Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation
Obtaining the geographic coordinates of single fruit trees enables the variable rate application of agricultural production materials according to the growth differences of trees, which is of great significance to the precision management of citrus orchards. The traditional method of detecting and p...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/17/4208 |
| _version_ | 1797493375124897792 |
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| author | Haoxin Tian Xipeng Fang Yubin Lan Chenyang Ma Huasheng Huang Xiaoyang Lu Dehua Zhao Hanchao Liu Yali Zhang |
| author_facet | Haoxin Tian Xipeng Fang Yubin Lan Chenyang Ma Huasheng Huang Xiaoyang Lu Dehua Zhao Hanchao Liu Yali Zhang |
| author_sort | Haoxin Tian |
| collection | DOAJ |
| description | Obtaining the geographic coordinates of single fruit trees enables the variable rate application of agricultural production materials according to the growth differences of trees, which is of great significance to the precision management of citrus orchards. The traditional method of detecting and positioning fruit trees manually is time-consuming, labor-intensive, and inefficient. In order to obtain high-precision geographic coordinates of trees in a citrus orchard, this study proposes a method for citrus tree identification and coordinate extraction based on UAV remote sensing imagery and coordinate transformation. A high-precision orthophoto map of a citrus orchard was drawn from UAV remote sensing images. The YOLOv5 model was subsequently used to train the remote sensing dataset to efficiently identify the fruit trees and extract tree pixel coordinates from the orchard orthophoto map. According to the geographic information contained in the orthophoto map, the pixel coordinates were converted to UTM coordinates and the WGS84 coordinates of citrus trees were obtained using Gauss–Krüger inverse calculation. To simplify the coordinate conversion process and to improve the coordinate conversion efficiency, a coordinate conversion app was also developed to automatically implement the batch conversion of pixel coordinates to UTM coordinates and WGS84 coordinates. Results show that the Precision, Recall, and <i>F</i>1 Score for Scene 1 (after weeding) reach 0.89, 0.97, and 0.92, respectively; the Precision, Recall, and <i>F</i>1 Score for Scene 2 (before weeding) reach 0.91, 0.90 and 0.91, respectively. The accuracy of the orthophoto map generated using UAV remote sensing images is 0.15 m. The accuracy of converting pixel coordinates to UTM coordinates by the coordinate conversion app is reliable, and the accuracy of converting UTM coordinates to WGS84 coordinates is 0.01 m. The proposed method is capable of automatically obtaining the WGS84 coordinates of citrus trees with high precision. |
| first_indexed | 2024-03-10T01:19:08Z |
| format | Article |
| id | doaj.art-8be5fb13686648fcacd7e484a152d2e5 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T01:19:08Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-8be5fb13686648fcacd7e484a152d2e52023-11-23T14:02:45ZengMDPI AGRemote Sensing2072-42922022-08-011417420810.3390/rs14174208Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate TransformationHaoxin Tian0Xipeng Fang1Yubin Lan2Chenyang Ma3Huasheng Huang4Xiaoyang Lu5Dehua Zhao6Hanchao Liu7Yali Zhang8College of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, ChinaNational Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, ChinaCollege of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Computer Sciences, Guangdong Polytechnic Normal University, Zhongshan Road, Guangzhou 510665, ChinaCollege of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Wushan Road, Guangzhou 510642, ChinaObtaining the geographic coordinates of single fruit trees enables the variable rate application of agricultural production materials according to the growth differences of trees, which is of great significance to the precision management of citrus orchards. The traditional method of detecting and positioning fruit trees manually is time-consuming, labor-intensive, and inefficient. In order to obtain high-precision geographic coordinates of trees in a citrus orchard, this study proposes a method for citrus tree identification and coordinate extraction based on UAV remote sensing imagery and coordinate transformation. A high-precision orthophoto map of a citrus orchard was drawn from UAV remote sensing images. The YOLOv5 model was subsequently used to train the remote sensing dataset to efficiently identify the fruit trees and extract tree pixel coordinates from the orchard orthophoto map. According to the geographic information contained in the orthophoto map, the pixel coordinates were converted to UTM coordinates and the WGS84 coordinates of citrus trees were obtained using Gauss–Krüger inverse calculation. To simplify the coordinate conversion process and to improve the coordinate conversion efficiency, a coordinate conversion app was also developed to automatically implement the batch conversion of pixel coordinates to UTM coordinates and WGS84 coordinates. Results show that the Precision, Recall, and <i>F</i>1 Score for Scene 1 (after weeding) reach 0.89, 0.97, and 0.92, respectively; the Precision, Recall, and <i>F</i>1 Score for Scene 2 (before weeding) reach 0.91, 0.90 and 0.91, respectively. The accuracy of the orthophoto map generated using UAV remote sensing images is 0.15 m. The accuracy of converting pixel coordinates to UTM coordinates by the coordinate conversion app is reliable, and the accuracy of converting UTM coordinates to WGS84 coordinates is 0.01 m. The proposed method is capable of automatically obtaining the WGS84 coordinates of citrus trees with high precision.https://www.mdpi.com/2072-4292/14/17/4208UAVorthophoto mapremote sensingHough transformYOLOv5Gauss–Krüger |
| spellingShingle | Haoxin Tian Xipeng Fang Yubin Lan Chenyang Ma Huasheng Huang Xiaoyang Lu Dehua Zhao Hanchao Liu Yali Zhang Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation Remote Sensing UAV orthophoto map remote sensing Hough transform YOLOv5 Gauss–Krüger |
| title | Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation |
| title_full | Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation |
| title_fullStr | Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation |
| title_full_unstemmed | Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation |
| title_short | Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation |
| title_sort | extraction of citrus trees from uav remote sensing imagery using yolov5s and coordinate transformation |
| topic | UAV orthophoto map remote sensing Hough transform YOLOv5 Gauss–Krüger |
| url | https://www.mdpi.com/2072-4292/14/17/4208 |
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