertainty was higher during rainfall than that after then. It suggested that in-situ soil moisture could be more spatially representative at a small area after rainfall, valuable for satellite validation. Uncertainty was correlated to soil moisture. It was strongly correlated to spatial mean at a small scale and was to the spatial pattern at a large scale. Results of this study offered some clues to examine the uncertainty of in-situ soil moisture for satellite validation.

A Multilayer Soil Moisture Dataset Based on the Gravimetric Method in China and Its Characteristics

“…The SM strongly depends on soil types, observation timing, and land cover, as well as on surface climate and environmental conditions; thus, it dramatically varies with space and time (S. U. et al 2014;Feng et al 2015). In the past two decades, SM point measurements at various numbers of Chinese stations have been analyzed and adopted in different applications (e.g., Zhang et al 2004;Li et al 2005;Nie et al 2008;Yang et al 2013;Feng et al 2015).…”

“…et al 2014;Feng et al 2015). In the past two decades, SM point measurements at various numbers of Chinese stations have been analyzed and adopted in different applications (e.g., Zhang et al 2004;Li et al 2005;Nie et al 2008;Yang et al 2013;Feng et al 2015). For instance, Li et al (2005) used data from 40 Chinese stations from 1981 to 1991 to evaluate the three reanalysis products from ERA-40, NCEP-NCAR, and NCEP-DOE.…”

“…Increasing researches noticed that the spatial inconsistence between soil moisture and precipitation. For example, Feng and Zhang (2015) pointed out that global soil moisture varies with the climate zones. Over arid and semiarid regions, precipitation exerts the controlling role on the SM (Seneviratne et al 2010;Wang and Zeng 2011).…”

Evaluation of SMOS, SMAP, AMSR2 and FY-3C soil moisture products over China

“…The problem of authenticity being affected by surface heterogeneity has become a major research issue because of the low resolution of passive microwave remote sensing data [ 31 ]. Information entropy indicates the extent of uncertainty or randomness in a variable, and it was used in our analysis of the effects of surface heterogeneity on SM data accuracy for the four products.…”

Spatial-Temporal Analysis of Environmental Data of North Beijing District Using Hilbert-Huang Transform

“…Adequate understanding of these field environment data as functions of space and time is necessary for developing empirical models of soil-vegetation-atmosphere transfer [4]; also it could help in expert system design of precision agriculture [5] and quantified the uncertainty caused by in-situ method for satellite remote sensing validation and calibration [6]. Given measurement data, it is still a challenge to understand and characterize the observations across multiple space-time scales.…”