ELIAC – Early Identification of Agricultural Crops using Artificial Intelligence and Sentinel-2 Data
The ELIAC project aims at fostering of Copernicus data, more specifically multispectral images from Sentinel-2 satellites, by producing land cover maps for application in Romanian agriculture. By deploying the latest AI models and techniques, we aim at realizing the early identification of agricultural crops, as opposed to the now-established techniques which identify the agricultural crops at the end of their life-time. Early identification, i.e. identification at the beginning of the vegetation status, is a challenge due to the confusion between spectral signatures of various vegetation types/agricultural crops.
This project is supported by a grant of the Ministry of Research, Innovation and Digitization, CCDI-UEFISCDI, project no. PN-IV-P7-7.1-PED-2024-0375 in PNCDI IV.
The ELIAC project scope is to start from the existing proof of concept, formulated by the project coordinator, of an approach for early identification of agricultural crops using artificial intelligence and EO data (TRL 2) and to develop it in a superior technological level i.e. an in-lab validated technology (TRL 4) together with the project partner, the private company. The specific ELIAC project objectives are:
Scientific Objective (SO) - to experiment, adapt, redesign and implement (thus reaching TRL 3) a software application of an existing approach for early identification of agricultural crops using AI and Sentinel-2 data, that allows reaching the scope of the project.
Technical Objective (TO) - to develop and validate in laboratory (thus reaching TRL 4) the prototype of the proposed solution that could become a commercial product of the partner, thus increasing the capacity of the coordinator to generate solutions for new products/technologies and services transferred to industry
Dissemination Objective (DO) - to disseminate the scientific findings of the ELIAC project through participation in international conferences and publication in open science international journals with peer review and high impact factor
IP Protection Objective (PO) - to identify and protect those scientific findings of the ELIAC project that have the potential of being technologically applicable and valorized through means of intellectual property protection
Management Objective (MO) - to ensure the appropriate project management that leads to a successful implementation of the ELIAC project
Dissemination
A. Kazak and M. Ivanovici, “Agricultural Crop Classification Using Sentinel-2 Data and Local Features,” 2025 International Symposium on Signals, Circuits and Systems (ISSCS), Iasi, Romania, 2025, pp. 1-4, doi: 10.1109/ISSCS66034.2025.11105680.
A. Kazak, V. Mirovski and M. Ivanovici, “Random Data Sampling for an Agricultural Crop Classification Task,” 2025 18th International Conference on Engineering of Modern Electric Systems (EMES), Oradea, Romania, 2025, pp. 1-6, doi: 10.1109/EMES65692.2025.11045606.