Indexed by:
Abstract:
In order to explore the application potential of unmanned aerial vehicle (UAV)remote sensing in the verification of afforestation results, unmanned aerial vehicle (UAV) remote sensing technique was used to extract the parameters and the number of tree well in a cutting area of Jiangle County, Fujian Province. Phantom 4Pro UAV equipped with a digital camera was used to obtain 0.01 m resolution aerial images. DOM, DSM and point cloud data were acquired after pre-processing. They were interpreted by artificial visual interpretation, template matching method, circular Hough transform, respectively, by which all the parameters of tree well were extracted and then analyzed and the applicability and classification accuracy of each method was evaluated in the parameters extraction of tree well in afforestation project.The correctness of tree well number obtained by template matching was 92.60%. The correctness of holes number obtained by circular Hough transform was 95.15%.At the same time, the measurement of tree well width and depth got a good results with the R2of 0.93 and 0.92, root mean square error (RMSE) values of 1.02 cm and 1.67 cm. It not only had high precision, and the results were consistent with template matching method, but also extracted the width and depth of tree well and improved the processing speed of big data.Remote sensing based on UAV could be used for number, width and depth parameters extraction of tree well. The circular Hough transform method could get precision parameters of tree well, which providing a technical plan for quality checking of tree well and extending UAVRS application in afforestation project. © 2021, Chinese Society of Agricultural Machinery. All right reserved.
Keyword:
Reprint 's Address:
Email:
Source :
Transactions of the Chinese Society for Agricultural Machinery
ISSN: 1000-1298
Year: 2021
Issue: 12
Volume: 52
Page: 201-206
Cited Count:
SCOPUS Cited Count: 3
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 1
Affiliated Colleges: