Information System for Abandoned Arable Land Detection From Sentinel-2 Images
| dc.contributor.author | Akymenko, Karyna | en |
| dc.contributor.author | Sergieieva, Kateryna L. | en |
| dc.contributor.author | Kavats, Yurii V. | en |
| dc.contributor.author | Kovrov, Oleksandr S. | en |
| dc.date.accessioned | 2025-10-23T11:29:54Z | |
| dc.date.issued | 2025 | |
| dc.description | K. Akymenko: ORCID 0009-0008-2615-5015; K. Sergieieva: ORCID 0000-0001-7345-2209; Yu. Kavats: ORCID 0000-0002-0180-5957; O. Kovrov: ORCID 0000-0003-3364-119X | en |
| dc.description.abstract | ENG: An information system for the automated detection of abandoned arable land, based on Sentinel-2 satellite images, is developed. The system provides monitoring of agricultural land, even in areas where ground surveys are challenging to conduct. Integrated with Google Earth Engine (GEE), the system classifies agricultural areas as cultivated or abandoned in near real time based on Normalized Difference Vegetation Index (NDVI) time series. It supports two modes of operation: local analysis of GeoTIFF files and cloud analysis using an interactive map. Its classification method compares the maximum NDVI values for the target and reference years, enabling the detection of the characteristics of the vegetation cover degradation of abandoned land. The results were experimentally validated for a sample of agricultural areas in the Dnipropetrovsk and Donetsk Oblasts. The proposed system can detect abandoned arable land with an accuracy of up to 92.5% (F1-score: 0.898), even in areas of military conflict where ground observations are unavailable. | en |
| dc.description.sponsorship | Dnipro University of Technology, Dnipro | |
| dc.identifier.citation | Akymenko K., Sergieieva K., Kavats Yu., Kovrov O. Information System for Abandoned Arable Land Detection From Sentinel-2 Images. CEUR Workshop Proceedings. Vol. 4048 : Proc. of the 13-th International Conference on Information Control Systems & Technologies (ICST 2025), Odesa, Ukraine, September 24-26, 2025. Odesa, 2025. P. 304–316. | en |
| dc.identifier.issn | 1613-0073 | |
| dc.identifier.uri | https://ceur-ws.org/Vol-4049/ | en |
| dc.identifier.uri | https://crust.ust.edu.ua/handle/123456789/21145 | en |
| dc.language.iso | en | |
| dc.publisher | CEUR-WS Team, Aachen, Germany | en |
| dc.rights | Creative Commons License Attribution 4.0 International (CC BY 4.0) | en |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
| dc.subject | information system | en |
| dc.subject | classification | en |
| dc.subject | NDVI | en |
| dc.subject | Sentinel-2 | en |
| dc.subject | monitoring | en |
| dc.subject | abandoned arable land | en |
| dc.subject | КІТС | uk_UA |
| dc.subject.classification | TECHNOLOGY | en |
| dc.subject.classification | TECHNOLOGY::Information technology | en |
| dc.title | Information System for Abandoned Arable Land Detection From Sentinel-2 Images | en |
| dc.type | Article | en |