About us

We measure the pulse of Colombia's forests

We estimate forest carbon, deforestation, EUDR compliance and ecosystem health across Colombia with satellite data and artificial intelligence, taking traditional monitoring from months to minutes.

Our purpose

We believe no territory can be protected if it cannot be measured. Estimating forest carbon the traditional way is costly, slow, and leaves out local communities, small carbon projects, and the institutions that need to track the state of their territory.

Our purpose is to change that. Every vereda in Colombia, from Chocó to the Amazon, should have data as rigorous as that of any capital in the world, and should have it in minutes rather than months. And that data should turn into decisions, from exports that comply with European regulation to carbon projects with a verifiable baseline and communities that know the value of their forest.

33,355 veredas monitored
21 years time series 2005 to 2026
25.1 Mg C/ha mean error in aboveground biomass, 56 km blocks
5 products on the platform

How BioAurea was built

Academic research
BioAurea was born from research into carbon markets that exposed a double gap. The communities with the potential to take part have no measurement, reporting and verification (MRV) technology within reach, and the tools that already exist lack the precision Colombia needs. Hence our purpose, to build Colombian technology, made for our territory and within reach of those who care for it.
AI models
We trained three carbon models, aboveground biomass, soil carbon, and necromass, with thousands of satellite data points and records from all of Colombia since 2005, calibrated with other tropical countries. We tested more than 50,000 configurations and evaluated them against the National Forest Inventory holding out 56 km blocks from training (spatial cross-validation).
Twenty satellite sources
The models integrate more than twenty satellite data sources calibrated for the Colombian territory, with automatic monthly updates for veredas and in real time for any coordinate.
Platform in production
Today it is a platform in production covering the country's 33,355 veredas, with published data in 32,050 in the latest snapshot. The satellite carbon base is 500 meters: each estimate averages a circle of 250 m radius (19.6 ha) and the field-verified signal starts at 500 m; the 10 and 30 meter layers are used for deforestation. It all reaches the user as four products, with clear reports, analysis, alerts and monthly dashboards.

Technological features

An ensemble of machine-learning models trained on multispectral and radar satellite imagery, calibrated against IDEAM's forest inventories. It estimates the four IPCC carbon pools at the vereda scale and across the entire time series.

Multisignal satellite modeling
Fuses multiple satellite and environmental data sources (spectral, climatic, topographic, and soil), combining optical and radar signals to estimate carbon even in areas with heavy cloud cover.
Complete carbon modeling
Three independent models for the IPCC pools, aboveground biomass, soil organic carbon and necromass. Belowground biomass is derived with the IPCC ratio, and everything is reported in Mg C/ha and in CO₂ equivalent.
Deep traceability
We reconstruct the history of any plot since 2005. For veredas, an annual carbon series from 2005 to 2026 on a 500 m base. For specific coordinates, live queries for the date the user chooses. Response to weekly events has not been demonstrated.
Three integrated products
Three products on the same database: the Carbon Explorer measures carbon live at any coordinate on the chosen date; the EUDR Passport gives the deforestation verdict by plot, the crop and its land-use history since 2017, and prepares the evidence for due diligence; and the Carbon Credit Comparator cross-verifies what a project declares. The Impact Auditor and mineral prospectivity remain a private lab.

How we validate, and against whom

The accuracy of a carbon model depends entirely on how it is measured. We publish the method before the result, and we publish the comparisons we do not win.

