DOI: 10.1016/j.jag.2017.08.014
Scopus记录号: 2-s2.0-85032189665
论文题名: Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery
作者: Malambo L ; , Popescu S ; C ; , Murray S ; C ; , Putman E ; , Pugh N ; A ; , Horne D ; W ; , Richardson G ; , Sheridan R ; , Rooney W ; L ; , Avant R ; , Vidrine M ; , McCutchen B ; , Baltensperger D ; , Bishop M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2018
卷: 64 起始页码: 31
结束页码: 42
语种: 英语
英文关键词: 3D point cloud
; Above-ground level
; Field-based
; High-throughput phenotyping
; Maize
; Multitemporal
; Pix4D
; Plant height
; Sorghum
; Structure from motion
; Terrestrial laser scanning
; Unmanned aerial systems
Scopus关键词: aerial survey
; angiosperm
; height determination
; image resolution
; maize
; phenotype
; terrestrial environment
; three-dimensional modeling
; unmanned vehicle
; Sorghum bicolor
; Zea mays
英文摘要: Plant breeders and agronomists are increasingly interested in repeated plant height measurements over large experimental fields to study critical aspects of plant physiology, genetics and environmental conditions during plant growth. However, collecting such measurements using commonly used manual field measurements is inefficient. 3D point clouds generated from unmanned aerial systems (UAS) images using Structure from Motion (SfM) techniques offer a new option for efficiently deriving in-field crop height data. This study evaluated UAS/SfM for multitemporal 3D crop modelling and developed and assessed a methodology for estimating plant height data from point clouds generated using SfM. High-resolution images in visible spectrum were collected weekly across 12 dates from April (planting) to July (harvest) 2016 over 288 maize (Zea mays L.) and 460 sorghum (Sorghum bicolor L.) plots using a DJI Phantom 3 Professional UAS. The study compared SfM point clouds with terrestrial lidar (TLS) at two dates to evaluate the ability of SfM point clouds to accurately capture ground surfaces and crop canopies, both of which are critical for plant height estimation. Extended plant height comparisons were carried out between SfM plant height (the 90th, 95th, 99th percentiles and maximum height) per plot and field plant height measurements at six dates throughout the growing season to test the repeatability and consistency of SfM estimates. High correlations were observed between SfM and TLS data (R2 = 0.88–0.97, RMSE = 0.01–0.02 m and R2 = 0.60–0.77 RMSE = 0.12–0.16 m for the ground surface and canopy comparison, respectively). Extended height comparisons also showed strong correlations (R2 = 0.42–0.91, RMSE = 0.11–0.19 m for maize and R2 = 0.61–0.85, RMSE = 0.12–0.24 m for sorghum). In general, the 90th, 95th and 99th percentile height metrics had higher correlations to field measurements than the maximum metric though differences among them were not statistically significant. The accuracy of SfM plant height estimates fluctuated over the growing period, likely impacted by the changing reflectance regime due to plant development. Overall, these results show a potential path to reducing laborious manual height measurement and enhancing plant research programs through UAS and SfM. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79879
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Ecosystem Science & Management, Texas A&M University, College Station, TX, United States; Department of Soil & Crop Sciences, Texas A&M University, College Station, TX, United States; Texas A&M AgriLife Research, Texas A&M University, College Station, TX, United States; Department of Geography, Texas A&M University, College Station, TX, United States
Recommended Citation:
Malambo L,, Popescu S,C,et al. Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2018-01-01,64