2026-09-20T09:54:59Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/99224 2023-07-11 col_2142_5131 col_2142_14847 com_2142_5130 com_2142_683 com_2142_397

Tian, Lei Zhu, Huangjian 2018-03-13T15:25:22Z 2018-03-13T15:25:22Z 2020-03-14T09:15:08Z 2017-12-04 2017-12 Crop height monitoring is important to appropriate field management. Previous studies have indicated that a Light Detection and Ranging (LiDAR) sensor was capable of accurate and fast data collection. As technology of Unmanned Aerial Vehicles (UAV) advanced, the airborne LiDAR system became a promising remote sensing based method for non-destructive crop height measurement. The objective of this study was to develop a UAV-based LiDAR system for crop height measurement. The system consisted of a 360-degree 2D laser scanner and an onboard computer mounted on an open source UAV platform. A data processing and visualization algorithm was developed to process dense spatial point cloud data and generate a crop height map of the target field. Outdoor experiments were conducted in a real corn field to evaluate the height measurement performance of the UAV-based LiDAR system. The results show that the average R2 value of 0.87, average mean error (absolute error) of 4.47% and average RMSE of 0.143 m, were achieved in comparison with manual measurements. The UAV-based LiDAR system could cover a 2 acre corn field within eight and half minutes, saving about 90% operation time compared with a tractor-based LiDAR system. The UAV-based LiDAR system developed in this study demonstrated its accurate and efficient crop height measurement in a real crop field, and is expected to be applied in practical agricultural production. Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-12-01 The student, Huangjian Zhu, accepted the attached license on 2017-12-02 at 16:28. The student, Huangjian Zhu, submitted this Thesis for approval on 2017-12-02 at 16:56. This Thesis was approved for publication on 2017-12-04 at 12:41. DSpace SAF Submission Ingestion Package generated from Vireo submission #11813 on 2018-03-13 at 09:56:44 Made available in DSpace on 2018-03-13T15:25:22Z (GMT). No. of bitstreams: 2 ZHU-THESIS-2017.pdf: 3174604 bytes, checksum: c14b158378743238b61142e7052b78d5 (MD5) LICENSE.txt: 4210 bytes, checksum: c7b95ae00c039efc5bfa04f3fedc5cc9 (MD5) Previous issue date: 2017-12-04 Embargo set by: Seth Robbins for item 105187 Lift date: 2020-03-13T15:25:40Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 105187 Lift date: 2020-03-13T15:28:52Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 105187 on 2020-03-14T09:15:08Z. application/pdf http://hdl.handle.net/2142/99224 en Copyright 2017 Huangjian Zhu Unmanned aerial vehicle Light Detection and Ranging (LiDAR) Remote sensing Point cloud Crop height Development of UAV-based lidar crop height mapping system text text Engineering Administration Agricultural & Biological Engr University of Illinois at Urbana-Champaign Thesis M.S.