| Ref.No: | 61516900 |
| Start date: | 07.06.2023 |
| End date: | 06.06.2025 |
| Approval date: | 01.06.2023 |
| Department: | RURAL & SURVEYING ENGINEERING |
| Sector: | TOPOGRAPHY SCOPE |
| Financier: | 4Η ΠΡΟΚΗΡΥΞΗ ΕΛΙΔΕΚ ΓΙΑ Υ.Δ., ELIDEK |
| Budget: | 21.600,00 € |
| Public key: | ΡΕΑ646ΨΖΣ4-ΒΣ0 |
| Scientific Responsible: | Assoc. Prof. KARANTZALOS |
| Email: | karank@central.ntua.gr |
| Description: | ORGANIC CROPS FOLLOWING SPECIFIC PRODUCTION PROCESSES, OFFERING ADDED VALUE TO PRODUCERS, CONSUMERS AND THE ENVIRONMENT. AUDITS AND CONTROL ARE REQUIRED ACCORDING TO THE CURRENT LEGISLATION. HOWEVER, THE SIMILARITY OF THE FINAL PRODUCTS PRODUCED, WITH THOSE OF CONVENTIONAL CULTIVATION, DOES NOT ALWAYS PROVE THAT A PRODUCT WAS PRODUCED, FOLLOWING THE RULES. THE AIM OF THE STUDY IS THE DEVELOPMENT OF A TOOL THAT WILL BE ABLE TO DETERMINE THE RISK OF DEVIATION FROM THE IMPLEMENTATION OF THE CULTIVATION PROGRAM OF THE FARMER. IT IS PLANNED TO USE MULTISPECTRAL IMAGERY, TIME SERIES ANALYSIS, AND TO MODEL THE CHANGES OBSERVED IN THE CROPS AND TO LINK THEM WITH THE INDICATED CULTIVATION METHOD (BIOLOGICAL, CONVENTIONAL, ETC.) BASED ON THE AVAILABLE LONG-TERM REMOTE SENSING DATA. THESE WILL ALSO BE COMBINED WITH THE RECORDS OF THE CULTIVATORS' WORK ON THE PLOTS. SELECTED INDICATORS AND TECHNIQUES OF OBJECT-ORIENTED IMAGE ANALYSIS, MACHINE LEARNING AND DEEP LEARNING MODELS WILL BE USED. |
