Laboratory calibration of a field imaging spectrometer system

Sensors

Volumn 11, Issue 3, 2011, Pages 2408-2425

  Zhang, Lifu ^a,b   Huang, Changping ^b,c   Wu, Taixia ^b   Zhang, Feizhou ^a   Tong, Qingxi ^b  

^a PEKING UNIVERSITY   (China)

^b INSTITUTE OF REMOTE SENSING APPLICATIONS   (China)

^c UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Calibration; Field imaging spectrometer system; FISS; Hyperspectral remote sensing; Imaging spectrometer

Indexed keywords

ARTICLE; CALIBRATION; INSTRUMENTATION; LABORATORY; METHODOLOGY; NORMAL DISTRIBUTION; RADIOMETRY; SIGNAL NOISE RATIO; SPECTROSCOPY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

CALIBRATION; IMAGING, THREE-DIMENSIONAL; LABORATORIES; LINEAR MODELS; NORMAL DISTRIBUTION; RADIOMETRY; SIGNAL-TO-NOISE RATIO; SPECTRUM ANALYSIS;

EID: 79953330025     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s110302408     Document Type: Article

References (40)

1. Goetz, A.F.H. Hyperspectral imaging and quantitative remote sensing. Land Satellite Information in the Next Decade; American Society for Photogrammetry & Remote Sensing(ASPRS): Bethesda, MD, USA, 1995; pp. E1-E10.
2. Goetz, A.F.H. Three decades of hyperspectral remote sensing of the earth: A personal view. Remote Sens. Environ. 2009, 113, S5-S16.
3. Goetz, A.F.H.; Vane, G.; Solomon, J.E.; Rock, B.N. Imaging Spectrometry for earth remote-sensing. Science 1985, 228, 1147-1153.
4. Tong, Q.; Zhang, B.; Zheng, L. Hyperspectral Remote Sensing-Principles, Techniques and Applications; Higher Education Press: Beijing, China, 2006; p. 40.
5. Chabrillat, S.; Goetz, A.F.H.; Krosley, L.; Olsen, H.W. Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution. Remote Sens. Environ. 2002, 82, 431-445.
6. Chang, C. Hyperspectral Imaging: Techniques for Spectral Detection and Classification; Springer: New York, NY, USA, 2003.
7. Wessman, C.; Aber, J.; Peterson, D.; Melillo, J. Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems. Nature 1988, 335, 154.
8. Castro-Esau, K.L.; Sanchez-Azofeifa, G.A.; Rivard, B.; Wright, S.J.; Quesada, M. Variability in leaf optical properties of Mesoamerican trees and the potential for species classification. Amer. J. Bot. 2006, 93, 517-530.
9. Cheng, Y.B.; Ustin, S.L.; Riano, D.; Vanderbilt, V.C. Water content estimation from hyperspectral images and MODIS indexes in Southeastern Arizona. Remote Sens. Environ. 2008, 112, 363-374.
10. Cheng, Y.B.; Zarco-Tejada, P.J.; Riano, D.; Rueda, C.A.; Ustin, S.L. Estimating vegetation water content with hyperspectral data for different canopy scenarios: Relationships between AVIRIS and MODIS indexes. Remote Sens. Environ. 2006, 105, 354-366.
11. Bruniquel-Pinel, V.; Gastellu-Etchegorry, J.P. Sensitivity of texture of high resolution images of forest to biophysical and acquisition parameters. Remote Sens. Environ. 1998, 65, 61-85.
12. Green, R.O.; Eastwood, M.L.; Sarture, C.M.; Chrien, T.G.; Aronsson, M.; Chippendale, B.J.; Faust, J.A.; Pavri, B.E.; Chovit, C.J.; Solis, M.S.; Olah, M.R.; Williams, O. Imaging spectroscopy and the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). Remote Sens. Environ. 1998, 65, 227-248.
13. Foody, G.M.; Cox, D.P. Sub-Pixel Land-Cover Composition Estimation Using a Linear Mixture Model and Fuzzy Membership Functions. Int. J. Remote Sens. 1994, 15, 619-631.
14. Borregaard, T. Crop-weed Discrimination by line imaging spectroscopy. J. Agr. Eng. Res. 2000, 75, 389-400.
15. Nicolai, B.M.; Lotze, E.; Peirs, A.; Scheerlinck, N.; Theron, K.I. Non-destructive measurement of bitter pit in apple fruit using NIR hyperspectral imaging. Postharvest Biol. Technol. 2006, 40, 1-6.
16. El Masry, G.; Wang, N.; El Sayed, A.; Ngadi, M. Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry. J. Food Eng. 2007, 81, 98-107.
17. Schuerger, A.; Capelle, G.; Di Benedetto, J.; Mao, C.; Thai, C.; Evans, M.; Richards, J.; Blank, T.; Stryjewski, E. Comparison of two hyperspectral imaging and two laser-induced fluorescence instruments for the detection of zinc stress and chlorophyll concentration in bahia grass (Paspalum notatum Flugge). Remote Sens. Environ. 2003, 84, 572-588.
