Using LiDAR System as a Data Source for Agricultural Land Boundaries
In this study, LiDAR sensor data were used to identify agricultural land boundaries. This is a remote sensing method using a pulsating laser directed toward the ground. This study focuses on accurately determining the edges of parcels using only the point cloud, which is an original approach because...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/4/1048 |
| _version_ | 1797476737689321472 |
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| author | Natalia Borowiec Urszula Marmol |
| author_facet | Natalia Borowiec Urszula Marmol |
| author_sort | Natalia Borowiec |
| collection | DOAJ |
| description | In this study, LiDAR sensor data were used to identify agricultural land boundaries. This is a remote sensing method using a pulsating laser directed toward the ground. This study focuses on accurately determining the edges of parcels using only the point cloud, which is an original approach because the point cloud is a scattered set, which may complicate finding those points that define the course of a straight line defining the parcel boundary. The innovation of the approach is the fact that no data from other sources are supported. At the same time, a unique contribution of the research is the attempt to automate the complex process of detecting the edges of parcels. The first step was to classify the data, using intensity, and define land use boundaries. Two approaches were decided, for two test fields. The first test field was a rectangular shaped parcel of land. In this approach, pixels describing each edge of the plot separately were automatically grouped into four parts. The edge description was determined using principal component analysis. The second test area was the inner subdivision plot. Here, the Hough Transform was used to emerge the edges. Obtained boundaries, both for the first and the second test area, were compared with the boundaries from the Polish land registry database. Performed analyses show that proposed algorithms can define the correct course of land use boundaries. Analyses were conducted for the purpose of control in the system of direct payments for agriculture (Integrated Administration Control System—IACS). The aim of the control is to establish the borders and areas of croplands and to verify the declared group of crops on a given cadastral parcel. The proposed algorithm—based solely on free LiDAR data—allowed the detection of inconsistencies in farmers’ declarations. These mainly concerned areas of field roads that were misclassified by farmers as subsidized land, when in fact they should be excluded from subsidies. This is visible in both test areas with areas belonging to field roads with an average width of 1.26 and 3.01 m for test area no. 1 and 1.31, 1.15, 1.88, and 2.36 m for test area no. 2 were wrongly classified as subsidized by farmers. |
| first_indexed | 2024-03-09T21:07:56Z |
| format | Article |
| id | doaj.art-2d9af02b769d496f984799a71f34f8c0 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T21:07:56Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-2d9af02b769d496f984799a71f34f8c02023-11-23T21:56:12ZengMDPI AGRemote Sensing2072-42922022-02-01144104810.3390/rs14041048Using LiDAR System as a Data Source for Agricultural Land BoundariesNatalia Borowiec0Urszula Marmol1Department of Photogrammetry Remote Sensing of Environment and Spatial Engineering, Faculty of Mining Surveying and Environmental Engineering, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, PolandDepartment of Photogrammetry Remote Sensing of Environment and Spatial Engineering, Faculty of Mining Surveying and Environmental Engineering, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, PolandIn this study, LiDAR sensor data were used to identify agricultural land boundaries. This is a remote sensing method using a pulsating laser directed toward the ground. This study focuses on accurately determining the edges of parcels using only the point cloud, which is an original approach because the point cloud is a scattered set, which may complicate finding those points that define the course of a straight line defining the parcel boundary. The innovation of the approach is the fact that no data from other sources are supported. At the same time, a unique contribution of the research is the attempt to automate the complex process of detecting the edges of parcels. The first step was to classify the data, using intensity, and define land use boundaries. Two approaches were decided, for two test fields. The first test field was a rectangular shaped parcel of land. In this approach, pixels describing each edge of the plot separately were automatically grouped into four parts. The edge description was determined using principal component analysis. The second test area was the inner subdivision plot. Here, the Hough Transform was used to emerge the edges. Obtained boundaries, both for the first and the second test area, were compared with the boundaries from the Polish land registry database. Performed analyses show that proposed algorithms can define the correct course of land use boundaries. Analyses were conducted for the purpose of control in the system of direct payments for agriculture (Integrated Administration Control System—IACS). The aim of the control is to establish the borders and areas of croplands and to verify the declared group of crops on a given cadastral parcel. The proposed algorithm—based solely on free LiDAR data—allowed the detection of inconsistencies in farmers’ declarations. These mainly concerned areas of field roads that were misclassified by farmers as subsidized land, when in fact they should be excluded from subsidies. This is visible in both test areas with areas belonging to field roads with an average width of 1.26 and 3.01 m for test area no. 1 and 1.31, 1.15, 1.88, and 2.36 m for test area no. 2 were wrongly classified as subsidized by farmers.https://www.mdpi.com/2072-4292/14/4/1048LiDAR systemsegmentationedge detectionagricultural land boundary |
| spellingShingle | Natalia Borowiec Urszula Marmol Using LiDAR System as a Data Source for Agricultural Land Boundaries Remote Sensing LiDAR system segmentation edge detection agricultural land boundary |
| title | Using LiDAR System as a Data Source for Agricultural Land Boundaries |
| title_full | Using LiDAR System as a Data Source for Agricultural Land Boundaries |
| title_fullStr | Using LiDAR System as a Data Source for Agricultural Land Boundaries |
| title_full_unstemmed | Using LiDAR System as a Data Source for Agricultural Land Boundaries |
| title_short | Using LiDAR System as a Data Source for Agricultural Land Boundaries |
| title_sort | using lidar system as a data source for agricultural land boundaries |
| topic | LiDAR system segmentation edge detection agricultural land boundary |
| url | https://www.mdpi.com/2072-4292/14/4/1048 |
| work_keys_str_mv | AT nataliaborowiec usinglidarsystemasadatasourceforagriculturallandboundaries AT urszulamarmol usinglidarsystemasadatasourceforagriculturallandboundaries |