农用无人机多传感器遥感辅助小麦育种信息获取

为实现小麦育种过程中大规模育种材料表型信息快速高通量获取,该文分别从无人机平台优选、农情信息采集传感器集成及数据处理与解析等方面开展研究,研发了一套农业多载荷无人机遥感辅助小麦育种信息获取系统。该系统基于多旋翼无人机平台,并集成高清数码相机、多光谱仪、热像仪等多载荷传感器,提出了无地面控制点条件下的无人机遥感数据几何精校正模型,实现多载荷遥感数据几何校正。该系统操控简便,适合农田复杂环境条件作业,能够高通量获取作物倒伏面积、叶面积指数、产量及冠层温度等育种关键表型参量,为研究小麦育种基因型与表型关联规律提供辅助支持。...

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Published in农业工程学报 Vol. 31; no. 21; pp. 184 - 190
Main Author 杨贵军 李长春 于海洋 徐波 冯海宽 高林 朱冬梅
Format Journal Article
LanguageChinese
Published 国家农业信息化工程技术研究中心,北京 100097%河南理工大学测绘与国土信息工程学院,焦作,454000%江苏里下河地区农业科学研究所/国家小麦改良中心扬州分中心,扬州,225007 2015
北京农业信息技术研究中心,北京 100097
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2015.21.024

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Summary:为实现小麦育种过程中大规模育种材料表型信息快速高通量获取,该文分别从无人机平台优选、农情信息采集传感器集成及数据处理与解析等方面开展研究,研发了一套农业多载荷无人机遥感辅助小麦育种信息获取系统。该系统基于多旋翼无人机平台,并集成高清数码相机、多光谱仪、热像仪等多载荷传感器,提出了无地面控制点条件下的无人机遥感数据几何精校正模型,实现多载荷遥感数据几何校正。该系统操控简便,适合农田复杂环境条件作业,能够高通量获取作物倒伏面积、叶面积指数、产量及冠层温度等育种关键表型参量,为研究小麦育种基因型与表型关联规律提供辅助支持。
Bibliography:11-2047/S
Yang Guijun, Li Changchun, Yu Haiyang, Xu Bo, Feng Haikuan, Gao Lin, Zhu Dongmei (1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. School of Surveying and Landing Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China; 4. Lixiahe Region Institute of Agricultural Sciences, Yangzhou Subcenter of National Wheat Improvement, Yangzhou 225007, China)
unmanned aerial vehicle(UAV); remote sensing; loads; crops; breeding; wheat
To realize rapid acquisition of massive phenotypic information of wheat breeding material, the studies on UAV(unmanned aerial vehicle) platform selection, sensor integration, and remote sensing data processing and analyses were carried out respectively, and a set of multi-load agricultural UAV based remote sensing system for assisting crop breeding information acquisition was developed. The speed and height of multi
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2015.21.024