IAGRO SAT CARIBBEAN // SATELLITE INTELLIGENCE

Eyes in the Sky,
Hands in the Soil

IAGRO SAT provides the intelligence. Farmers provide the knowledge. Together: precision agriculture at Caribbean scale.

Originally developed for Brazilian agriculture (18M+ properties, 850M ha) — the Caribbean arm launched first because the idle land crisis demanded urgent action. Brazil is a CDB non-borrowing member, enabling South-South technology transfer.

4+
SATELLITES
10m
RESOLUTION
5 days
REVISIT
Free data
COST
01 // DATA SOURCES

Four Pillars of Satellite Intelligence

All data is open-access or free-tier. No proprietary satellite contracts. No vendor lock-in.

OPTICALEuropean Space Agency

Sentinel-2 L2A

Multispectral optical imagery at 10-metre resolution with a 5-day revisit cycle. 13 spectral bands covering visible, near-infrared, and shortwave infrared. Free and open under the Copernicus programme.

10m resolution5-day revisit13 bandsFree / Copernicus
RADAREuropean Space Agency

Sentinel-1 SAR

Synthetic Aperture Radar that sees through clouds, day or night. Critical during hurricane season when optical imagery is blocked by persistent cloud cover. C-band dual polarization.

5m resolutionCloud-penetratingC-band SARDay + Night
LAND COVERESA / Copernicus

ESA WorldCover v200

Global land cover classification at 10-metre resolution. 9 land cover classes including cropland, grassland, tree cover, and built-up areas. Used as the baseline for idle land identification.

10m resolution9 classesGlobal coverageAnnual update
COMPUTEGoogle Cloud

Google Earth Engine

Planetary-scale geospatial analysis platform. Processes petabytes of satellite data without downloading a single file. Over 1,000 EECU-hours per month free for research and non-profit use.

1,000+ EECU-hours/mo freePetabyte catalogueCloud computeJavaScript + Python API
OPEN DATA NOTE

Sentinel-1 and Sentinel-2 are funded by the European Commission under the Copernicus Earth Observation Programme. All data is free, full, and open to any user worldwide. ESA WorldCover is similarly open under Creative Commons CC BY 4.0. Google Earth Engine provides free compute for research, education, and humanitarian use.

SATELLITE IMAGERY

Real Data from Barbados

These images are not mockups. They are computed from real Sentinel-2 and ESA WorldCover data for Barbados.

Barbados ESA WorldCover land cover classification at 10m resolution
ESA WORLDCOVER V200
Land Cover Classification

9 land cover classes at 10m resolution. Grassland (amber) represents idle agricultural land — 13,468 hectares identified for activation.

Barbados NDVI vegetation health map from Sentinel-2
SENTINEL-2 NDVI
Vegetation Health

NDVI (Normalized Difference Vegetation Index) computed from 55 cloud-free Sentinel-2 scenes, January to June 2024. Mean NDVI: 0.579.

Barbados NDVI time series showing vegetation health over time
TEMPORAL MONITORING
NDVI Time Series

Continuous monitoring over time reveals seasonal patterns, drought events, and the impact of interventions. Every 5 days, a new Sentinel-2 pass updates the picture.

02 // MONITORING SERVICES

Six Services, One Platform

From monthly crop health to emergency hurricane damage assessment. Every field, every 5 days.

01

Monthly Crop Health

NDVI, EVI, and SAVI vegetation indices computed per-field from Sentinel-2 imagery. Fields classified into health tiers: vigorous, moderate, stressed, or failing. Monthly reports delivered to farmers and cooperatives.

NDVIEVISAVIPer-field classificationMonthly cadence
02

Pest & Disease Early Warning

Spectral anomaly detection identifies stress patterns weeks before they are visible to the human eye. Red-edge and SWIR bands distinguish water stress from nutrient deficiency from pest damage.

Red-edge analysisAnomaly detectionStress classificationEarly warning alerts
03

Irrigation Optimization

Soil moisture estimation using the Normalized Difference Moisture Index (NDMI) from Sentinel-2. Water stress alerts trigger when moisture drops below crop-specific thresholds.

