High-resolution soil moisture mapping in northern boreal forests using SMAP data and downscaling techniques

Jääskeläinen, Emmihenna; Luoto, Miska; Putkiranta, Pauli; Aurela, Mika; Virtanen, Tarmo

doi:10.5194/hess-29-6237-2025

Articles | Volume 29, issue 21

https://doi.org/10.5194/hess-29-6237-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-29-6237-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 29, issue 21

Research article

|

13 Nov 2025

Research article |

| 13 Nov 2025

High-resolution soil moisture mapping in northern boreal forests using SMAP data and downscaling techniques

Emmihenna Jääskeläinen, Miska Luoto, Pauli Putkiranta, Mika Aurela, and Tarmo Virtanen

Data sets

Data for "High-resolution soil moisture mapping in northern boreal forests using SMAP data and downscaling techniques" by Jääskeläinen et al. Emmihenna Jääskeläinen et al. https://doi.org/10.57707/fmi-b2share.f8c5bef87fc1489885206959839e9579

Short summary

The challenge with current satellite-based soil moisture products is their coarse resolution. Therefore, we used machine-learning model to improve spatial resolution of well-known SMAP (Soil Moisture Active Passive) soil moisture data, by using in situ soil moisture observations and additional weather data and vegetation properties. Comparisons against independent data set show that the model estimated soil moisture values have better agreement with in situ observations compared to other SMAP-related soil moisture data.