张宏鸣,谭紫薇,韩文霆,朱珊娜,张姝茵,葛晨宇.基于无人机遥感的玉米株高提取方法[J].农业机械学报,2019,50(5):241-250.
ZHANG Hongming,TAN Ziwei,HAN Wenting,ZHU Shanna,ZHANG Shuyin,GE Chenyu.Extraction Method of Maize Height Based on UAV Remote Sensing[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(5):241-250.
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基于无人机遥感的玉米株高提取方法   [下载全文]
Extraction Method of Maize Height Based on UAV Remote Sensing   [Download Pdf][in English]
投稿时间:2019-01-25  
DOI:10.6041/j.issn.1000-1298.2019.05.028
中文关键词:  玉米株高  遥感  无人机  数码正射影像  数字表面模型
基金项目:国家重点研发计划项目(2017YFC0403203)、国家自然科学基金项目(41771315)、宁夏自治区重点研发计划项目(2017BY067)和欧盟地平线2020研究与创新计划项目(GA:635750)
作者单位
张宏鸣 西北农林科技大学 
谭紫薇 西北农林科技大学 
韩文霆 西北农林科技大学 
朱珊娜 西北农林科技大学 
张姝茵 西北农林科技大学 
葛晨宇 西北农林科技大学 
中文摘要:为在玉米生长周期内,准确、快速地掌握玉米生长信息,通过无人机获取玉米生长阶段4期不同高清数码正射影像(Digital orthophoto map, DOM)及数字表面模型(Digital surface model,DSM),利用K-means算法、遗传神经网络算法和骨架算法分别对DOM中的玉米区域进行提取,生成掩膜,与DSM套和,获取玉米高度信息。与实地测量株高进行对比,3种方法的R2分别为0.853、0.877、0.923,RMSE分别为15.886、14.519、11.493cm,MAE分别为13.743、11.884、8.927cm。结果表明:结合DOM和DSM可以较好地提取生长阶段的玉米高度。与K-means算法、遗传神经网络算法相比,基于骨架算法提取玉米高度具有一定优势,且精度较高。采用DOM和DSM相结合的骨架算法提取植株骨架,为株高提取提供了一种新途径,可为无人机遥感监测作物株高状况提供参考。
ZHANG Hongming  TAN Ziwei  HAN Wenting  ZHU Shanna  ZHANG Shuyin  GE Chenyu
Northwest A&F University,Northwest A&F University,Northwest A&F University,Northwest A&F University,Northwest A&F University and Northwest A&F University
Key Words:maize height  remote sensing  UAV  digital orthophoto map  digital surface model
Abstract:In order to accurately and quickly grasp the growth information of maize in the growth cycle, different digital orthophoto maps(DOM)and digital surface model (DSM) in the four stages of the nutritional growth stage of maize were obtained by unmanned aerial vehicle(UAV). K-means, genetic neural network and skeleton algorithm were used to extract the maize areas in the DOM, generate masks, and combined with DSM sets to obtain the height information of maize. Compared with the field measurement of plant height, the R2 of three methods were 0.853, 0.877 and 0.923, respectively, RMSE were 15.886cm, 14.519cm and 11.493cm, respectively, MAE were 13.743cm, 11.884cm and 8.927cm, respectively. The results showed that combining DOM and DSM can better extract the height value of maize in the nutritional growth stage. Compared with K-means and genetic neural network, the maize height extracted by the skeleton algorithm was highly consistent with the field measurement (R2 was 0.923, RMSE was 11.493cm, MAE was 8.927cm), and the extraction accuracy was high. Skeleton extraction combining DOM and DSM provided a way to extract plant height, which can be used as a reference for monitoring maize height by UAV remote sensing.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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