# Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation

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## Abstract

**:**

## 1. Introduction

- 1.
- UAV remote sensing images were collected to generate the orthophoto map of the citrus orchard.
- 2.
- The accuracy of the traditional target detection algorithm, based on the Hough transform and the YOLOv5-based deep learning algorithm, were analyzed to determine the higher-precision algorithm as the method to extract the pixel coordinates of the citrus tree.
- 3.
- The extracted pixel coordinates were transformed into the Universal Transverse Mercator (UTM) coordinate system according to the geographic information in the orthophoto map, and the transformation accuracy was also verified.
- 4.
- The geodetic coordinate transformation of the space rectangular coordinate system was carried out according to the inverse calculation formula of Gauss–Krüger and the transformation accuracy was verified as well.
- 5.
- A coordinate conversion app was developed to achieve the batch conversion of pixel coordinates to UTM coordinates and geodetic coordinates, which helps improve coordinate conversion efficiency and simplify work complexity.

## 2. Materials and Methods

#### 2.1. Overview of the Experimental Site

#### 2.2. The Overall Scheme of Fruit Tree Identification and Coordinate Extraction

#### 2.3. Remote Sensing Data Collection and Orthophoto Mapping

#### 2.4. Citrus Tree Identification

#### 2.4.1. Citrus Tree Detection Method Based on Hough Transform

#### 2.4.2. Detection Method Based on YOLOv5 Target Detection Algorithm

#### 2.4.3. Training Parameter Setting and Evaluation

#### 2.5. Citrus Tree Coordinate Extraction

#### 2.5.1. Conversion of Citrus Tree Pixel Coordinates to UTM Projection Coordinates

#### 2.5.2. Conversion from UTM Projection Coordinates of Fruit Trees to WGS84 Coordinates

## 3. Results

#### 3.1. Comparison and Analysis of Citrus Trees Identification

#### 3.2. Orthophoto Map Accuracy Verification

#### 3.3. UTM Coordinate Verification

#### 3.4. Coordinate Conversion App Design and WGS84 Coordinate Verification

^{−6}. The conversion accuracy of the method proposed in this study can reach centimeter-level precision, which meets the requirements of the geodetic coordinate conversion of citrus trees.

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 1.**The study area (

**right**) circled by the red box is located in Guangdong Province (

**left**), China (23°36′N, 112°68′E).

**Figure 2.**Overall flow chart: image acquisition, orthophoto map production, citrus tree identification, coordinate conversion.

**Figure 3.**Orchard remote sensing image datasets: (

**a**) Scene 1: after weeding, (

**b**) Scene 2: before weeding.

**Figure 4.**Mobile base station and control point layout: (

**a**) D-RTK 2 high-precision GNSS mobile station, (

**b**) the red box is the test field, and "x" is the six control points selected in the test field, (

**c**) control point.

**Figure 7.**The horizontal and vertical templates of Sobel: (

**a**) vertical templates of Sobel, (

**b**) horizontal templates of Sobel.

**Figure 9.**Pixel coordinate system and UTM coordinate system: ${x}_{1}{y}_{1}{z}_{1}$ is the UTM coordinate system; ${x}_{2}{y}_{2}{z}_{2}$ is the pixel coordinate system.

**Figure 10.**Calculation result of YOLOv5s loss. (

**a**) Calculation result of YOLOv5s loss in Scene 1: after weeding; (

**b**) calculation result of YOLOv5s loss in Scene 2: before weeding.

**Figure 11.**Field sampling and point cloud sampling: (

**a**) on-site extraction of WGS84 coordinates of sampling points; (

**b**) point cloud model extraction coordinates.

**Figure 12.**UTM coordinate verification. (

**a**–

**c**) are experimental plot 1; (

**d**–

**f**) are experimental plot 2; (

**g**–

**i**) are experimental plot 3; (

**a**,

**d**,

**g**) are converted UTM projection coordinate points; (

**b**,

**e**,

**h**) are the orthophoto map of the extracted fruit tree pixels; (

**c**,

**f**,

**i**) are the correspondence between the coordinate point and the orthophoto map in the UTM coordinate system.

**Table 1.**UAV operational parameters [33].

Name | Parameter | Value |
---|---|---|

UAV | Takeoff Weight/g | 1391 |

Max Flight Time/min | 30 | |

Horizontal Hover Accuracy (RTK)/m | ±0.1 | |

Vertical Hover Accuracy (RTK)/m | ±0.1 | |

Sensor | Pixels/× 10^{4} | 2000 |

Max Image Size | 5472 × 3648 (3:2) 4864 × 3648 (4:3) | |

Field Of View FOV/° | 84 |

Scene | Hough Transform | YOLOv5s | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|

step_r | step_angle | minr | maxr | Thresh | Input Size | Batch Size | Epoch | Weights | Optimizer | Score_Threhold | |

