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Remote Sensing for Land & Resources    2019, Vol. 31 Issue (2) : 66-72     DOI: 10.6046/gtzyyg.2019.02.10
Atmospheric radiation correction of airborne hyperspectral image by adding elevation factor
Piyuan YI, Hanbo LI, Peng TONG, Yingjun ZHAO, Chuan ZHANG, Feng TIAN, Yongfei CHE, Wenhuan WU
National Key Laboratory of Remote Sensing Information and Image Analyzing Technology, Beijing Research Institute of Uranium Geology, Beijing 100029, China
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Topographic effect is one of the main obstacles in quantitative analysis of remote sensing. For the airborne hyperspectral remote sensing, both of the impact of terrain height and angle can’t be ignored, and this causes more severe topographic effects. By taking the CASI image and LiDAR data of Qinghai Province as experimental data, the impact of elevation factor was analyzed in this paper. Firstly, on the premise that each elevation point is a horizontal Lambert body, four different elevation values were taken as reference to calculate the corresponding atmospheric radiation correction parameters by performing MODTRAN, which contain path radiance,atmospheric transmittance between the object and the sensor, atmospheric hemisphere albedo, and total downward radiance. Then an atmospheric radiation correction method with elevation factor was designed and applied to the atmospheric correction of CASI image. Finally, the CASI hyperspectral image was also processed by using FLAASH, which could only take one elevation value as reference. A comparison of two results shows that the reflectance spectrum shapes of the same ground objects are roughly the same,but the reflectance values are different. Especially, the short-wavelength reflectance values of FLAASH results are negative, and it is undoubtedly wrong. The experiment shows that the impact of elevation factors can’t be neglected. Atmospheric correction by adding elevation factors can get better results. For achieving accurate topographic correction of airborne hyperspectral image, both elevation and topographic angle factors should be considered simultaneously.

Keywords topographic effect      elevation      hyperspectral      atmospheric correction     
:  TP79  
Issue Date: 23 May 2019
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Piyuan YI
Hanbo LI
Yingjun ZHAO
Yongfei CHE
Wenhuan WU
Cite this article:   
Piyuan YI,Hanbo LI,Peng TONG, et al. Atmospheric radiation correction of airborne hyperspectral image by adding elevation factor[J]. Remote Sensing for Land & Resources, 2019, 31(2): 66-72.
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CASI-1500参数 参数数值 ALTM Gemini参数 参数数值
光谱范围/nm 3801 050 作业高度范围/m 1 5004 000
每行像元数 1 474 激光波长/nm 1 064
连续光谱通道数 288 波束角/mrad 0.3
光谱带宽/nm 2.4 平面精度 1/5 500×
帧频(全波段) 14
焦距/ mm 41.2 高程精度/cm 535
垂直航线方向视场角/(°) 40 激光脉冲频率/kHz 33167
扫描频率/Hz 070
沿航线方向瞬时视场角/mRad 0.49 视场角/(°) ±25
侧滚补偿/(°) ±5
绝对辐射测量精度 <2% 回波接收能力/次 4
信噪比(峰值) >1 100
量化水平/bit 14 量化水平/bit 12
Tab.1  Specification of CASI hyperspectral sensor and ALTM Gemini LiDAR
Fig.1  Data of the study area
地面高程/m 地表反射率 传感器高度/m
3 500 0 6 900
0.1 6 900
0.2 6 900
0.1 3 501
0.2 3 501
Tab.2  Input parameters
Fig.2  Structure of look-up table
Fig.3  Path radiation corresponding to different elevation
Fig.4  Atmospheric transmittance of different elevation to sensor
Fig.5  Atmospheric hemisphere albedo corresponding to different elevation
Fig.6  Downward radiance received at different elevation
Fig.7  Distribution of selected ground objects
Fig.8  Reflectance comparison of different methods
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