TAYA CRISTO PARREIRAS, UNIVERSIDADE ESTADUAL DE CAMPINAS; EDSON LUIS BOLFE, CNPTIA; DANIELLE ELIS GARCIA FURUYA, UNIVERSIDADE ESTADUAL DE CAMPINAS.2026-07-07http://hdl.handle.net/123456789/457458Despite the advances, accurately identifying recently renovated and skeletonized coffee areas remains a challenge, as their altered canopy structure and reduced vigor produce spectral signatures similar to those of fallow or non-coffee areas. To address these limitations, upcoming research will focus on leveraging a space-time hybrid approach with deep learning and surface phenology modeling. Specifically, we plan to implement a workflow combining the spatial detail of Sentinel-2 with the temporal continuity of HLS.openAccessAgricultura digitalAprendizado profundoDados multisensorDigital agricultureDeep learningCaféSensoriamento RemotoRemote sensingResumo em anais e proceedings