سابِق|تال

Advances in topographic correction methods for optical remote sensing imageries

  • role： First author第一作者
  • Affiliation：

    College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China

  • Email：linxw@zjnu.edu.cn
  • Introduction：林兴稳，1989年生，男，讲师，研究方向为山区地表辐射传输建模与产品真实性检验。E-mail: linxw@zjnu.edu.cn
LIN Xingwen1,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：wenjg@aircas.ac.cn
  • Introduction：闻建光，1978年生，男，研究员，研究方向为遥感辐射传输建模与参数反演。E-mail: wenjg@aircas.ac.cn
WEN Jianguang23*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

WU Shengbiao2,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

HAO Dalei2,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

XIAO Qing23,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

LIU Qinhuo23

ملخص

Steep terrain produces serious topographic effects on remote sensing satellite imageries. Serious topographic effects cause difficulty in classifying vegetation species and retrieving key essential climate variables (such as albedo, Leaf Area Index, and fraction of absorbed photo synthetically active radiation). These effects also bring complexity in distinguishing the unhealthy change in land covers over rugged terrains. Topographic correction is necessary for remote sensing applications over mountainous areas. Researchers have attempted to remove or at least reduce topographic effects in remote sensing imageries by using various standard methodological algorithms. The background and the topographic correction model have been reviewed in former studies. However, several effective topographic correction models, which have high quality and have been newly developed during these years, have not been mentioned and recommended comprehensively. Therefore, topographic correction models and evaluation methods for optical remote sensing imageries from the presented research chain were reviewed comprehensively in this paper. The aim was to determine the potential effective solutions for topographic effect correction over rugged terrains. This study is important for quantitative remote sensing applications in mountainous areas.Topographic correction models have been explored for more than 30 years (Fig. 1). These models can be divided into three categories, namely, the regression model, the Lambertian-based model, and the non-Lambertian-based model. The regression model generally has obvious advantages of simplified formulation and easy operation. However, this model has the shortage of lack of physical meaning for empirical parameters. The Lambertian-based model has rigorous mathematical formulas, which have clear physical meaning for parameters and are easy to operate for reducing complex topographic effects. Meanwhile, the Lambertian models are built on the basis of several assumptions and have the obvious shortage of ignoring the non-Lambertian surface reflectance. This negligence may result in overcorrection, especially over shady surfaces. The non-Lambertian model can improve the performance of the Lambertian-based model, especially over heterogeneous land surfaces.On the basis of this study, we summarized the problems in existing topographic correction model and provided several possible suggestions for the development of a topographic correction model in optical remote sensing. These suggestions can provide important guidance to the research on topographic correction and its practical application.

مفهوم

remote sensing;image procession;Lambertian based model;Non-Lambertian model;land surface reflectance;topographic correction assessment

