The AIGODS project has reached a major scientific milestone with the online publication of its systematic literature review in Smart Agricultural Technology, a Q1 journal published by Elsevier. This article now stands as the project’s first peer-reviewed journal publication and represents the formal consolidation of one of its central scientific foundations: the study of automated vineyard area identification through remote sensing (RS) and artificial intelligence. Its publication marks the transition from internal methodological development to internationally visible scientific output, reinforcing the project’s credibility within the fields of precision viticulture, geospatial intelligence, and applied agricultural technology.

This achievement also gives continuity to the earlier peer-review milestone announced at the end of December, when the manuscript received positive feedback and was invited for minor revisions. With those revisions completed, the article has now been formally published, confirming both the strength of the review itself and the scientific maturity of the work produced within AIGODS. In practical terms, this publication provides the project with a robust and citable evidence base for its vineyard mapping branch, while also placing Douro Demarcated Region (DDR)-centred research within a broader international discussion on how vineyards can be identified, monitored, and interpreted through increasingly advanced RS workflows.

The published review synthesises 108 sources, of which 80 empirical studies contributed directly to the evidence base, and traces the evolution of vineyard identification from classical pixel-based approaches to workflows centred on UAV imagery, deep learning, and growing integration of 3D information. Beyond summarising the literature, the paper introduces a domain-adapted risk-of-bias framework designed to assess the credibility, validation quality, and portability of vineyard mapping studies. This is especially important in a field where technical performance is often reported without sufficient attention to reproducibility, external validity, or realistic deployment conditions. By addressing those issues directly, the review does more than map the state of the art. It helps clarify what should count as robust evidence in future vineyard monitoring research.

For AIGODS, the publication is important not only because it adds a scientific output to the project record, but because it strengthens the theoretical and methodological basis of the work being developed for the DDR. The review clarifies the main technical trends, identifies persistent limitations such as weak spatiotemporal portability and validation gaps, and supports the project’s own emphasis on careful benchmarking, interpretability, and operational relevance. In that sense, this publication is both a scientific achievement in its own right and a foundational reference for the project’s ongoing contribution to intelligent viticulture.

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