geospatial
SatMAE
Stanford multispectral/temporal MAE; evaluated on fMoW RGB and fMoW Sentinel.
Levelmodel
Classgeospatial
Parametersnot in the notes
Contextnot in the notes
Released17 Jul 2022
Opennessopen weights restricted
Runs onsingle datacentre GPU
Statusactive
Identity
- Developer
- Stanford University
- Family
- not in the notes
- Released
- 17 Jul 2022 sourcesannouncement page
- Weights published
- –
- Record checked
- 10 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- dense transformer MAE ViT with temporal embedding and grouped spectral positional encodings
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- image
- Output
- image
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- open weights restricted
- Licence
- Creative Commons Attribution-NonCommercial (version not stated) sources
- Access routes
- open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- single datacentre GPU
- Footprint
- not in the notes
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
DeveloperStanford Universityuniversity, USA
Stanford Universityuniversity, USAModelSatMAEStanford University, geospatial
SatMAEStanford University, geospatialR&D TopicsEarth Observation Foundation Models
Use CasesSatellite Monitoring (Land Cover, Floods, Forests)Public SectorLand Use and Crop MappingAgricultureUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
BRIN Data Science and Information Research Center (PRSDI)Research, 10 Mar 2026Deployments of these use cases; none names this model.
BRIN Data Science and Information Research Center (PRSDI)Research, 10 Mar 2026Deployments of these use cases; none names this model.Organisations 1
Sources
- SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery arxiv.org https://arxiv.org/abs/2207.08051
- GitHub - sustainlab-group/SatMAE: Official code repository for NeurIPS 2022 paper "SatMAE: Pretraining Transformers for Temporal and Multi-S github.com https://github.com/sustainlab-group/SatMAE
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "SatMAE", https://aurion.semai.id/models/stanford-university-satmae/, records of October 2026.