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Related Experiment Video

Updated: Jul 24, 2025

In Situ Soil Moisture Sensors in Undisturbed Soils

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

Chinese Soil Moisture Observation Network and Time Series Data Set for High Resolution Satellite Applications.

Chunmei Wang^1,2, Xingfa Gu^3,4, Xiang Zhou^5,6

¹Aerospace Information Research Institute, Chinese Academy of Sciences, 100094, Beijing, China.

Scientific Data

|July 1, 2023

Summary

This summary is machine-generated.

China

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Area of Science:

Earth and Environmental Sciences
Remote Sensing
Soil Science

Background:

High-quality ground observation networks are crucial for scientific research.
Accurate soil moisture and temperature data are essential for various applications.

Purpose of the Study:

Establish an automatic soil observation network in China (SONTE-China) for high-resolution satellite applications.
Measure pixel- and multilayer-based soil moisture and temperature.
Validate soil moisture products and provide data for forecasting and resource management.

Main Methods:

Deployed 17 field observation stations across diverse ecosystems in China.
Collected soil moisture and temperature data.
Analyzed temporal and spatial characteristics of the data.
Correlated Sentinel-1 C-band radar signals with observed soil moisture.

Main Results:

SONTE-China network established with 17 stations covering varied ecosystems.
Average RMSE of station-based soil moisture is 0.027 m³/m³ after calibration.
Observed data align with geographical location, seasonality, and rainfall.
Strong correlations found between Sentinel-1 radar data and soil moisture, with RMSE < 0.05 m³/m³ at specific stations.

Conclusions:

SONTE-China provides reliable soil moisture and temperature data.
The network supports validation of satellite-derived soil moisture products.
SONTE-China data are valuable for weather forecasting, flood prediction, drought monitoring, and water management.