The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia)
Abstract Irrigation is a cornerstone of global food security, enabling sustainable agricultural production and helping to ensure that food is available for people around the world, now and in the future. Mapping irrigated fields provides valuable information for sustainable water management, agricul...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04443-9 |
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| author | Mirjana Radulović Miljana Marković Sanja Brdar Ioannis Athanasiadis Gordan Mimić |
| author_facet | Mirjana Radulović Miljana Marković Sanja Brdar Ioannis Athanasiadis Gordan Mimić |
| author_sort | Mirjana Radulović |
| collection | DOAJ |
| description | Abstract Irrigation is a cornerstone of global food security, enabling sustainable agricultural production and helping to ensure that food is available for people around the world, now and in the future. Mapping irrigated fields provides valuable information for sustainable water management, agricultural development, and environmental conservation efforts. However, the collection of high-quality training data, which is necessary for accurate irrigation mapping remains costly and labour-intensive. To address this, we created a georeferenced regional dataset consisting of location, crop type, and occurrence of the irrigation equipment which are essential information for mapping irrigated fields. Four main irrigated crops were considered: maize, soybean, sugar beet, and wheat. The dataset, consisting of a total of 1256 parcels, is created for Vojvodina, the main agricultural area in Serbia, spanning the period of five years (2020–2024). This study’s goal is to give accessibility to our dataset which further can be explored and used for building or fine-tuning machine learning and deep learning models for the automatic detection of irrigated fields using satellite imagery. |
| format | Article |
| id | doaj-art-3e253362ce734f6981807da33f4f7f21 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-3e253362ce734f6981807da33f4f7f212025-01-19T12:09:55ZengNature PortfolioScientific Data2052-44632025-01-011211610.1038/s41597-025-04443-9The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia)Mirjana Radulović0Miljana Marković1Sanja Brdar2Ioannis Athanasiadis3Gordan Mimić4BioSense Institute - the Research and Development Institute for Information Technologies in Biosystems, University of Novi SadBioSense Institute - the Research and Development Institute for Information Technologies in Biosystems, University of Novi SadBioSense Institute - the Research and Development Institute for Information Technologies in Biosystems, University of Novi SadWageningen University and Research CentreBioSense Institute - the Research and Development Institute for Information Technologies in Biosystems, University of Novi SadAbstract Irrigation is a cornerstone of global food security, enabling sustainable agricultural production and helping to ensure that food is available for people around the world, now and in the future. Mapping irrigated fields provides valuable information for sustainable water management, agricultural development, and environmental conservation efforts. However, the collection of high-quality training data, which is necessary for accurate irrigation mapping remains costly and labour-intensive. To address this, we created a georeferenced regional dataset consisting of location, crop type, and occurrence of the irrigation equipment which are essential information for mapping irrigated fields. Four main irrigated crops were considered: maize, soybean, sugar beet, and wheat. The dataset, consisting of a total of 1256 parcels, is created for Vojvodina, the main agricultural area in Serbia, spanning the period of five years (2020–2024). This study’s goal is to give accessibility to our dataset which further can be explored and used for building or fine-tuning machine learning and deep learning models for the automatic detection of irrigated fields using satellite imagery.https://doi.org/10.1038/s41597-025-04443-9 |
| spellingShingle | Mirjana Radulović Miljana Marković Sanja Brdar Ioannis Athanasiadis Gordan Mimić The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia) Scientific Data |
| title | The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia) |
| title_full | The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia) |
| title_fullStr | The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia) |
| title_full_unstemmed | The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia) |
| title_short | The first geospatial dataset of irrigated fields (2020–2024) in Vojvodina (Serbia) |
| title_sort | first geospatial dataset of irrigated fields 2020 2024 in vojvodina serbia |
| url | https://doi.org/10.1038/s41597-025-04443-9 |
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