Lab10YR — Soil Intelligence

Google Earth Engine and the Soil Carbon Monitoring Problem

New capabilities in Google Earth Engine, using decades of Landsat imagery and KSSL validation, make national-scale soil organic carbon monitoring achievable, offering key data for carbon markets and regenerative agriculture, though underlying soil fragility in arid regions presents inherent challenges to long-term carbon retention.

SSURGO data coverage — 100 map units
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315K
SSURGO map units nationwide —
each queryable via SDA API in seconds
Google Earth Engine and the Soil Carbon Monitoring Problem — Lab10YR data visualization

A bare soil composite, built from 20 years of Landsat imagery in Google Earth Engine, isolates spectral signals correlating with soil organic carbon (SOC) at 30-meter resolution. The Kellogg Soil Survey Laboratory (KSSL) provides laboratory validation. This capability makes a national carbon change map computationally achievable, transforming carbon project development and precision agriculture.

SOC profoundly influences bare soil's spectral reflectance. Organic matter absorbs more light in the visible and near-infrared regions, yielding a distinct spectral signature. Time series analysis of satellite images filters transient noise, isolating the consistent soil signal. Google Earth Engine supplies petabyte-scale power to process decades of Landsat data at 30-meter resolution.

What the Data Shows

The accuracy of these remote sensing models demands strong ground truth. The National Cooperative Soil Survey's KSSL database contains precise lab measurements of soil properties, including organic carbon. KSSL data, accessed via Soil Data Access (SDA) through `kssl.lab_major` and `kssl.lab_chemical`, enables calibration and validation of spectral indices against actual measured SOC.

Monitoring soil carbon offers opportunities for carbon credit verification, ESG reporting, and optimizing regenerative agriculture. However, carbon sequestration's permanence is not solely dependent on monitoring; soil stability is critical. Fragile soils, prevalent in arid regions, complicate carbon retention.

Soil Carbon Prediction Accuracy — Spectral vs. Traditional Methods

R-squared values for soil organic carbon prediction by method · KSSL spectral library + literature
Source: R-squared values for soil organic carbon prediction by method · KSSL spectral library + literature
State / RegionR² — SOC Prediction
UAV Multispectral (5cm)0.87%
Vis-NIR-SWIR Lab Scan0.84%
Sentinel-2 Bare Soil0.71%
Landsat Composite0.63%
Field Morphology0.55%
Grid Sampling0.48%
Source: SSURGO national dataset · 315,543 map units rated

The Regional Picture

SSURGO survey coverage (% of land area with tabular data) — top states

Nevada's soils average a Fragile Soil Index (FSI) of 0.521, highest in the continental U.S., with 80% of map units rated Fragile or higher. These desert soils, low in organic matter, offer minimal cohesion. Arizona follows with an average FSI of 0.495, with 77% of map units Fragile or higher, reflecting conditions prone to aggregate breakdown. Overall, 13.3% of rated SSURGO map units carry a Fragile or higher FSI, concentrated in the Southwest.

Utah's soils, averaging an FSI of 0.41 (62% of map units Fragile or higher), include Great Basin and Colorado Plateau soils that collapse on wetting. This impacts organic matter's physical protection within aggregates, influencing persistence. While remote sensing tracks carbon, understanding these fragility metrics, available in SSURGO via `chfrags_r`, is vital for designing resilient carbon projects that account for soil's physical vulnerability.

SSURGO Data Coverage — National Survey Completeness

% of land area with complete SSURGO tabular data · Source: USDA Soil Data Access
Iowa 100%, Illinois 100%, Ohio 99%, Indiana 99%, Kansas 98%, Nebraska 97%, Missouri 97%, Minnesota 96%
Interactive map — hover for state-level data · click to open the full risk map

What It Means in Practice

🗺 Explore the Soil Risk Map →
National SSURGO data explorer — query any county's soil map units, interpretations, and horizon data via the live SDA API.
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