Detecting Cadastral Boundary from Satellite Images Using U-Net model
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909496080596992 |
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| author | Anaraki, Neda Rahimpour Tahmasbi, Maryam Kheradpisheh, Saeed Reza |
| author_facet | Anaraki, Neda Rahimpour Tahmasbi, Maryam Kheradpisheh, Saeed Reza |
| contents | Finding the cadastral boundaries of farmlands is a crucial concern for land administration. Therefore, using deep learning methods to expedite and simplify the extraction of cadastral boundaries from satellite and unmanned aerial vehicle (UAV) images is critical. In this paper, we employ transfer learning to train a U-Net model with a ResNet34 backbone to detect cadastral boundaries through three-class semantic segmentation: "boundary", "field", and "background". We evaluate the performance on two satellite images from farmlands in Iran using "precision", "recall", and "F-score", achieving high values of 88%, 75%, and 81%, respectively, which indicate promising results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_11044 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Detecting Cadastral Boundary from Satellite Images Using U-Net model Anaraki, Neda Rahimpour Tahmasbi, Maryam Kheradpisheh, Saeed Reza Computer Vision and Pattern Recognition Machine Learning Finding the cadastral boundaries of farmlands is a crucial concern for land administration. Therefore, using deep learning methods to expedite and simplify the extraction of cadastral boundaries from satellite and unmanned aerial vehicle (UAV) images is critical. In this paper, we employ transfer learning to train a U-Net model with a ResNet34 backbone to detect cadastral boundaries through three-class semantic segmentation: "boundary", "field", and "background". We evaluate the performance on two satellite images from farmlands in Iran using "precision", "recall", and "F-score", achieving high values of 88%, 75%, and 81%, respectively, which indicate promising results. |
| title | Detecting Cadastral Boundary from Satellite Images Using U-Net model |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2502.11044 |