Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia
Abstract This study highlights the vital role of high-resolution (HR), open-source land cover maps for food security, land use planning, and environmental protection. The scarcity of freely available HR datasets underscores the importance of multi-spectral HR aerial images. We used unmanned aerial v...
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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/s41597-025-04437-7 |
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| author | Bojana Ivošević Nina Pajević Sanja Brdar Rana Waqar Maryam Khan João Valente |
| author_facet | Bojana Ivošević Nina Pajević Sanja Brdar Rana Waqar Maryam Khan João Valente |
| author_sort | Bojana Ivošević |
| collection | DOAJ |
| description | Abstract This study highlights the vital role of high-resolution (HR), open-source land cover maps for food security, land use planning, and environmental protection. The scarcity of freely available HR datasets underscores the importance of multi-spectral HR aerial images. We used unmanned aerial vehicle (UAV) to capture images for a centimeter-level orthomosaics, facilitating advanced remote sensing and spatial analysis. Our method compares the efficacy and accuracy of object-based image analysis (OBIA) combined with random forest and convolutional neural networks (CNN) for land cover classification. We produced detailed land cover maps for 27 varied landscapes across Serbia, identifying nine unique land cover classes and assessing human impact on natural habitats. This resulted in a valuable dataset of HR multi-spectral orthomosaics across ecological zones, alongside land cover classification with extensive metrics and training data for each site. This dataset is a valuable resource for researchers working on habitats mapping and assessment for biodiversity monitoring studies on one side and researchers working on novel machine learning methods for land cover classification. |
| format | Article |
| id | doaj-art-945a7a652d154b0cb3de7c5714105f44 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-945a7a652d154b0cb3de7c5714105f442025-01-19T12:09:56ZengNature PortfolioScientific Data2052-44632025-01-0112111610.1038/s41597-025-04437-7Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in SerbiaBojana Ivošević0Nina Pajević1Sanja Brdar2Rana Waqar3Maryam Khan4João Valente5BioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi SadBioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi SadBioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi SadBioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi SadFarmevo TechnologiesCentre for Automation and Robotics (CAR), Spanish National Research Council (CSIC)Abstract This study highlights the vital role of high-resolution (HR), open-source land cover maps for food security, land use planning, and environmental protection. The scarcity of freely available HR datasets underscores the importance of multi-spectral HR aerial images. We used unmanned aerial vehicle (UAV) to capture images for a centimeter-level orthomosaics, facilitating advanced remote sensing and spatial analysis. Our method compares the efficacy and accuracy of object-based image analysis (OBIA) combined with random forest and convolutional neural networks (CNN) for land cover classification. We produced detailed land cover maps for 27 varied landscapes across Serbia, identifying nine unique land cover classes and assessing human impact on natural habitats. This resulted in a valuable dataset of HR multi-spectral orthomosaics across ecological zones, alongside land cover classification with extensive metrics and training data for each site. This dataset is a valuable resource for researchers working on habitats mapping and assessment for biodiversity monitoring studies on one side and researchers working on novel machine learning methods for land cover classification.https://doi.org/10.1038/s41597-025-04437-7 |
| spellingShingle | Bojana Ivošević Nina Pajević Sanja Brdar Rana Waqar Maryam Khan João Valente Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia Scientific Data |
| title | Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia |
| title_full | Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia |
| title_fullStr | Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia |
| title_full_unstemmed | Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia |
| title_short | Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia |
| title_sort | comprehensive dataset from high resolution uav land cover mapping of diverse natural environments in serbia |
| url | https://doi.org/10.1038/s41597-025-04437-7 |
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