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A New Method for Crop Row Detection Using Unmanned Aerial Vehicle Images
Chen, Pengfei1,2,3; Ma, Xiao1,4; Wang, Fangyong5; Li, Jing1
2021-09-01
Source PublicationREMOTE SENSING
Volume13Issue:17Pages:16
Corresponding AuthorLi, Jing(Jingli@igsnrr.ac.cn)
AbstractCrop row detection using unmanned aerial vehicle (UAV) images is very helpful for precision agriculture, enabling one to delineate site-specific management zones and to perform precision weeding. For crop row detection in UAV images, the commonly used Hough transform-based method is not sufficiently accurate. Thus, the purpose of this study is to design a new method for crop row detection in orthomosaic UAV images. For this purpose, nitrogen field experiments involving cotton and nitrogen and water field experiments involving wheat were conducted to create different scenarios for crop rows. During the peak square growth stage of cotton and the jointing growth stage of wheat, multispectral UAV images were acquired. Based on these data, a new crop detection method based on least squares fitting was proposed and compared with a Hough transform-based method that uses the same strategy to preprocess images. The crop row detection accuracy (CRDA) was used to evaluate the performance of the different methods. The results showed that the newly proposed method had CRDA values between 0.99 and 1.00 for different nitrogen levels of cotton and CRDA values between 0.66 and 0.82 for different nitrogen and water levels of wheat. In contrast, the Hough transform method had CRDA values between 0.93 and 0.98 for different nitrogen levels of cotton and CRDA values between 0.31 and 0.53 for different nitrogen and water levels of wheat. Thus, the newly proposed method outperforms the Hough transform method. An effective tool for crop row detection using orthomosaic UAV images is proposed herein.
Keywordrow detection wheat cotton unmanned aerial vehicle image
DOI10.3390/rs13173526
WOS KeywordAUTOMATIC DETECTION ; PRECISION AGRICULTURE ; SYSTEM ; NETWORK ; INDEXES
Indexed BySCI
Language英语
Funding ProjectNational Science and Technology Major Project of China's High Resolution Earth Observation System[21-Y20B01-9001-19/22] ; National Natural Science Foundation of China[41871344] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23100101]
Funding OrganizationNational Science and Technology Major Project of China's High Resolution Earth Observation System ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences
WOS Research AreaEnvironmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000694482100001
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/165434
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLi, Jing
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
3.Natl Sci & Technol Infrastruct China, Natl Earth Syst Sci Data Ctr, Beijing 100101, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Xinjiang Acad Agr & Redamat Sci, Cotton Inst, Shihezi 832000, Peoples R China
Recommended Citation
GB/T 7714
Chen, Pengfei,Ma, Xiao,Wang, Fangyong,et al. A New Method for Crop Row Detection Using Unmanned Aerial Vehicle Images[J]. REMOTE SENSING,2021,13(17):16.
APA Chen, Pengfei,Ma, Xiao,Wang, Fangyong,&Li, Jing.(2021).A New Method for Crop Row Detection Using Unmanned Aerial Vehicle Images.REMOTE SENSING,13(17),16.
MLA Chen, Pengfei,et al."A New Method for Crop Row Detection Using Unmanned Aerial Vehicle Images".REMOTE SENSING 13.17(2021):16.
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