Sample Earth — Tree Crop Reference Dataset — (Colombia, Ghana)

This dataset contains GPS-located land-cover samples that can be used to train and validate AI models that generate detailed, accurate maps, with a focus on coffee and cocoa production systems. The data were collected across Colombia and Ghana through expert interpretation of high-resolution satellite imagery. Each sample is labelled and quality-controlled to represent the land-cover types. The classification scheme includes four main classes: coffee, cocoa, tree crops, and seasonal agriculture. While the primary goal is to distinguish coffee and cocoa systems from other land uses, the dataset also supports broader applications such as agricultural monitoring, deforestation analysis, ecosystem-service mapping, land-use planning, and suitability modelling. By providing transparent, well-validated training data, this dataset contributes to the Sample Earth initiative's broader objective of strengthening AI-based land monitoring tools and supporting global efforts — including the EU Deforestation Regulation (EUDR) — to ensure sustainable, deforestation-free agricultural supply chains.