Rule 1
Against field data, not against another model
We measure against biomass and soil carbon measured by people in plots, with a published source and DOI. Comparing one map with another map is circular.
Rule 2
By spatial blocks, never at random
Neighbouring points resemble each other. Split them at random between training and test and the result comes out inflated. Here the whole block is held out.
Rule 3
A winner only if the margin excludes chance
Every comparison carries its 95 % confidence interval. If the interval touches zero, no victory is declared even when the number is favourable.
Aboveground biomass, outside Colombia
On 335 field plots with traceable ground truth, more than 25 km from any training point and across three tropical regions, the mean error is 28.7 Mg C/ha: a tie with CTrees (29.4; difference -0.7, 95% CI -2.8 to +1.3) and better than GEDI L4B (33.0), Spawn ORNL (35.1), ESA CCI (37.2) and WHRC (39.3), as those maps are published. If every map is given the same canopy height our calibration uses, CTrees and GEDI match or lead. Measured exceptions: Mexico and vegetation below 30 Mg C/ha; dense forest is underestimated.
Soil carbon
Validated in Colombia on 556 IDEAM and IGAC points holding out 56 km blocks (rank correlation 0.59). Outside training, on 174 international profiles 5 km or farther away (WoSIS and ISCN), its error is indistinguishable from SoilGrids (mean-error difference +0.5 Mg C/ha, 95% CI -3.3 to +5.1), except in Brazil: on 299 tropical SoilData profiles, SoilGrids has less error (29.8 vs 35.7 Mg C/ha) because the model underestimates humid South American soils. The model uses SoilGrids layers as inputs.
Deadwood
On 32 international sites it ranks with a correlation of 0.55, but its mean error (2.8 Mg C/ha) does not beat predicting a constant (3.0), and the measurement unit of those ground truths is unresolved. No global deadwood map exists to compare against; in Colombia a free regional table gives 3.76 Mg C/ha of error against 3.56 for the model.

Every estimate outside Colombia carries a 90 % interval whose measured coverage is 90 % on 509 field plots (69 % in dense forest above 120 Mg C/ha). Global maps publish per-pixel uncertainty; its coverage has not been measured here. Full tables and method: October 2026 validation.

And in Colombia, against the national forest inventory

Above-ground biomass
0.79
rank correlation against 953 National Forest Inventory clusters, with 25.1 Mg C/ha of mean error versus 33.1 for GEDI L4B, 33.5 for CTrees, 35.1 for Spawn and 38.9 for ESA CCI, all with intervals that exclude zero (spatial cross-validation by 56 km blocks; not an independent validation).
Soil carbon
556
points from IDEAM and IGAC, evaluated holding out 56 km blocks, with a rank correlation of 0.59. It is the hardest pool: veredas less than 5 km apart differ by 25 Mg/ha.
Deadwood
0.73
rank correlation against 908 IDEAM plots, holding out 56 km blocks, with 3.56 Mg C/ha of mean error (R² 0.31; a free regional table gives 3.76).
Resolution
66.8 %
accuracy in telling which of two plots 500 m or more apart holds more carbon (95% CI 58.8 to 74.2; six field sites, 2,363 pairs). Chance gets 50 % and the placebo yields P below 0.0001. It does not quantify, nor resolve plots smaller than 500 m.

Beyond 500 metres the model ranks, it does not quantify. Estimates are for pre-assessment and do not replace accredited field verification.

And in Colombia, with plots the model never saw

Above-ground biomass, 52 independent plots
On 52 field plots from SiB and BioResilience, 5 km or more from any training point and measured with the same equation, the mean error is 32.0 Mg C/ha: it ties CTrees (34.6), ESA CCI (36.6) and WHRC (36.4) and beats Spawn ORNL (33.8) and GEDI L4B (47.4). Before the canopy-height adjustment it was 36.0 and tied all of them.
Dense montane forest
On 31 oak-forest plots in Huila, the Serranía de los Yariguíes and the Amazon (97 to 396 Mg C/ha), every product lands between a third and a half of the field value. BioAurea (134 Mg C/ha of error) ties CTrees and ESA CCI; Spawn and WHRC are ahead. This is the regime the model does not yet resolve.
Soil carbon
Calibrated to the scale of the National Forest Inventory. Measured on the 534 inventory plots the model did not see (spatial cross-validation with 56 km blocks), its error is 13% lower than SoilGrids: 21.5 vs 24.7 Mg C/ha (95% interval: 6% to 21% lower). The advantage rises to 27% where tree cover is low, such as pastures and savannas (interval: 10% to 41%). In studies using other measurement protocols the result is not conclusive: less error in Caquetá, a tie in the Andes and more error in the Orinoquía (20.0 vs 7.0 Mg C/ha in Vichada and Meta). Above 500 m of elevation there is not yet enough evidence either way. Legacy IGAC profiles are on a different scale and are not part of the comparison; mountain andosols above 170 remain unresolved. It uses 33 SoilGrids layers, plus one variable derived from them, among its 64 variables (including carbon concentration by depth, but not the 0 to 30 cm stock it is compared against) and adds its own satellite and climate signal, calibrated with the Colombian inventory.

