Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet
Accurate positioning is one of the main components and challenges for precision forestry. This study was established to test the feasibility of a low-cost GNSS receiver, u-blox ZED-F9P, in movable RTK mode with features that determine its positioning accuracy following logging trails in the forest e...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/12/2856 |
| _version_ | 1797482696987901952 |
|---|---|
| author | Omid Abdi Jori Uusitalo Julius Pietarinen Antti Lajunen |
| author_facet | Omid Abdi Jori Uusitalo Julius Pietarinen Antti Lajunen |
| author_sort | Omid Abdi |
| collection | DOAJ |
| description | Accurate positioning is one of the main components and challenges for precision forestry. This study was established to test the feasibility of a low-cost GNSS receiver, u-blox ZED-F9P, in movable RTK mode with features that determine its positioning accuracy following logging trails in the forest environment. The accuracy of the low-cost receiver was controlled via a geodetic-grade receiver and high-density LiDAR data. The features of nearby logging trails were extracted from the LiDAR data in three main categories: tree characteristics; ground-surface conditions; and crown-surface conditions. An object-based TreeNet approach was used to explore the influential features of the receiver’s positioning accuracy. The results of the TreeNet model indicated that tree height, ground elevation, aspect, canopy-surface elevation, and tree density were the top influencing features. The partial dependence plots showed that tree height above 14 m, ground elevation above 134 m, western direction, canopy-surface elevation above 138 m, and tree density above 30% significantly increased positioning errors by the low-cost receiver over southern Finland. Overall, the low-cost receiver showed high performance in acquiring reliable and consistent positions, when integrated with LiDAR data. The system has a strong potential for navigating machinery in the pathway of precision harvesting in commercial forests. |
| first_indexed | 2024-03-09T22:37:06Z |
| format | Article |
| id | doaj.art-d5467af9e5b146ce999d01f1d6c3c7ce |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T22:37:06Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d5467af9e5b146ce999d01f1d6c3c7ce2023-11-23T18:47:58ZengMDPI AGRemote Sensing2072-42922022-06-011412285610.3390/rs14122856Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNetOmid Abdi0Jori Uusitalo1Julius Pietarinen2Antti Lajunen3Department of Forest Sciences, University of Helsinki, Latokartanonkaari 7, 00014 Helsinki, FinlandDepartment of Forest Sciences, University of Helsinki, Latokartanonkaari 7, 00014 Helsinki, FinlandDepartment of Agricultural Sciences, University of Helsinki, Koetilantie 5, 00790 Helsinki, FinlandDepartment of Agricultural Sciences, University of Helsinki, Koetilantie 5, 00790 Helsinki, FinlandAccurate positioning is one of the main components and challenges for precision forestry. This study was established to test the feasibility of a low-cost GNSS receiver, u-blox ZED-F9P, in movable RTK mode with features that determine its positioning accuracy following logging trails in the forest environment. The accuracy of the low-cost receiver was controlled via a geodetic-grade receiver and high-density LiDAR data. The features of nearby logging trails were extracted from the LiDAR data in three main categories: tree characteristics; ground-surface conditions; and crown-surface conditions. An object-based TreeNet approach was used to explore the influential features of the receiver’s positioning accuracy. The results of the TreeNet model indicated that tree height, ground elevation, aspect, canopy-surface elevation, and tree density were the top influencing features. The partial dependence plots showed that tree height above 14 m, ground elevation above 134 m, western direction, canopy-surface elevation above 138 m, and tree density above 30% significantly increased positioning errors by the low-cost receiver over southern Finland. Overall, the low-cost receiver showed high performance in acquiring reliable and consistent positions, when integrated with LiDAR data. The system has a strong potential for navigating machinery in the pathway of precision harvesting in commercial forests.https://www.mdpi.com/2072-4292/14/12/2856mobile RTKlow-cost GNSS receiverpositioning accuracyLiDAR datatree characteristicsterrain conditions |
| spellingShingle | Omid Abdi Jori Uusitalo Julius Pietarinen Antti Lajunen Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet Remote Sensing mobile RTK low-cost GNSS receiver positioning accuracy LiDAR data tree characteristics terrain conditions |
| title | Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet |
| title_full | Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet |
| title_fullStr | Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet |
| title_full_unstemmed | Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet |
| title_short | Evaluation of Forest Features Determining GNSS Positioning Accuracy of a Novel Low-Cost, Mobile RTK System Using LiDAR and TreeNet |
| title_sort | evaluation of forest features determining gnss positioning accuracy of a novel low cost mobile rtk system using lidar and treenet |
| topic | mobile RTK low-cost GNSS receiver positioning accuracy LiDAR data tree characteristics terrain conditions |
| url | https://www.mdpi.com/2072-4292/14/12/2856 |
| work_keys_str_mv | AT omidabdi evaluationofforestfeaturesdetermininggnsspositioningaccuracyofanovellowcostmobilertksystemusinglidarandtreenet AT joriuusitalo evaluationofforestfeaturesdetermininggnsspositioningaccuracyofanovellowcostmobilertksystemusinglidarandtreenet AT juliuspietarinen evaluationofforestfeaturesdetermininggnsspositioningaccuracyofanovellowcostmobilertksystemusinglidarandtreenet AT anttilajunen evaluationofforestfeaturesdetermininggnsspositioningaccuracyofanovellowcostmobilertksystemusinglidarandtreenet |