引用本文:周蕊, 欧毅, 虞豹, 王茜.多旋翼无人机载高光谱成像系统几何和辐射校正方法研究[J].西南大学学报(自然科学版),2019,41(9):141~147
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多旋翼无人机载高光谱成像系统几何和辐射校正方法研究
周蕊, 欧毅, 虞豹, 王茜
重庆市农业科学院农业科技信息中心, 重庆 400060
摘要:
针对农林环保等行业应用,结合成像光谱仪与无人机(unmanned aerial vehicle,UAV)技术,有效地解决了高光谱遥感数据不足和空间分辨率低等问题.但UAV高光谱成像系统面临的设备昂贵、数据质量差和效率低等一系列问题,致使低成本高效便捷的UAV高光谱成像系统成为了研究的关键.介绍了将室内成像光谱仪搭载在多旋翼UAV上采集数据的高光谱成像系统,在试验区布设控制点和标准灰布,用GPS-RTK测量控制点的三维坐标和ASD地物光谱仪测量标准灰布的反射率以验证系统的成像精度.从辐射和几何两个方面进行分析评价.在辐射方面,经过辐射定标和MODTRAN模型大气校正的高光谱数据中校准灰布的反射率与ASD地物光谱仪测量的结果十分吻合;在几何方面,用GPS-IMU数据进行初始几何校正的图像与地面控制点坐标以分析图像处理后的几何误差,并提出通过改正姿态偏转角的方法提高图像的地理位置精度.
关键词:  高光谱遥感  多旋翼无人机  辐射校准  几何校正  成像光谱仪
DOI:10.13718/j.cnki.xdzk.2019.09.018
分类号:TP7
基金项目:重庆市科技服务平台专项项目(cstc2015ptfw-ggfw80001);重庆市科技计划项目(cstc2017jxjl00014).
Research of Geomatric and Radiation Correction of the Hyperspectral Imaging System Carried by a Multi-rotor Unmanned Aerial Vehicle
ZHOU Rui, OU Yi, YU Bao, WANG Qian
Agricultural Science and Technology Information Center, Chongqing Academy of Agricultural Sciences, Chongqing 400060, China
Abstract:
For agriculture, forestry, environmental protection and other industrial applications, the technology of unmanned aerial vehicle (UAV) used in combination with imaging spectrometry has effectively solved the problems of insufficient data and low spatial resolution of hyperspectral remote sensing. But the UAV hyperspectral imaging system is facing a series of other problems, such as expensive equipment, poor data quality and low efficiency. Therefore, it is a key topic of research to develop a low-cost, efficient and convenient UAV hyperspectral imaging system. In this paper, we introduce a hyperspectral imaging system that collects the data of the indoor imaging spectrometer on a multi-rotor UAV. In the study reported herein, control points and standard gray cloths were set up in the test area, and the three-dimensional coordinates of the control points were measured with GPS-RTK and the reflectivity of the standard gray cloths was measured with the ASD feature spectrometer to verify the imaging accuracy of the system. The results of the test was analyzed and evaluated from the aspects of radiation and geometry. In radiation, the reflectivity of the calibrated gray cloth in the hyperspectral data corrected by the radiation calibration and the MODTRAN model was well consistent with that measured by the ASD feature spectrometer. The initial geometric correction of the image with GPS-IMU data and the ground control point coordinates were used to analyze the geometric error after the image processing. The authors recommended that the data accuracy of the geographical positions of the images be improved by correcting the attitude bias angle. In conclusion, this UAV hyperspectral imaging system improves the utilization of indoor imaging spectrometers, and the use of low-precision, low-cost imaging spectrometers and GPS-IMU to collect hyperspectral data is perfectly suited for industry applications.
Key words:  hyperspectral remote sensing  multi-rotor unmanned aerial vehicle (UAV)  radiometric calibration  geometric correction  imaging spectrometer
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