A spatially adaptive fast atmospheric correction algorithm

International Journal of Remote Sensing

Volumn 17, Issue 6, 1996, Pages 1201-1214

  Richter, R ^a  

^a GERMAN AEROSPACE CENTER DLR   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ATMOSPHERIC CORRECTION; HAZE; LOOK-UP TABLES; TM DATA;

ALGORITHMS; ATMOSPHERIC AEROSOLS; ATMOSPHERIC HUMIDITY; ATMOSPHERIC PRESSURE; ATMOSPHERIC TEMPERATURE; CLOUDS; COMPUTER SIMULATION; REFLECTION; TABLE LOOKUP;

ATMOSPHERIC CONDITIONS; ATMOSPHERIC CORRECTION; AUTOMATIC PHASE; DIGITAL NUMBER; GROUND BRIGHTNESS TEMPERATURE IMAGE; GROUND REFLECTANCE IMAGE; HAZE; HISTOGRAM MATCHING; INTERACTIVE PHASE; LANDSAT THEMATIC MAPPER;

OPTICAL SENSORS;

EID: 0029667637     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431169608949077     Document Type: Article

References (40)

1. Anding, D., and Kauth, R., 1970, Estimation of sea surface temperature from space. Remote Sensing of Environment, 1, 217-220.
2. Barton, I. J., 1983, Dual channel satellite measurements of sea surface temperature. Quarterly Journal of the Royal Meteorological Society, 109, 365-378.
3. Berk, A., Bernstein, L. S., and Robertson, D. C., 1989, MODTRAN: a moderate resolution model for LOWTRAN 7, GL-TR-89-0122, Geophysics Laboratory, Bedford, MA, U.S.A.
4. Buettner, K. J. K., and Kern, C. D, 1965, The determination of infrared emissivities of terrestrial surfaces. Journal of Geophysical Research, 70, 1329-1337.
5. Crist, E. P., and Cicone, R. C., 1984, A physically based transformation of Thematic Mapper data-the Tasseled Cap. I.E.E.E. Trans. Geoscience Remote Sensing, 22, 256-263.
6. Dave, J. V., 1980, Effect of atmospheric conditions on remote sensing of a surface nonhomogeneity. Photogrammetric Engineering and Remote Sensing, 46, 1173-1180.
7. EOSAT, 1986, Landsat Technical Notes (August 1986), Lanham, MD.
8. Gao, B. C., Heidebrecht, K. B., and Goetz, A. F. H., 1993, Derivation of scaled surface reflectances from AVIRIS data. Remote Sensing of Environment, 44, 165-178.
9. Goetz, A. F.H., Gao, B. C, Wessman, C. A., and Bowman, W.D., 1990, Estimation of biochemical constituents from fresh, green leaves by spectrum matching techniques. Proceedings of the International Geoscience and Remote Sensing Symposium, (IGARSS’90), College Park, MD, May 1990, vol. 2 (New York: I.E.E.E.), pp. 971-974.
10. Goetz, A. F. H., and Davis, C. O., 1991, High Resolution Imaging Spectrometer (HIRIS): science and instrument, International Journal of Imaging Systems and Technology, 3, 131-143.
11. Goetz, A. F. H., 1992, Imaging spectrometry for earth remote sensing. In Imaging Spectroscopy: Fundamentals and Prospective Applications, edited by F. Toselli and J. Bod. (Dordrecht/Boston/London: Kluwer), pp. 1-19.
12. Green, R. O., 1992, Retrieval of reflectance from calibrated radiance imagery measured by the airborne visible/infrared imaging spectrometer (AVIRIS) for lithological mapping of the Clark Mountains, California, Imaging Spectroscopy: Fundamentals and Prospective Applications, edited by F. Toselli and J. Bod. (Dordrecht/Boston/London: Kluwer), pp. 61-71.
13. Huete, A. R., 1987, Soil and sun angle interactions on partial canopy spectra. International Journal of Remote Sensing, 8, 1307-1317.
14. Isaacs, R. G., Wang, W, C., and Goldenberg, S., 1987, Multiple scattering LOWTRAN and FASCODE models. Applied Optics, 26, 1272-1281.
15. ISRO, 1988, Indian Space Research Organization. IRS Newsletter, May, Ahmedabad, India.
16. Kattenborn, G., 1991, Atmospharenkorrektur von multispektralen Satellitendaten fiir forstliche Anwendungen. PhD thesis, University of Freiburg, Germany.
17. Kaufman, Y. J., 1985, The atmospheric effect on the separability of field classes measured from satellites. Remote Sensing of Environment, 18, 21-34.
18. Kaufman, Y. J., and Sendra, C., 1988, Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery. International Journal of Remote Sensing, 9, 1357-1381.
