کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5755416 | 1621793 | 2018 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery
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کلمات کلیدی
3D point cloud - ابر نقطه 3Dplant height - ارتفاع گیاهTerrestrial laser scanning - اسکن لیزر زمینیMaize - ذرت یا جواریStructure from motion - ساختار از حرکتSorghum - سورگوم Unmanned aerial systems - سیستم های هوایی بدون سرنشینHigh-throughput phenotyping - فنوتیپی با کارایی بالاField-based - مبتنی بر فیلدMultitemporal - چند روزه
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
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 (R2Â =Â 0.88-0.97, RMSEÂ =Â 0.01-0.02Â m and R2Â =Â 0.60-0.77 RMSEÂ =Â 0.12-0.16Â m for the ground surface and canopy comparison, respectively). Extended height comparisons also showed strong correlations (R2Â =Â 0.42-0.91, RMSEÂ =Â 0.11-0.19Â m for maize and R2Â =Â 0.61-0.85, RMSEÂ =Â 0.12-0.24Â 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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 64, February 2018, Pages 31-42
Journal: International Journal of Applied Earth Observation and Geoinformation - Volume 64, February 2018, Pages 31-42
نویسندگان
L. Malambo, S.C. Popescu, S.C. Murray, E. Putman, N.A. Pugh, D.W. Horne, G. Richardson, R. Sheridan, W.L. Rooney, R. Avant, M. Vidrine, B. McCutchen, D. Baltensperger, M. Bishop,