SOMOSPIE

SOMOSPIE (Soil Moisture Spatial Inference Engine) consists of a Jupyter Notebook and a suite of machine learning methods to process inputs of available coarse-grained soil moisture data at its native spatial resolution. Features include the selection of a geographic region of interest, prediction of missing values across the entire region of interest (i.e., gap-filling), analysis of generated fine-grained predictions, and visualization of both predictions and analyses.

Aug 27 2025
Latest Release SOMOSPIE Version 1.6 (01 May 2025)
Pegasus Version No version information available
Dependencies No dependencies information available
License BSD 3-Clause "New" or "Revised" License
GitHub Repository https://github.com/TauferLab/SOMOSPIE
Topics data-driven-decisions  machine-learning  remote-sensing  soil-moisture  

Contributors