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Modeling the land surface reflectance for optical remote sensing data in rugged terrain

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Abstract

A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented. Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively, the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model. A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper. The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.

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References

  1. Chen Y, Hall A, Liou K N. Application of three-dimensional solar radiative transfer to mountains. J Geophys Res, 2006, 111, D21111, doi: 10.1029/2006JD007163

  2. Holben B N, Jusice C O. The topographic effect on spectral response from nadir-pointing sensors. Photogram Eng Remote Sensing, 1980, 46:1191–1200

    Google Scholar 

  3. Holben B N, Jusice C O. An examination of spectral band ratio to reduce the topographic effect on remotely-sensed data. Int J Remote Sensing, 1981, 2: 115–123

    Article  Google Scholar 

  4. Smith J A, Lin T L, Ranson K J. The Lambertian assumption and Landsat data. Photogram Eng Remote Sensing, 1980, 46: 1183–1189

    Google Scholar 

  5. Teilet P M, Guindon B, Goodenough D G. On the slope-aspect correction of multispectral scanner data. Canada J Remote Sensing, 1982, 8(2): 84–106

    Google Scholar 

  6. Gu D, Gillespie A. Topographic normalization of Landsat TM images of forest based on subpixel Sun-Canopy-Sensor geometry. Remote Sensing Environ, 1998, 64: 166–175

    Article  Google Scholar 

  7. Dymond J R, Shepherd J D. Correction of the topographic effect in remote sensing. IEEE Trans Geosci Remote Sensing, 1999, 37(5): 2618–2620

    Article  Google Scholar 

  8. Soenen S A, Peddle D R, Coburn C A. SCS+C: A modified Sun-Canopy-Sensor topographic Correction in forested terrain. IEEE Trans Geosci Remote Sensing, 2005, 43(9): 2148–2159

    Article  Google Scholar 

  9. Kumar L, Skidmore A K, Knowles E. Modeling Topographic Variation in Solar Radiation in a GIS Environment. Int J Geogr Information Sci, 1997,11(5): 475–497

    Article  Google Scholar 

  10. Proy C, Tanre D, Deschamps P Y. Evaluation of topographic effects in remotely sensed data. Remote Sensing Environ, 1989, 30: 21–32

    Article  Google Scholar 

  11. Gratton D J, Howarth P J, Marceau D J. Using Landsat-5 Thematic Mapper and Digital Elevation Data to Determine the Net Radiation Field of a Mountain Glacier. Remote Sensing Environ, 1993, 43: 315–331

    Article  Google Scholar 

  12. Duguay C R, Ledrew E F. Estimating surface reflectance and albedo from Landsat-5 Thematic Mapper over rugged terrain. Photogram Remote Sensing, 1992, 58(5): 551–558

    Google Scholar 

  13. Sandmeier S, Itten K I. A physically-based model to correct atmospheric and illumination effects in optical satellite data of rugged terrain. IEEE Trans Geosci Remote Sensing,1997, 35(3): 708–717

    Article  Google Scholar 

  14. Richter R, Correction of atmospheric and topographic effects for high spatial resolution satellite imagery. Int J Remote sensing, 1997, 18(5): 1099–1111

    Article  Google Scholar 

  15. Richter R, Schläpfer D. Geo-atmospheric processing of airborne imaging spectrometry data: Part 2. Atmospheric/topographic correction. Int J Remote Sensing, 2002, 23(13): 2631–2649

    Article  Google Scholar 

  16. Wang J, White K, Robinson G J. Estimating surface net solar radiation by use of Landsat-5 TM and digital elevation models. Int J Remote Sensing, 2000, 21(1): 31–43

    Article  Google Scholar 

  17. Shepherd J D, Dymond J R. Correcting satellite imagery for the variance of reflectance and illumination with topography. Int J Remote Sensing, 2003, 24(17): 3503–3514

    Article  Google Scholar 

  18. Yan G J, Zhu C G, Guo J, et al. A model based radiative transfer algorithm to correct remotely sensed image in mountainous area. J Image Graphics (in Chinese), 2000, 5:11–15

    Google Scholar 

  19. Beisl U. Correction of bidirectional effects in imaging spectrometer data. Remote Sensing Ser 37, Department of Geography, University of Zurich, 2001. 24–38

  20. Gutman G. Normalization of multi-annual global AVHRR reflectance data over land surfaces to common sun-target-sensor geometry. Adv Space Res, 1994, 14: 121–124

    Article  Google Scholar 

  21. Wu A, Li Z, Cihlar J. Effects of land cover type and greenness on advanced very high resolution radiometer bidirectional reflectance: Analysis and removal. J Geophys Res, 1995, 100: 9179–9192

    Article  Google Scholar 

  22. Wen J, Liu Q, Xiao Q, et al. A semi-empirical model for topographic/atmospheric correction in Jiangxi rugged area, China. In: Maitre H, Sun H, Liu J B, eds. Proceedings of SPIE, Nov.15–7, 2007, Wuhan. Bellingham, USA: SPIE, 2007, 6787: 678721-1–678721-9

    Google Scholar 

  23. Nicodemus F, Richmond J, Hsia J, et al. Technical Report, Geometrical Considerations and Nomenclature for Reflectance, NBS, US Department of Commerce, Washington, D.C., 1977

    Google Scholar 

  24. Walthall G L, Norman J M, Welles J M, et al. Simple eq. to approximate the bi-directional reflectance from vegetative canopies and bare soil surfaces. Appl Optics, 1985, 24(3): 383–387

    Article  Google Scholar 

  25. Liang S L, Strahler A H. Retrieval of Surface BRDF from Multiangle Remotely Sensed Data. Remote Sensing Environ, 1994, 50: 18–30

    Article  Google Scholar 

  26. Danaher T, Wu X l, Campbell N. Bidirectional reflectance distribution function approaches to radiometric calibration of Landsat ETM+ Imagery. Geosci and Remote Sensing Sym, 2001, 6: 2654–2657

    Google Scholar 

  27. Danaher T. An empirical BRDF correction for Landsat TM and ETM+ imagery. In: Proceedings of the 11th Australasian Remote Sensing and Photogrammetry Conference, Brisbane, Australia, 2002

  28. Li X, Strahler A H. Geometric-Optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of crown shape and mutual shadowing. IEEE Trans Geosci Remote Sensing, 1992, 30(2): 276–292

    Article  Google Scholar 

  29. Wen J G, Liu Q H, Xiao Q. Assessment of Different Topographic Correction Methods and Validation. J Beijing Normal Univ (Natural Science) (in Chinese), 2007, 43(3): 255–263

    Google Scholar 

  30. Gyanesh C, Brian M. Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Trans Geosci Remote Sensing, 2003, 41(11): 2674–2677

    Article  Google Scholar 

Download references

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Correspondence to JianGuang Wen.

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Supported in part by the National Natural Science Foundation of China (Grant No. 40730525), Knowledge Innovation Engineering Project of Chinese Academy of Sciences (Grant No. KZCX2-YW-313) and China’s Special Funds for Major State Basic Research Project (Grant No. 2007CB714401)

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Wen, J., Liu, Q., Xiao, Q. et al. Modeling the land surface reflectance for optical remote sensing data in rugged terrain. Sci. China Ser. D-Earth Sci. 51, 1169–1178 (2008). https://doi.org/10.1007/s11430-008-0085-5

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  • DOI: https://doi.org/10.1007/s11430-008-0085-5

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