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Remote Sensing for Land & Resources    2019, Vol. 31 Issue (4) : 26-31     DOI: 10.6046/gtzyyg.2019.04.04
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Atmospheric correction of Worldview3 image based on FLAASH model
Ling CHEN, Li CHEN, Wei LI, Jianyu LIU
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China
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Abstract  

With the development of remote sensing technology, the remote sensing has been developed from qualitative application to quantitative application,and atmospheric correction is an important part of quantitative remote sensing research. In this study, the authors used the FLAASH model of ENVI software to conduct atmospheric correction for Worldview3, a satellite image with high spatial resolution and high spectral resolution, and then evaluated the method. Worldview3 data and ASD measurement spectral data of typical ground objects(saline-alkali land and diorite)in Lop Nur were obtained. Firstly, the DN value of Worldview3 was converted into radiation brightness and apparent reflectance, and the atmosphere correction of Worldview3 image was carried out by using FLAASH model. The radiation brightness, apparent reflectance and FLAASH atmospheric corrected reflectance of two typical ground objects (saline-alkali land and diorite) in the study area were comparatively studied, and the measured reflection spectra of saline-alkali and diorite by ASD were also compared after resampling to the response band of Worldview3 by Gaussian filtering function. The results show that it is effective to apply FLAASH model to atmospheric correction of Worldview3 data, and the two methods can obtain high coincidence degree of reflection spectrum, with the correlation coefficient reaching 0.8.
Keywords Worldview3 image      FLAASH model      atmospheric correction     
:  TP79  
Issue Date: 03 December 2019
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Ling CHEN
Li CHEN
Wei LI
Jianyu LIU
Cite this article:   
Ling CHEN,Li CHEN,Wei LI, et al. Atmospheric correction of Worldview3 image based on FLAASH model[J]. Remote Sensing for Land & Resources, 2019, 31(4): 26-31.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2019.04.04     OR     https://www.gtzyyg.com/EN/Y2019/V31/I4/26
波段号 波段名 光谱范
围/nm		 空间分
辨率/m		 位数/bit
全色 Panchromatic 450~800 0.5 11
1 Coast Blue 400~450 1.2
2 Blue 450~510 1.2
3 Green 510~580 1.2
4 Yellow 585~625 1.2
5 Red 630~690 1.2
6 Red Edge 705~745 1.2
7 NIR1 770~895 1.2
8 NIR2 860~1 040 1.2
9 SWIR1 1 195~1 225 7.5
10 SWIR2 1 550~1 590 7.5
11 SWIR3 1 640~1 680 7.5
12 SWIR4 1 710~1 750 7.5
13 SWIR5 2 145~2 185 7.5
14 SWIR6 2 185~2 225 7.5
15 SWIR7 2 235~2 285 7.5
16 SWIR8 2 295~2 365 7.5
Tab.1  Technical parameters of the remote sensing data used in this research
Fig.1  False color image composed of WV3 B8(R),B4(G),B3(B)in study area
序号 波段名 增益 偏差 中心波
长/nm		 波段宽
度/nm
1 Coast Blue 0.298 559 38 -7.07 425.00 50
2 Blue 0.305 176 06 -4.253 480.00 60
3 Green 0.199 247 59 -2.633 545.00 70
4 Yellow 0.172 458 2 -2.074 605.00 40
5 Red 0.241 242 09 -1.807 660.00 60
6 Red Edge 0.164 408 7 -2.633 725.00 40
7 NIR1 0.165 111 91 -3.406 832.50 125
8 NIR2 0.122 808 61 -2.258 950.00 180
9 SWIR1 0.012 376 451 -3.295 1 210.00 30
10 SWIR2 0.006 776 925 -1.496 1 570.00 40
11 SWIR3 0.006 506 7 -1.385 1 660.00 40
12 SWIR4 0.005 493 318 -1.009 1 730.00 40
13 SWIR5 0.002 801 196 -0.356 2 165.00 40
14 SWIR6 0.002 815 416 -0.353 2 205.00 40
15 SWIR7 0.002 442 118 -0.252 2 260.00 50
16 SWIR8 0.001 791 85 -0.167 2 330.00 70
Tab.2  Parameters of radiometric calibration for WV3 image
Fig.2  Comparison image before and after FLAASH atmospheric correction
Fig.3  Transverse section spectral comparison images before and after FLAASH atmospheric correction
Fig.4  WV3 image and field photos of diorite and saline-alkali soil in research area
Fig.5  Comparison of saline-alkali soil and diorite ASD spectra and WV3 reflectance after FLAASH
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