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.
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 |