No DOI is live yet. Below is the structure every artifact will follow, plus the planned anchor preprint. Method explainers already public: Sentinel-1 SAR, sparse ground truth, flux model, uncertainty quantification.
Preprints
Uncertainty propagation from sparse water-level sensors to plot-level methane estimates in smallholder rice using Sentinel-1 C-band backscatter
Status: Draft for Q4 2026. Target venues: arXiv (eess.SP / physics.ao-ph) or EGUsphere. Patent counsel sequencing before public posting.
Abstract (draft): We describe error propagation from a statistically designed sparse network of in-field water-level sensors through Sentinel-1 C-band flood classification to plot-level methane estimates under monsoon cloud, and report validation against chamber and sensor holdouts in an Indian district.
Cite this work (placeholder)
@techreport{oryzalabs_uncertainty_2026,
title = {Uncertainty propagation from sparse water-level sensors to plot-level methane estimates in smallholder rice using Sentinel-1 C-band backscatter},
author = {{Oryza Labs}},
institution = {Praesidio Care},
year = {2026},
note = {Preprint forthcoming — DOI pending}
}Datasets
Each release will include: Zenodo DOI, CC BY 4.0 licence, file listing, Schema.org Dataset JSON-LD, and a cite block. Planned first release: plot-level flooding classification for one validation district, one full growing season, with co-located sensor ground truth and per-plot uncertainty fields.
No public DOI yet — placeholder for Zenodo entry
Validation reports
Versioned PDFs with dates will appear here as ground calibration completes (Q1 2027 onward). Reports will state what was measured, what was inferred, and what failed.
Code
Public repositories will link from github.com/oryzalabs when the organisation and first repo are live. Until then, treat processing claims as pre-release.