19. Kaufmann, H, Meissner, D., Bodechtel, J., and Behr, F.J., 1989, Design of spectral and panchromatic bands for the German MOMS-02 sensor. Photogrammetric Engineering and Remote Sensing, 55, 875-881.
20. Kneizys, F. X., Shettle E. P., Abreu, L. W., et at, 1988, Users Guide to LOWTRAN 7, AFGL-TR-88-0177. Air Force Geophysics Laboratory, Bedford, MA, U.S.A.
21. Kruse, F. A., Lefkoff, A. B., Boardman, J.W et al, 1993, The Spectral Image Processing System (SIPS)-interactive visualization and analysis of imaging spectrometer data. Remote Sensing of Environment, 44, 145-163.
22. Markham, B. L., and Barker, J. L., 1985, Spectral characterization of the Landsat Thematic Mapper sensors. International Journal of Remote Sensing, 6, 697-716.
23. Metzlfr, M. D., and Malila, W. A., 1985, Characterization of Landsat-4 and Landsat-5 Thematic Mapper Data. Photogrammetric Engineering and Remote Sensing, 51, 1315-1330.
24. NASA, 1987, HIRIS, High-Resolution Imaging Spectrometer: science opportunities for the 1990s, Earth Observing System, Instrument Panel Report V. lie, National Aeronautics and Space Administration, Washington, DC, U.S.A.
25. Pearce, W. A., 1977, A study of the effects of the atmosphere on Thematic Mapper observations. NASA Contract NAS5-23639.
26. Popp, T, 1993, Korrektur der atmospharischen Maskierung zur Bestimmung der spektralen Albedo von Landoberflachen aus Satellitendaten. PhD thesis, University of Munich, Germany.
27. Price, J. C., 1989, Calibration comparison for the Landsat 4 and 5 multispectral scanners and thematic mappers. Applied Optics, 28, 465-471.
28. Research Systems, Inc., 1992, IDL User’s Guide Version 3.0. Boulder, CO, U.S.A.
29. Richter, R., and Lehmann, F., 1989, MOMS-02 sensor simulation and spectral band selection, International Journal of Remote Sensing, 10, 1429-1435.
30. Richter, R., 1990, A fast atmospheric correction algorithm applied to Landsat TM images. International Journal of Remote Sensing, 11, 159-166.
31. Richter, R., 1991, Error bounds of a fast atmospheric correction algorithm for the Landsat thematic mapper and multispectral scanner bands. Applied Optics, 30, 4412-4417.
32. Richter, R, 1994a, Model SENSAT-5: Sensor - Atmosphere - Target. DLR-IB 552-01/94, DLR Wessling, Germany.
33. Richter, R, 1994 b, A Spatially-Adaptive Fast Atmospheric Correction Algorithm: ATCOR2 User Manual. DLR-IB 552-04/94, DLR Wessling, Germany.
34. Shettle, E. P., and Fenn, R. W., 1979, Models of the aerosols of the lower atmosphere and the effects of humidity variations on their optical properties. AFGL-TR-79-0214, Air Force Geophysics Laboratory, Bedford, MA, U.S.A.
35. Singh, S. M., 1988, Brightness temperature algorithms for Landsat Thematic Mapper Data. Remote Sensing of Environment, 24, 509-512.
36. Slater, P. N., Biggar, S. F., Holm, R. G., Jackson, R. D., Mao, Y., Moran, M. S., Palmer, J. M., and Yuan, B., 1987, Reflectance and radiance-based methods for the in-flight absolute calibration of multispectral sensors. Remote Sensing of Environment, 22, 11-37.
37. Tanre, D., Deschamps, P. Y., Duhaut, P., and Horman, M., 1987, Adjacency effect produced by the atmospheric scattering in Thematic Mapper data. Journal of Geophysics Research, 92, 12000-12006.
38. Tornow, C., 1993, AMOD - an atmospheric correction program for TM data using fractal methods to estimate the optical depth. Proceedings of Workshop on Atmospheric Correction of Landsat Imagery, Torrance (Los Angeles), CA, 29 June-1 July (Torrance, CA: Geodynamics Corp.) pp. 60-64.
39. Vane, G., et al, 1993, The airborne visible/infrared imaging spectrometer (AVIRTS). Remote Sensing of Environment, 44, 127-143.
40. Vane, G., and Goetz, A. F. H., 1993, Terrestrial imaging spectrometry: current status, future trends. Remote Sensing of Environment, 44, 117-126.