18. Kruse, F.A. Identification and mapping of minerals in drill core using hyperspectral image analysis of infrared reflectance spectra. Int. J. Remote Sens. 1996, 17, 1623-1632.
19. Pan, Z.H.; Healey, G.; Prasad, M.; Tromberg, B. Face recognition in hyperspectral images. IEEE Trans. Patt. Anal. Mach. Int. 2003, 25, 1552-1560.
20. Stamatas, G.N.; Southall, M.; Kollias, N. In vivo monitoring of cutaneous edema using spectral imaging in the visible and near infrared. J. Invest. Dermatol. 2006, 126, 1753-1760.
21. Liu, Y.N.; Xue, Y.Q.; Wang, J.Y.; Shen, M.M. Operational modular imaging spectrometer. Int. J. Infrar. Millim. Wave. 2002, 21, 9-13.
22. Zhang, B.; Wang, X.; Liu, J.; Zheng, L.; Tong, Q. Hyperspectral image processing and analysis system (HIPAS) and its applications. Photogramm. Eng. Remote Sens. 2000, 66, 605-610.
23. Huang, C.; Zhang, L.; Zhang, X.; Zheng, L.; Tong, Q. Study on discrimination of varieties of milk based on FISS Imaging spectral data. Spectrosc. Spectr. Anal. 2011, 31, in press.
24. Tong, Q.; Xue, Y.; Wang, J.; Zhang, L.; Fang, J.; Yang, Y.; Liu, X.; Qi, H.; Zheng, L.; Huang, C. Development and application of the field imaging spectrometer system. J. Remote Sens. 2010, 14, 409-422.
25. Liu, B.; Fang, J.Y.; Liu, X.; Zhang, L.F.; Zhang, B.; Tong, Q.X. Research on crop-weed discrimination using a field imaging spectrometer. Spectrosc. Spectr. Anal. 2010, 30, 1830-1833.
26. Geladi, P. Hyperspectral imaging: Calibration problems and solutions. Chemometr. Intell. Lab. Syst. 2004, 72, 209-217.
27. Teillet, P.; Fedosejevs, G.; Thome, K.; Barker, J. Impacts of spectral band difference effects on radiometric cross-calibration between satellite sensors in the solar-reflective spectral domain. Remote Sens. Environ. 2007, 110, 393-409.
28. Gao, B.; Montes, M.; Davis, C. Refinement of wavelength calibrations of hyperspectral imaging data using a spectrum-matching technique. Remote Sens. Environ. 2004, 90, 424-433.
29. Chen, H. Remote Sensing Calibration Systems: An Introduction; A. Deepak Publishing: Hampton, NH, USA, 1997.
30. Schmidt, M. A method for operational calibration of AVHRR reflective time series data. Remote Sens. Environ. 2008, 112, 1117-1129.
31. Devries, C.; Danaher, T.; Denham, R.; Scarth, P.; Phinn, S. An operational radiometric calibration procedure for the Landsat sensors based on pseudo-invariant target sites. Remote Sens. Environ. 2007, 107, 414-429.
32. Zama, T.; Saito, I. Calibration of absolute spectral radiance in UV and VUV regions by using synchrotron radiation. J. Electron Spectrosc. Relat. Ph. 2005, 144-147, 1087-1091.
33. Chander, G.; Markham, B.L.; Helder, D.L. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sens. Environ. 2009, 113, 893-903.
34. Dell'Endice, F.; Team, A. Calibration algorithms for an imaging spectrometer. 2009 IEEE Int. Geosci. Remote Sens. Symp. 2009, 1-5, 332-335.
35. Drake, N.A.; Mackin, S.; Settle, J.J. Mapping vegetation, soils, and geology in semiarid shrublands using spectral matching and mixture modeling of SWIR AVIRIS imagery. Remote Sens. Environ. 1999, 68, 12-25.
36. Aikio, M.; Tutkimuskeskus, V.T. Hyperspectral Prism-Grating-Prism Imaging Spectrograph; Technical Research Centre of Finland: Heinola, Finland, 2001.
37. Gao, B.C. An operational method for estimating signal to noise ratios from data acquired with imaging spectrometers. Remote Sens. Environ. 1993, 43, 23-33.
38. Healey, G.; Kondepudy, R. Radiometric CCD camera calibration and noise estimation. IEEE Trans. Patt. Anal. Mach. Int. 1994, 267-276.
39. Ortiz, A.; Oliver, G. Radiometric calibration of CCD sensors: Dark current and fixed pattern noise estimation. In Proceedings of 2004 IEEE International Conference on Robotics and Automation, New Orleans, LA, USA, 26 April-1 May 2004; Volumes 1-5, pp. 4730-4735.
40. Curran, P.; Dungan, J. Estimation of signal-to-noise: A new procedure applied to AVIRIS data. IEEE Trans. Geosci. Remote Sens. 2002, 27, 620-628.