🌵 Our project SinergIA — Remote Sensing and Artificial Intelligence for Mapping Energy Crops in the Brazilian Semi-Arid Region has been funded by CNPq (Chamada 22/2024 – Redes, process 444316/2024-8, R$ 249,937.95), led by Prof. Aldo Torres Sales. I am taking part as International Technical Lead & Collaborator.

The project maps energy and forage crops — with a focus on forage cactus (palma) — across the semi-arid Caatinga, fusing Sentinel-1 (SAR) and Sentinel-2 (optical) time series with machine learning to overcome the region’s cloud cover and complex, heterogeneous landscapes.

Study area: the Brazilian Semi-Arid region (red) and the state of Pernambuco (green).

Field campaign — March 2026. We carried out our first ground-truth campaign across palma plantations and native Caatinga, collecting reference data to train and validate the classification models.

Forage cactus (palma) plantation within the Caatinga, Pernambuco — March 2026 field campaign.

Using this field data, we are building multi-sensor Sentinel-1 + Sentinel-2 time series for each surveyed field and extracting preliminary phenological signatures — an early step toward reliable, within-season mapping of energy crops in the region.

Sentinel-2 NDVI and Sentinel-1 RVI time series for a surveyed palma field, with the March 2026 field-work date marked (dashed line).