NDMISoil moisture proxyWater stress alertsCrop-specific thresholds
04

Yield Forecasting

Pre-harvest yield models trained on historical NDVI time series and harvest data. Predicts tonnage per field 4-8 weeks before harvest. Enables better logistics and market planning.

ML regression modelsNDVI time series4-8 week lead timePer-field estimates
05

Hurricane Damage Assessment

Pre/post storm comparison using SAR radar within 48 hours of landfall. Detects flooding, defoliation, and structural damage. Damage maps delivered to CDEMA and national emergency agencies.

SAR change detection48-hour turnaroundFlood mappingDefoliation index
06

Annual Land Use Report

Year-over-year change detection tracking land cover transitions. Identifies abandoned farmland returning to cultivation, urban encroachment on agricultural land, and reforestation progress.

Change detectionTransition matricesLand cover trackingAnnual reporting
03 // THE PIPELINE

From Raw Pixels to Farmer Alerts

Six stages transform raw satellite imagery into actionable intelligence delivered to the field.

1
Raw Imagery Acquisition
Sentinel-2 and Sentinel-1 scenes are ingested from the Copernicus Open Access Hub or Planetary Computer. For Barbados, 55 cloud-free Sentinel-2 scenes were processed from January to June 2024.
2
Cloud Masking & QA
SCL (Scene Classification Layer) removes clouds, cloud shadows, and cirrus. Only pixels classified as vegetation, bare soil, or water pass through. Typical cloud-free yield per scene: 60-85%.
3
Index Computation
Vegetation and moisture indices computed at native 10m resolution. NDVI = (NIR - Red) / (NIR + Red). EVI, SAVI, NDMI, and other indices derived from band math on the atmospherically corrected L2A product.
4
ML Classification
Random Forest and gradient-boosted models classify each pixel by crop type, health status, or land cover. Models trained on ground-truth data from agricultural extension services and field surveys.
5
Field-Level Aggregation
Pixel-level results are aggregated to cadastral parcels or parish boundaries. Zonal statistics (mean, median, percentiles) computed per field. Outlier detection flags anomalous fields for manual review.
6
Reports & Farmer Alerts
Structured reports generated for cooperatives, banks, and government agencies. SMS and push notifications alert individual farmers when their fields require attention.
Raw Imagery
Cloud Masking
Index Computation
ML Classification
Field Reports
Farmer Alerts
04 // COST ADVANTAGE

10% of the Cost, 100% of the Coverage

Satellite monitoring replaces expensive manual field visits with continuous, automated intelligence.

TRADITIONAL MONITORING
$2,000+
per farm per year
Agronomist visits: $200-500 each
4-10 visits per year recommended
Subjective visual assessment
No continuous monitoring between visits
Scaled by headcount, not technology
RECOMMENDED
IAGRO SAT MONITORING
$49
per hectare per year at scale
Every field monitored every 5 days
Objective, quantitative measurements
6 monitoring services included
Automated alerts for anomalies
Scales to any number of farms instantly
Barbados idle land
13,468 ha
Full monitoring cost
$660K/yr
Cost per farmer (avg 2 ha)
$98/yr
Vs. traditional
95% cheaper
05 // OPEN DATA PHILOSOPHY

The Technology Barrier Has Been Removed

The satellites are free. The compute is free. The only cost is the expertise to turn raw data into actionable intelligence.

FREE
Sentinel data
ESA Copernicus Programme
FREE
GEE compute
1,000+ EECU-hours/month
FREE
WorldCover
CC BY 4.0 license
Pennies
CaribVista cost
per pixel, per year

The technology barrier to Caribbean food sovereignty has been removed. What remains is the will to act — and the institutional framework to scale.

SEE FOR YOURSELF

See the satellite data for yourself

Every claim in the CaribVista dossier is backed by real satellite imagery and reproducible computation. The proof annex traces every number to its source.