Researchers develop new approaches to assess spatial representativeness of soil moisture stations

A research team at the Aerospace Information Research Institute (AIR) at the Chinese Academy of Sciences has developed a new framework for globally assessing the spatial representation of soil moisture stations. Their study found that approximately 63% of existing soil moisture observation stations certainly reflect satellite pixel-scale conditions.

Published in the IEEE Transactions on Earth Science and Remote Sensing, this study provides valuable insight into optimal deployment of soil moisture sites and robust verification of satellite products.

Soil moisture is extremely important for climate systems, hydrology and agriculture. Passive microwave remote sensing is effective for large-scale monitoring, but often suffers from low spatial resolution. In contrast, ground stations provide accurate local measurements, but struggle to represent wider satellite scale conditions, complicating the verification process.

To address these issues, the researchers used extended triple collocation (e.g.) methods to assess the correlation between ground station data and satellite-scale soil moisture measurements, thereby requiring additional field data. I avoided sex.

The researchers evaluated the spatial representativeness of 322 soil moisture stations around the world. They determined that stations with ET-R values ​​above 0.7 represent satellite scale conditions. The results showed that approximately 63% of the stations achieved good spatial representativeness.

Furthermore, this study shows that station representativeness is high in surface heterogeneity affected by environmental factors such as soil texture, land cover, elevation, and vegetation, especially in areas that emerged as the most influential factor. It has been revealed that it will decline.

Additionally, researchers have introduced a new metric called “similar area ratios of sites.” This assesses how well the station’s environmental characteristics match the environmental characteristics of the surrounding area. This approach was confirmed by high-resolution (1 km) soil moisture data analysis, highlighting the effects of surface heterogeneity on soil moisture variability and station representativeness.

This new framework can be adapted to evaluate other environmental parameters and will become a valuable tool for improving remote sensing validation. The findings lay the foundation for significantly enhancing satellite-based soil moisture monitoring and improving climate monitoring, agricultural planning, and water resource management.