Agriculture data

Agriculture data describes what is grown, where and how well: planted area, crop type, yields, soil conditions, weather impacts, land use and farm structure. Commodity traders, food companies, insurers, lenders, input suppliers and governments use it to forecast supply, assess crop risk, plan sourcing and target products to growers.

Typical fields

• Region or field boundary and growing season
• Crop type and planted or harvested area
• Yield estimates and forecasts, with uncertainty
• Vegetation indices such as NDVI from satellite imagery
• Soil properties, soil moisture and weather indicators
• Source flag: official statistics, survey, satellite model or farm records

Sources and methods

Official statistics from national agriculture ministries and international bodies provide reported production, usually with a lag. Satellite programmes such as Sentinel-2 and Landsat let providers map crop types and monitor crop health through the season. Yield models combine this imagery with weather and soil data. Farm-level data from machinery and farm management software also exists, but it belongs to growers and is subject to their consent and contracts.

Delivery and pricing

Regional statistics and forecasts are usually sold by subscription for chosen crops and countries, delivered as CSV, Parquet or API. Field-level layers come as GeoTIFF, GeoJSON or shapefiles. Price depends on geography, crop coverage, spatial resolution and how often forecasts update during the season.

Before you buy

• Ask how crop type maps were validated against ground truth.
• Check historical forecast accuracy against final official figures.
• Confirm the update cadence during the growing season.
• Clarify whether any farm-level data is shared with grower consent.
• Check that field boundaries and regions match your reporting units.