SOMOSPIE: A modular
SOil MOisture SPatial Inference Engine
based on data-driven decisions

Funded by the National Science Foundation (NSF) under grant numbers 1724843, 2103845, 2103836, 2138811, and 2334945

GEOtiled: A Framework for Scalable
Terrain Parameter Computation

Funded by the National Science Foundation (NSF) under grant numbers 1724843, 2103845, 2103836, 2138811, and 2334945

About SOMOSPIE

SOMOSPIE is a modular SOil MOisture SPatial Inference Engine that allows Earth scientists to address the coarse-grained resolution and spatial information gaps associated with satellite data. The modular components of SOMOSPIE consists of:
Input of available satellite data at its native spatial resolution.
Selection of a geographic region of interest.
Prediction, of missing values across the entire region of interest (i.e., gap-filling) and at finer-grained resolution.
Analysis and visualization of generated predictions.

SOMOSPIE and FAIR

SOMOSPIE supports reproducibility, explainability, and portability of results. Its new features allow users to:
Deploy container technology on cloud platforms to perform rapid data movement and achieve portability.
Collect workflow execution's record trails to enable data traceability and results explainability.
Ready to dive in? Join us and explore the full power of our software, data, and documentation! Discover more here:

About GEOtiled

GEOtiled is a modular workflow that allows the rapid computation of terrain parameters (e.g., slope, aspect, hillshade) from Digital Elevation Models (DEMs) by leveraging data decomposition and parallel processing. GEOtiled allows:
Download available DEM data from the United States Geological Survey (USGS) webpage.
Over 15 different computable terrain parameters.
Generation of terrain parameters using either the GDAL or SAGA library.
Visualization of generated results.

GEOtiled and FAIR

GEOtiled supports reproducibility, explainability, and portability of results. Its new features allow users to:
Index their data in easily searchable repositories.
Access public platforms such as GeoTIFF and Shapefile.
Operate common geospatial formats for easy use on other software or systems.
Document data curation along with the organization and content of files.
Power up your projects! Tap into our software, data sets, and detailed docs now:

Recent Publications

Gabriel Laboy, Ian Lumsden, Jack Marquez, Kin Wai NG Lugo, Rodrigo Vargas, and Michela Taufer. A Modular, Cross-Platform Toolkit for High-Resolution Terrain Parameter Analysis. In Proceedings of the 21st IEEE International Conference on eScience (eScience), Chicago, IL, USA, September 2025. IEEE Computer Society. (Acceptance Rate: 33/98, 33.6%).

@inproceedings{laboy2025modular,
author = {Gabriel Laboy and Ian Lumsden and Jack Marquez and Kin Wai NG Lugo and Rodrigo Vargas and Michela Taufer},
title = {A Modular, Cross-Platform Toolkit for High-Resolution Terrain Parameter Analysis},
booktitle = {\textit{Proceedings of the 21st IEEE International Conference on eScience (eScience)}},
address = {Chicago, IL, USA},
month = {September},
year = {2025},
publisher = {IEEE Computer Society},
url = {MISSING},
doi = {MISSING}
}

Gabriel Laboy, Paula Olaya, Jack Marquez, Michael Sutherlin, Rodrigo Vargas, and Michela Taufer. Advancing the GEOtiled Framework Through Scalable Terrain Parameter Computation. In Proceedings of the 34th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), pages 1–2, Notre Dame, IN, USA, July 20–23 2025. ACM. (Short Paper).

@inproceedings{laboy2025advancing,
author = {Gabriel Laboy and Paula Olaya and Jack Marquez and Michael Sutherlin and Rodrigo Vargas and Michela Taufer},
title = {Advancing the GEOtiled Framework Through Scalable Terrain Parameter Computation},
booktitle = {\textit{Proceedings of the 34th International Symposium on High-Performance Parallel and Distributed Computing (HPDC)}},
pages = {1--2},
address = {Notre Dame, IN, USA},
month = {July 20--23},
year = {2025},
publisher = {ACM},
url = {MISSING},
doi = {MISSING}
}

Befikir Bogale, Ian Lumsden, Dalal Sukkari, Dewi Yokelson, Stephanie Brink, Olga Pearce, and Michela Taufer. Surrogate Models for Analyzing Performance Behavior of HPC Applications Using RAJAPerf. In Proceedings of the International Conference on Computational Science (ICCS), page 1–8, Singapore, July 7–9 2025. Springer. [link]

@inproceedings{bogale2025surrogate,
author = {Befikir Bogale and Ian Lumsden and Dalal Sukkari and Dewi Yokelson and Stephanie Brink and Olga Pearce and Michela Taufer},
title = {Surrogate Models for Analyzing Performance Behavior of HPC Applications Using RAJAPerf},
booktitle = {\textit{Proceedings of the International Conference on Computational Science (ICCS)}},
pages = {1--8},
address = {Singapore},
month = {July 7--9},
year = {2025},
publisher = {Springer},
url = {https://doi.org/10.1007/978-3-031-97635-3_39},
doi = {doi.org/10.1007/978-3-031-97635-3_39}
}

Paula Olaya, Sophia Wen, Jay Lofstead, and Michela Taufer. PerSSD: Persistent, Shared, and Scalable Data with Node-Local Storage for Scientific Workflows in Cloud Infrastructure. In Proceedings of the 2024 IEEE International Conference on Big Data, Washington DC, US, December 2024. IEEE Computer Society. (Acceptance Rate: 600/124, 18.8%). [link]

@inproceedings{olaya2024perssd,
author = {Paula Olaya and Sophia Wen and Jay Lofstead and Michela Taufer},
title = {PerSSD: Persistent, Shared, and Scalable Data with Node-Local Storage for Scientific Workflows in Cloud Infrastructure},
booktitle = {\textit{Proceedings of the 2024 IEEE International Conference on Big Data}},
address = {Washington DC, USA},
month = {December},
year = {2024},
publisher = {IEEE Computer Society},
url = {https://doi.org/10.1109/BigData62323.2024.10826021},
doi = {10.1109/BigData62323.2024.10826021}
}

Discover the latest breakthroughs powered by this software! Check out our publications:
SOMOSPIE Publications GEOtiled Publications