Mean-error differences with 95% confidence intervals from resampling localities. Since October 2026, above-ground biomass in Colombia is adjusted by canopy height when the canopy is 10 m or taller; on low-biomass land with tall canopy the value can be about 15 Mg C/ha too high. Full table: Colombia benchmark, October 2026.

Total carbon by bioregion
The breakdown by bioregion (Pacific, Andes, Amazon, Caribbean, Orinoquia) lives on the site's main panel, where it is updated with every data cut. It was removed from here to avoid keeping two copies of the same number that could drift out of sync.
See the live panel

The plot was already farmland before 2020: the proof the EU map does not give

For the European deforestation regulation the blind spot is that shade-grown coffee has a canopy and the EU reference map marks it as forest. The EUDR Passport reviews the plot history year by year since 2017 with 10-metre imagery: whether the cover changed, which crop is there (coffee, cocoa, oil palm, timber, pasture or forest; rubber and soy are not recognised today) and whether that reading is conclusive or needs a field check. In Colombia the classifier is evaluated against official land-cover data holding out 55-kilometre blocks so no neighbouring point leaks information.

See it in the EUDR Passport →
What we do claim
In Colombia, holding out 55 km blocks, it finds 89 out of 100 coffee plots and is right 88 out of 100 times it names coffee; against official planted area by municipality the correlation is 0.89. The history since 2017 only asserts continuous agricultural use when the sources agree, and then it is right 97 out of 100.
What we do not claim
It is not a world map: it is offered in Colombia only. It does not recognise soy, rice, maize, sugarcane, rubber or cattle, and saying forest does not rule out a tree crop. Nor does it yet resolve shade-grown coffee that the EU map marks as forest: there is not enough sample to claim it.
Where we do not win
Cocoa: it finds 62 out of 100 plots. Natural forest: when it says forest it is right 52 out of 100, because coffee, cocoa and canopy plantations get confused with it. And in about 7 out of 10 plots the history answers inconclusive: it is checked in the field.

Indicative land-use attribution. It does not constitute EU-accredited verification; the legal deforestation verdict rests on Hansen and JRC, in a separate layer.

Validated with real institutions

We presented BioAurea to 104 representatives from local governments across more than 15 municipalities of eastern Antioquia and the rest of the country. This is what they answered.

71.2% raised their interest in carbon markets after seeing BioAurea
77.9% would trust a digital platform to manage carbon projects
69.2% had an immediate positive reaction to the platform
79.8% value involving strategic partners in the process
Validation study of BioAurea with municipal representatives, 2026.

Where we're headed

Environmental agency

To become the primary source of analysis and information on Colombia's ecosystems, and an official source for the media and for government, with two editorial analyses each month.

Better technology

To keep refining the models, incorporate new sensors and field data, and narrow the margin of error until we approach direct measurement.

Colombia's communities

To put data in the hands of the communities, cooperatives and smallholders who care for the forest, so they can reach fair markets with their own information.

The environment

To contribute to conservation with evidence. Every hectare measured is a hectare that can be protected, restored and defended against deforestation.

The platform is available to you

We are looking for alliances with public entities, carbon project developers, green finance, and energy operators to validate and scale the technology. Try the explorer for free, or write to us for a demonstration.

Explore the map soporte@bioaurea.org