A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing Images
Farmland boundary information plays a key role in agricultural remote sensing, and it is of importance to modern agriculture. We collected the relevant research in this field at home and abroad in this review, and we systematically assessed the farmland boundary extraction process, detection algorit...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/5/1156 |
| _version_ | 1797615507009961984 |
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| author | Xuying Wang Lei Shu Ru Han Fan Yang Timothy Gordon Xiaochan Wang Hongyu Xu |
| author_facet | Xuying Wang Lei Shu Ru Han Fan Yang Timothy Gordon Xiaochan Wang Hongyu Xu |
| author_sort | Xuying Wang |
| collection | DOAJ |
| description | Farmland boundary information plays a key role in agricultural remote sensing, and it is of importance to modern agriculture. We collected the relevant research in this field at home and abroad in this review, and we systematically assessed the farmland boundary extraction process, detection algorithms, and influencing factors. In this paper, we first discuss the five parts of the assessment: (1) image acquisition; (2) preprocessing; (3) detection algorithms; (4) postprocessing; (5) the evaluation of the boundary information extraction process. Second, we discuss recognition algorithms. Third, we discuss various detection algorithms. The detection algorithms can be divided into four types: (1) low-level feature extraction algorithms, which only consider the boundary features; (2) high-level feature extraction algorithms, which consider boundary information and other image information simultaneously; (3) visual hierarchy extraction algorithms, which simulate biological vision systems; (4) boundary object extraction algorithms, which recognize boundary object extraction ideas. We can subdivide each type of algorithm into several algorithm subclasses. Fourth, we discuss the technical factors and natural factors that affect boundary extraction. Finally, we summarize the development history of this field, and we analyze the problems that exist, such as the lack of algorithms that can be adapted to higher-resolution images, the lack of algorithms with good practical ability, and the lack of a unified and effective evaluation index system. |
| first_indexed | 2024-03-11T07:27:29Z |
| format | Article |
| id | doaj.art-3c99226441bf433f9171444fff8f3fee |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T07:27:29Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-3c99226441bf433f9171444fff8f3fee2023-11-17T07:32:26ZengMDPI AGElectronics2079-92922023-02-01125115610.3390/electronics12051156A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing ImagesXuying Wang0Lei Shu1Ru Han2Fan Yang3Timothy Gordon4Xiaochan Wang5Hongyu Xu6College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, ChinaCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, ChinaCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, ChinaSchool of Mathematics and Statistics, Jiangsu Normal University, Xuzhou 221116, ChinaSchool of Engineering, University of Lincoln, Lincoln LN6 7TS, UKCollege of Engineering, Nanjing Agricultural University, Nanjing 210031, ChinaCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, ChinaFarmland boundary information plays a key role in agricultural remote sensing, and it is of importance to modern agriculture. We collected the relevant research in this field at home and abroad in this review, and we systematically assessed the farmland boundary extraction process, detection algorithms, and influencing factors. In this paper, we first discuss the five parts of the assessment: (1) image acquisition; (2) preprocessing; (3) detection algorithms; (4) postprocessing; (5) the evaluation of the boundary information extraction process. Second, we discuss recognition algorithms. Third, we discuss various detection algorithms. The detection algorithms can be divided into four types: (1) low-level feature extraction algorithms, which only consider the boundary features; (2) high-level feature extraction algorithms, which consider boundary information and other image information simultaneously; (3) visual hierarchy extraction algorithms, which simulate biological vision systems; (4) boundary object extraction algorithms, which recognize boundary object extraction ideas. We can subdivide each type of algorithm into several algorithm subclasses. Fourth, we discuss the technical factors and natural factors that affect boundary extraction. Finally, we summarize the development history of this field, and we analyze the problems that exist, such as the lack of algorithms that can be adapted to higher-resolution images, the lack of algorithms with good practical ability, and the lack of a unified and effective evaluation index system.https://www.mdpi.com/2079-9292/12/5/1156farmland boundaryedge detectionimage segmentationremote sensing |
| spellingShingle | Xuying Wang Lei Shu Ru Han Fan Yang Timothy Gordon Xiaochan Wang Hongyu Xu A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing Images Electronics farmland boundary edge detection image segmentation remote sensing |
| title | A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing Images |
| title_full | A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing Images |
| title_fullStr | A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing Images |
| title_full_unstemmed | A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing Images |
| title_short | A Survey of Farmland Boundary Extraction Technology Based on Remote Sensing Images |
| title_sort | survey of farmland boundary extraction technology based on remote sensing images |
| topic | farmland boundary edge detection image segmentation remote sensing |
| url | https://www.mdpi.com/2079-9292/12/5/1156 |
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