The Data of 'UAV Remote Sensing Monitoring of Yellow Leaf Disease of Arecanut'

The areca industry is one of the main sources of income in the Hainan Province of China, accounting for the income of nearly 2.3 million farmers. The areca yellowing disease is a highly infectious disease that has severely deteriorated the production and cultivation of areca. We did a study to apply the multispectral data obtained by using a UAV along with highresolution UAV remote sensing images to monitor the severity of the areca yellowing disease through five machine learning algorithms. The following is the data package of our research:

1.The data in the folder (Areca Vegetation Index) is the vegetation index calculated by the DJI   Phantom 4 RTK to obtain the multi-spectral image and then import it into the DJI Terra software through the two-dimensional multi-spectral reconstruction.

2.The data in the folder (Machine Learning Classification) contains the vegetation index data of 200 sampling points of 603 areca trees, the vegetation index data of 57 areca trees and the identification results of the yellowing area, and the yellowing prediction training set of five machine learning methods and the predicted result.

3.The data in the folder (Model Accuracy Analysis) is the accuracy evaluation result of the correlation model between the LVV of areca and the severity of the Yellow Leaf Disease of Arecanut.

4.The data in the folder (The Severity of the Yellow Leaf Disease of Arecanut and LVV) is the prediction results of the severity of the yellow leaf disease of arecanut and the LVV measurement results of 603 areca trees in the research area.

5.The data in the folder (The Research Area DOM) is a digital orthophoto map of the research area.

6.The data in the folder (3D Point Cloud of the Areca(LAS)) is the 3D point cloud data of the research area, which is in LAS format.

7.The data in the folder (Figures) is the relevant illustration in the research paper.