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Journal of Zhejiang University SCIENCE A 2006 Vol.7 No.4 P.641~646


Refined empirical line method to calibrate IKONOS imagery

Author(s):  Xu Jun-feng, Huang Jing-feng

Affiliation(s):  Institute of Agricultural Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310029, China

Corresponding email(s):   hjf@zju.edu.cn

Key Words:  Calibration, Refined empirical line (REL) method, IKONOS

Xu Jun-feng, Huang Jing-feng. Refined empirical line method to calibrate IKONOS imagery[J]. Journal of Zhejiang University Science A, 2006, 7(4): 641~646.

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author="Xu Jun-feng, Huang Jing-feng",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%T Refined empirical line method to calibrate IKONOS imagery
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%A Huang Jing-feng
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%I Zhejiang University Press & Springer
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T1 - Refined empirical line method to calibrate IKONOS imagery
A1 - Xu Jun-feng
A1 - Huang Jing-feng
J0 - Journal of Zhejiang University Science A
VL - 7
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SP - 641
EP - 646
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Y1 - 2006
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2006.A0641

To extract quantitative biophysical parameters such as leaf biomass and leaf chlorophyll concentration from the remotely sensed imagery, the effect of atmospheric attenuation must be removed. The refined empirical line (REL) method was used to calibrate the IKONOS multispectral imagery. The IKONOS digital numbers (DN) were converted to the at-satellite reflectance, then the linear relation between at-satellite reflectance and surface spectral reflectance (ρλ) was derived from six bright targets of known reflectance in the image, and modelled estimates of the image reflectance at ρλ=0. Validation targets were used to test the feasibility of REL method. The mean relative errors between ρλ retrieved from IKONOS image using REL method and ground-measured ρλ were 11%, 13%, 3% and 5% in the IKONOS blue, green, red and near-infrared (NIR) respectively. When dark targets are unavailable or measurement of dark target is inconvenient, the REL method was most crucial for retrieving surface spectral reflectance. The REL offers a simple approach for quantitative retrieval of biophysical parameters from IKONOS imagery.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1] Ben-Dor, E., Levin, N., 2000. Determination of surface reflectance from raw hyperspectral data without simultaneous ground data measurements: a case study of the GER 63-channel sensor data acquired over Naan, Israel. International Journal of Remote Sensing, 21(10):2053-2074.

[2] Berk, A., Bernstein, L.S., Anerson, G.P., Acharya, P.K., Roberston, D.C., Chetwynd, J.H., Adler-Golden, S.M., 1998. MODTRAN cloud and multiple scattering upgrades with application to AVIRIS. Remote Sensing of Environment, 65(3):367-375.

[3] Farrand, W.H., Singer, R.B., Merenyi, E., 1994. Retrieval of apparent surface reflectance from AVIRIS data: a comparison of empirical line, radiative transfer, and spectral mixture methods. Remote Sensing of Environment, 47(3):311-321.

[4] Ferrier, G., 1995. Evaluation of apparent surface reflectance estimation methodologies. International Journal of Remote Sensing, 17(12):2291-2297.

[5] Fleming, D., 2003. Ikonos DN Value Conversion to Planetary Reflectance. Http://www.geog.umd.edu/cress/papers/ guide_dn2pr.pdf.

[6] Karpouzli, E., Malthus, T., 2003. The empirical line method for the atmospheric correction of IKONOS imagery. International Journal of Remote Sensing, 24(5):1143-1150.

[7] Kneizys, F.X., Shettle, E.P., Abreu, L.W., Chettwynd, J.H., Anderson, G.P., Gallery, W.O., Selby, J.E.A., Clough, S.A., 1989. User Guide to Lowtran 7. Hanscom AFB, Massachusetts, p.146.

[8] Kruse, F.A., 1988. Use of airborne imaging spectrometer data to map minerals associated with hydrothermally altered rocks in the northern Grapenvine Mountains, Nevada and California. Remote Sensing of Environment, 24(1):31-51.

[9] Matthew, M.W., Adler-Golden, S.M., Berk, A., Felde, G., Anderson, G.P., Gorodetzky, D., Paswaters, S., Shippert, M., 2002. Atmospheric Correction of Spectral Imagery: Evaluation of the FLAASH Algorithm with AVIRIS Data. Proceedings of 31st Applied Imagery Pattern Recognition Workshop. Bellingham, WA, p.157-163.

[10] Moran, M.S., Bryanta, R., Thomeb, K., Nia, W., Nouvellona, Y., 2001. A refined empirical line approach for reflectance factor retrieval from Landsat-5 TM and Landsat-7 ETM+. Remote Sensing of Environment, 78(1-2):71-82.

[11] Perry, E.M., Warner, T., Foote, P., 2000. Comparison of atmospheric modelling versus empirical line fitting for mosaicking HYDICE imagery. International Journal of Remote Sensing, 21(4):799-803.

[12] Richter, R., Schläpfer, D., 2002. Geo-atmospheric processing of airborne imaging spectrometry data: Part 2. Atmospheric/topographic correction. International Journal of Remote Sensing, 23(13):2631-2649.

[13] Roger, N., Gregg, A., 2002. Surface Reflectance Calibration of Terrestrial Imaging Spectroscopy Data: a Tutorial Using AVIRIS. Http://popo.jpl.nasa.gov/docs/workshops/02_ docs/ 2002_Clark_web.pdf.

[14] Smith, G.M., Milton, E.J., 1999. The use of the empirical line method to calibrate remotely sensed data to reflectance. International Journal of Remote Sensing, 20(13):2653-2662.

[15] Tanre, D., 1990. Description of a computer code to simulate the satellite signal in the solar spectrum: 5S code. International Journal of Remote Sensing, 11(4):659-668.

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