Abstract

Long-term near-surface soil moisture (SM) data can be obtained on a regional scale through microwave remote sensing. Therefore, to quantitatively analyze the accuracy of multisource remote sensing–based observation products, improve the retrieval algorithm, and effectively use in terminal environments, a standardized comprehensive evaluation is imperative. The SM data obtained by the China Meteorological Administration and Ministry of Water Resources were used as reference data to verify the performance of six passive microwave remote sensing–based SM products from the SMOS, SMAP, GCOM-W, FY-3B, and FY-3C satellites in Hunan province, China. These data were also used to analyze the effects of topographical, land cover, and meteorological factors on SM retrieval accuracy. Results show that SMAP shows the best overall performance in Hunan province; furthermore, it exhibits stable accuracy and is not easily affected by environmental factors. The FY series of satellite products shows the worst performance, and some grid remote sensing data are negatively correlated with the ground measurement data. AMSR2 possesses the largest amount of data and the largest deviation, and only this product exhibits significant differences with the fluctuation trend of the measured SM and precipitation. Passive microwave detection technology presents the best performance in the central part of Hunan province and the largest bias in the Dongting Lake area. SMOS-L3 and SMOS-IC, two products of the same satellite, show the lowest bias but present differences in the SM fluctuation range, orbital accuracy, as well as dry or wet bias. Furthermore, FY-3B and FY-3C, two satellites belonging to the same series, exhibit excellent consistency in performance. The evaluation results and accuracy variation between products as well as other factors identified in the study provide a baseline reference for improving the retrieval algorithm. This study provides a quantitative basis for developing improved applications of passive microwave SM products.

Highlights

  • Soil moisture (SM) is a critical variable that links the atmospheric system and terrestrial ecosystem and is an important parameter of climate change

  • Remote sensing measurements are obtained using various microwave sensors (Table 1) and the in situ measurement data are obtained from the ground observation stations by China Meteorological Administration (CMA) and Ministry of Water Resources (MWR)

  • The CMA soil moisture (SM) data are mainly used for agrometeorological operations, while the MWR observation data are mainly used for hydrological monitoring

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Summary

Introduction

Soil moisture (SM) is a critical variable that links the atmospheric system and terrestrial ecosystem and is an important parameter of climate change. The ground observation data are authentic and accurate but limited owing to the number of stations and the representativeness of singlepoint observations. They cannot meet the demand of SM data acquisition in a wide spatial range. Satellite data in the microwave wavelength region show excellent potential for SM estimation because of their penetration capability (Koley and Jeganathan, 2020). They are conventionally used in SM detection because their detection capability is unaffected by weather conditions and they can provide all-weather global observation data with long time series

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