Tree crop mapping of South America reveals links to deforestation and conservation

TL;DR

This paper introduces the first high-resolution map of tree crops in South America, revealing links to deforestation and highlighting issues in current regulatory classifications affecting smallholder farmers.

Contribution

It presents a novel 10m-resolution tree crop map for South America using deep learning on satellite data, improving accuracy in monitoring agricultural expansion and forest loss.

Findings

Approximately 11 million hectares of tree crops identified

23% of tree crops linked to forest cover loss (2000-2020)

Regulatory maps often misclassify smallholder agroforestry as forest

Abstract

Monitoring tree crop expansion is vital for zero-deforestation policies like the European Union's Regulation on Deforestation-free Products (EUDR). However, these efforts are hindered by a lack of highresolution data distinguishing diverse agricultural systems from forests. Here, we present the first 10m-resolution tree crop map for South America, generated using a multi-modal, spatio-temporal deep learning model trained on Sentinel-1 and Sentinel-2 satellite imagery time series. The map identifies approximately 11 million hectares of tree crops, 23% of which is linked to 2000-2020 forest cover loss. Critically, our analysis reveals that existing regulatory maps supporting the EUDR often classify established agriculture, particularly smallholder agroforestry, as "forest". This discrepancy risks false deforestation alerts and unfair penalties for small-scale farmers. Our work mitigates this risk by providing a high-resolution baseline, supporting conservation policies that are effective, inclusive, and equitable.