1 | 0.5 | 0.15 | 30 | 150 | 0.58 | 640 × 640 | 8 | 300 | s | SGD | 0.5 |

2 | 0.4 | 0.1 | 40 | 150 | 0.57 | 640 × 640 | 8 | 300 | s | SGD | 0.5 |

Image Number | Scene 1: After Weeding | Scene 2: Before Weeding | ||||||
---|---|---|---|---|---|---|---|---|

Precision | Recall | F1 Score | FPS | Precision | Recall | F1 Score | FPS | |

1 | 0.96 | 0.94 | 0.95 | 0.0241 | 0.40 | 0.53 | 0.46 | 0.0135 |

2 | 0.87 | 0.86 | 0.86 | 0.0243 | 0.50 | 0.41 | 0.45 | 0.0717 |

3 | 0.88 | 0.84 | 0.86 | 0.0251 | 0.56 | 0.50 | 0.53 | 0.0349 |

4 | 0.87 | 0.87 | 0.87 | 0.0257 | 0.34 | 0.54 | 0.42 | 0.0547 |

5 | 0.88 | 0.90 | 0.89 | 0.0258 | 0.35 | 0.48 | 0.41 | 0.0371 |

6 | 0.86 | 0.87 | 0.87 | 0.0258 | 0.48 | 0.55 | 0.51 | 0.0371 |

7 | 0.93 | 0.80 | 0.86 | 0.0242 | 0.52 | 0.52 | 0.52 | 0.0389 |

8 | 0.83 | 0.93 | 0.88 | 0.0216 | 0.57 | 0.48 | 0.52 | 0.0456 |

9 | 0.81 | 0.80 | 0.81 | 0.0238 | 0.44 | 0.50 | 0.47 | 0.0337 |

10 | 0.92 | 0.82 | 0.87 | 0.0205 | 0.63 | 0.64 | 0.63 | 0.0608 |

Average | 0.88 | 0.87 | 0.87 | 0.0241 | 0.48 | 0.52 | 0.49 | 0.0428 |

Scene | Hough Transform | YOLOv5s | ||||||
---|---|---|---|---|---|---|---|---|

F1 Score | Recall | Precision | FPS | F1 Score | Recall | Precision | FPS | |

1 | 0.87 | 0.87 | 0.88 | 0.0241 | 0.92 | 0.97 | 0.89 | 63 |

2 | 0.49 | 0.52 | 0.48 | 0.0428 | 0.91 | 0.90 | 0.91 | 60 |

Sampling Point | Coordinate Information/(X, Y) | Horizontal Error/m | Euclidean Distance Error/m | |
---|---|---|---|---|

Actual Value | Measured Value | |||

5 | (655,123.054, 2,593,077.514) | (655,123.093, 2,593,077.607) | (0.041, 0.093) | 0.101 |

4 | (655,143.585, 2,593,080.156) | (655,143.669, 2,593,080.21) | (0.084, 0.054) | 0.099 |

3 | (655,101.704, 2,593,067.178) | (655,101.896, 2,593,067.318) | (0.192, 0.14) | 0.238 |

6 | (655,135.416, 2,592,983.677) | (655,135.616, 2,592,983.785) | (0.2, 0.118) | 0.227 |

12 | (655,143.153, 2,592,974.833) | (655,143.272, 2,592,974.714) | (0.119, 0.119) | 0.168 |

1 | (655,111.020, 2,593,050.100) | (655,111.049, 2,593,050.112) | (0.029, 0.012) | 0.031 |

Mean Euclidean distance error: 0.15 m, average horizontal distance error: (0.11, 0.089) |

Experimental Plot 1 | Experimental Plot 2 | Experimental Plot 3 | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

Longitude error/10^{−6} | 0.11 | 0.10 | 0.10 | 0.11 | 0.10 | 0.10 | 0.11 | 0.11 | 0.10 | 0.11 | 0.11 | 0.11 | 0.11 | 0.10 | 0.11 | 0.11 | 0.11 | 0.10 |

Latitude error/10^{−6} | −0.1 | −0.2 | −0.1 | −0.1 | −0.2 | −0.1 | −0.2 | −0.1 | −0.1 | −0.2 | −0.1 | −0.2 | −0.1 | −0.2 | −0.1 | −0.1 | −0.2 | −0.2 |

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## Share and Cite

**MDPI and ACS Style**

Tian, H.; Fang, X.; Lan, Y.; Ma, C.; Huang, H.; Lu, X.; Zhao, D.; Liu, H.; Zhang, Y.
Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation. *Remote Sens.* **2022**, *14*, 4208.
https://doi.org/10.3390/rs14174208

**AMA Style**

Tian H, Fang X, Lan Y, Ma C, Huang H, Lu X, Zhao D, Liu H, Zhang Y.
Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation. *Remote Sensing*. 2022; 14(17):4208.
https://doi.org/10.3390/rs14174208

**Chicago/Turabian Style**

Tian, Haoxin, Xipeng Fang, Yubin Lan, Chenyang Ma, Huasheng Huang, Xiaoyang Lu, Dehua Zhao, Hanchao Liu, and Yali Zhang.
2022. "Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation" *Remote Sensing* 14, no. 17: 4208.
https://doi.org/10.3390/rs14174208