Toward the Estimation of Surface Soil Moisture Content Using Geostationary Satellite Data over Sparsely Vegetated Area

Pei Leng,Zhao-Liang Li,Yawei Wang,Xiaoning Song,Ruixin Wang

doi:10.3390/rs70404112

Abstract

Based on a novel bare surface soil moisture (SSM) retrieval model developed from the synergistic use of the diurnal cycles of land surface temperature (LST) and net surface shortwave radiation (NSSR) (Leng et al. 2014. “Bare Surface Soil Moisture Retrieval from the Synergistic Use of Optical and Thermal Infrared Data”. International Journal of Remote Sensing 35: 988–1003.), this paper mainly investigated the model’s capability to estimate SSM using geostationary satellite observations over vegetated area. Results from the simulated data primarily indicated that the previous bare SSM retrieval model is capable of estimating SSM in the low vegetation cover condition with fractional vegetation cover (FVC) ranging from 0 to 0.3. In total, the simulated data from the Common Land Model (CoLM) on 151 cloud-free days at three FLUXNET sites that with different climate patterns were used to describe SSM estimates with different underlying surfaces. The results showed a strong correlation between the estimated SSM and the simulated values, with a mean Root Mean Square Error (RMSE) of 0.028 m3·m−3 and a coefficient of determination (R2) of 0.869. Moreover, diurnal cycles of LST and NSSR derived from the Meteosat Second Generation (MSG) satellite data on 59 cloud-free days were utilized to estimate SSM in the REMEDHUS soil moisture network (Spain). In particular, determination of the model coefficients synchronously using satellite observations and SSM measurements was explored in detail in the cases where meteorological data were not available. A preliminary validation was implemented to verify the MSG pixel average SSM in the REMEDHUS area with the average SSM calculated from the site measurements. The results revealed a significant R2 of 0.595 and an RMSE of 0.021 m3·m−3.

Highlights

The water held in the top few centimeters of the soil, namely surface soil moisture (SSM), is an essential land surface variable because it determines the partitioning of energy at the surface and impacts the associated water and energy fluxes especially over low vegetated conditions [1,2]
When fractional vegetation cover (FVC) is higher than 0.7, some of the model coefficients vary irregularly compared to the cases when FVC is lower than 0.7
Temperature and net shortwave radiation of the soil surface become extremely weak in the dense vegetation coverage (FVC > 0.7) conditions for remote sensing observations, and most of the signals are from the canopy

Summary

Introduction

The water held in the top few centimeters of the soil, namely surface soil moisture (SSM), is an essential land surface variable because it determines the partitioning of energy at the surface and impacts the associated water and energy fluxes especially over low vegetated conditions [1,2]. The SSM always plays a considerable role in various hydrological models [3,4], meteorological studies [5,6] and ecological applications [7,8]. It is a fundamental parameter in many other domains, such as the agricultural process [9,10] and carbon/nitrogen cycles [11,12]

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Conclusion