KVASIR Intelligence™

The verification library

Independent evidence for climate-smart agriculture practices under §45Z. Each article shows what satellite-based verification produces at county scale — and what it means for the facilities claiming the credit.

Documentation records what was claimed. A grower files paperwork. A platform timestamps it. An aggregator bundles it into a report. The record exists. But the record does not test whether the practice actually occurred on the specific acres, in the relevant crop year, at the intensity required by the regulation.

Verification tests what actually happened. Satellite observations — radar and optical, at 10-meter resolution — measure field-level conditions independently of any commercial relationship with the grower. No enrollment required. No self-reported records as primary proof. Where the evidence is not strong enough, acres are classified UNKNOWN and counted against the claim, not excluded from the denominator.

That distinction is not philosophical. Under proposed §45Z regulations, insufficient substantiation of upstream practices does not reduce a credit. It can eliminate it entirely. The articles below show what a defensible evidentiary standard looks like in practice — one layer at a time.

Practice verification series

Each layer addresses one satellite-verifiable practice defined under USDA’s Climate-Smart Agriculture framework. Together, they build the integrated verification stack that maps directly to §45Z carbon intensity calculations.

L1
Layer 1 — Conservation tillage
This is what verification looks like: conservation tillage at county scale

NDTI-based residue detection identifies conservation tillage practices across millions of acres. SAR corroboration resolves ambiguity in high-clay soils where optical signals alone cannot distinguish practice types.

Ohio & Iowa Census-validated
L2
Layer 2 — Cover crops
This is what verification looks like: cover crop detection through winter vegetation trajectories

Temporal vegetation signatures across fall-through-spring windows detect overwintered biomass presence and termination timing — the agronomic outcome, independent of how or when the cover crop was established.

Ohio & Iowa Census-validated
L3
Layer 3 — Crop rotation
Crop rotation is easy to claim and hard to prove

Per-year crop classification across five observation years, validated against NASS county statistics. A hierarchical architecture adapts classifier complexity to signal conditions while holding evidentiary controls constant.

Putnam & Darke counties, Ohio NASS-validated
L4
Layer 4 — The integrated stack
What happens when all three practices are measured on the same acres

Pixel-level overlay of tillage, cover crop, and rotation verification. GOLD / SILVER / BRONZE classification quantifies how many acres in a sourcing radius substantiate multiple simultaneous practices.

Putnam & Darke counties, Ohio
The economics of verification
NTJ
National Tax Journal — Submitted
Moral hazard in §45Z credit verification: why self-reported practices require independent evidence

A short paper examining the structural economics of verification in clean fuel production credits. When credit value depends on upstream practices but verification depends on self-reporting, the incentive architecture creates a textbook moral hazard. Independent satellite-based MRV is the corrective mechanism.

Manuscript #2026068 Submitted April 10, 2026

GREET calculates carbon intensity. KVASIR verifies the practices that justify those calculations.

KVASIR Intelligence™ is a product of IMAREAN, operating as CMetricsGlobal

Independent satellite-based measurement, reporting, and verification for §45Z Clean Fuel Production Credits

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The Problem
How It Works
Verification
Why KVASIR
§45Z FAQ
Request a Briefing
Aurea Effect
KVASIR Intelligence™
The Problem
How It Works
Verification
Why KVASIR
§45Z FAQ
Request a Briefing
Aurea Effect
KVASIR Intelligence™
The Problem
How It Works
Verification
Why KVASIR
§45Z FAQ
Request a Briefing
Aurea Effect