Research of Geomatric and Radiation Correction of the Hyperspectral Imaging System Carried by a Multi-rotor Unmanned Aerial Vehicle

Rui ZHOU; Yi OU; Bao YU; Qian WANG

doi:10.13718/j.cnki.xdzk.2019.09.018

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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.

Corresponding author: Yi OU ;

Received Date: 20/08/2018

Available Online: 20/09/2019

Key words:

hyperspectral remote sensing /
multi-rotor unmanned aerial vehicle (UAV) /
radiometric calibration /
geometric correction /
imaging spectrometer

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.

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高光谱遥感技术广泛应用于农林、生态环境等^[1-3]方面，如作物监测、产量预测^[4-5]和环境监测，并根据特征波段反演植被冠层的含水量、叶绿素和氮等物理参数^[6].目前，高光谱遥感一般是将传感器安装在载人飞行器上或有限的航天平台上.相比星载高光谱成像系统的质量和精度而言，机载高光谱影像具有很高的空间和光谱分辨率等优势，而且相较于星载而言具有灵活、运营成本低等特点^[7-10].但是，针对高性能的高光谱成像系统，如AVIRIS和HyMap^[11-12]机载可见光-近红外高光谱成像仪，此类均是搭载在载人飞行器上，而且载人飞行器很长时间才能安排调度，且成本费用较高，容易受天气干扰.此外，载人平台的提供商的时间调度困难.随着轻小型无人机(unmanned aerial vehicle，UAV)技术的发展，基于UAV的高光谱成像系统可以克服飞行器调度和飞行空域限制等难题^[13].那么就可以采用新的方式，使用按需定制的平台，在数小时内快速地完成高光谱数据^[15-16]的采集工作.

近年来，UAV飞行技术在军事、摄影测量和倾斜摄影等方面应用较为成熟.到目前为止，相关研究领域已经将UAV、旋翼或固定翼无人机平台与视频、多频带数字相机、量测相机、合成孔径雷达(synthetic aperture radar，SAR)和激光扫描等中的某一种或多种配合使用^[17-20].同时，也有很多无人机载高光谱成像系统的研究，主要有框幅式和推扫式，然而，很少有研究成功测试了轻小型、旋翼或固定翼无人机上搭载推扫式高光谱传感器^[21-22].而且，现在很多科研院所购置的成像光谱仪仅用于地面高光谱的研究，失去了高光谱遥感本质上的意义.因此，本研究提出了一种地面成像光谱仪、车载全球定位系统(global positioning system，GPS)和惯性测量单元(inertial measurement unit，IMU)与多旋翼无人机集成的低成本线阵推扫式高光谱遥感成像系统.因高光谱遥感成像系统需要经过辐射和几何校正才能进行定量的科学分析，本研究通过实验测试并评价分析此无人机载高光谱成像系统所采集高光谱图像的辐射校准和几何校正的精度.

4. 结论

本研究从充分利用室内成像光谱仪、节约成本和轻便地获取高光谱遥感影像数据等角度考虑，基于机载POS的航测原理，将价格便宜的GPS-IMU和小型的成像光谱仪紧凑地集成于多旋翼无人机上采集合格高光谱数据.研究通过增加三轴自稳云台以减小UAV自身机械振动所产生的测量误差，从而能获取更准确的姿态、位置和光谱信息.利用测量的辅助数据对高光谱图像进行辐射定标、大气校正和几何校正等预处理工作，并从辐射和几何两个方面分析评价UAV高光谱成像系统的可靠性.实验结果表明，组合GPS-IMU和高光谱成像设备通过三轴自稳云台挂载于多旋翼UAV上采集的高光谱影像数据可靠，系统操作灵活便捷；而且，辐射和几何精度均可满足研究和应用的需求，达到了节约成本和现有设备综合利用的目的.

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Research of Geomatric and Radiation Correction of the Hyperspectral Imaging System Carried by a Multi-rotor Unmanned Aerial Vehicle

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