References

  1. 1.
    Adhikari H, Heiskanen J, Maeda E E and Pellikka P K E. 2016. The effect of topographic normalization on fractional tree cover mapping in tropical mountains: an assessment based on seasonal Landsat time series. International Journal of Applied Earth Observation and Geoinformation, 52: 20-31
  2. 2.
    Balthazar V, Vanacker V and Lambin E F. 2012. Evaluation and parameterization of ATCOR3 topographic correction method for forest cover mapping in mountain areas. International Journal of Applied Earth Observation and Geoinformation, 18: 436-450
  3. 3.
    Bishop M P and Colby J D. 2011. Topographic Normalization of Multispectral Satellite Imagery. Dordrecht: Springer
  4. 4.
    Chander G, Markham B L and Helder D L. 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113(5): 893-903
  5. 5.
    Chen J S. 1964. The spatial variation and distribution of surface reflectance over China. Acta Geographica Sinica, 30(2): 85-93
  6. 6.
    Civco D L. 1989. Topographic normalization of Landsat Thematic Mapper digital imagery. Photogrammetric Engineering and Remote Sensing, 55(9): 1303-1309
  7. 7.
    Colby J D. 1991. Topographic normalization in rugged terrain. Photogrammetric Engineering and Remote Sensing, 57(5): 531-537
  8. 8.
    Colby J D and Keating P L. 1998. Land cover classification using Landsat TM imagery in the tropical highlands: the influence of anisotropic reflectance. International Journal of Remote Sensing, 19(8): 1479-1500
  9. 9.
    Conese C, Gilabert M A, Maselli F and Bottai L. 1993. Topographic normalization of TM scenes through the use of an atmospheric correction method and digital terrain models. Photogrammetric Engineering and Remote Sensing, 59(12): 1745-1753
  10. 10.
    Dawn S, Saxena V and Sharma B. 2010. Remote sensing image registration techniques: a survey//Proceedings of the 4th International Conference on Image and Signal Processing. Trois-Rivières, QC, Canada: Springer: 103-112
  11. 11.
    Dozier J and Frew J. 1981. Atmospheric corrections to satellite radiometric data over rugged terrain. Remote Sensing of Environment, 11: 191-205
  12. 12.
    Dozier J and Frew J. 1990. Rapid calculation of terrain parameters for radiation modeling from digital elevation data. IEEE Transactions on Geoscience and Remote Sensing, 28(5): 963-969
  13. 13.
    Dozier J and Outcalt S I. 1979. An approach toward energy balance simulation over rugged terrain. Geographical Analysis, 11(1): 65-85
  14. 14.
    Duan S B and Yan G J. 2007. A review of models for topographic correction of remotely sensed images in mountainous area. Journal of Beijing Normal University (Natural Science), 43(4): 362-366
  15. 15.
    Duguay C R and LeDrew E F. 1992. Estimating surface reflectance and albedo from landsat-5 thematic mapper over rugged terrain. Photogrammetric Engineering and Remote Sensing, 58(5): 551-558
  16. 16.
    Dymond J R and Shepherd J D. 1999. Correction of the topographic effect in remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2618-2619
  17. 17.
    Ekstrand S. 1996. Landsat TM-based forest damage assessment: correction for topographic effects. Photogrammetric Engineering and Remote Sensing, 62(2): 151-162
  18. 18.
    Fan W L, Li J, Liu Q H, Zhang Q, Yin G F, Li A N, Zeng Y L, Xu B D, Xu X J, Zhou G M and Du H Q. 2018. Topographic correction of forest image data based on the canopy reflectance model for sloping terrains in multiple forward mode. Remote Sensing, 10(5): 717
  19. 19.
    Fan Y C, Koukal T and Weisberg P J. 2014. A sun–crown–sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 96: 94-105
  20. 20.
    Gao Y N and Zhang W C. 2009. A simple empirical topographic correction method for ETM+ imagery. International Journal of Remote Sensing, 30(9): 2259-2275
  21. 21.
    Ge H L, Lu D S, He S Z, Xu A J, Zhou G M and Du H Q. 2008. Pixel-based minnaert correction method for reducing topographic effects on a landsat 7 ETM+ image. Photogrammetric Engineering and Remote Sensing, 74(11): 1343-1350
  22. 22.
    Ghasemi N, Mohammadzadeh A and Sahebi M R. 2013. Assessment of different topographic correction methods in ALOS AVNIR-2 data over a forest area. International Journal of Digital Earth, 6(5): 504-520
  23. 23.
    Goslee S C. 2012. Topographic corrections of satellite data for regional monitoring. Photogrammetric Engineering and Remote Sensing, 78(9): 973-981
  24. 24.
    Gu D G and Gillespie A. 1998. Topographic normalization of landsat TM images of forest based on subpixel Sun-canopy-sensor geometry. Remote Sensing of Environment, 64(2): 166-175
  25. 25.
    Hay J E. 1979. Calculation of monthly mean solar radiation for horizontal and inclined surfaces. Solar Energy, 23(4): 301-307
  26. 26.
    Hay J E and McKay D C. 1985. Estimating solar irradiance on inclined surfaces: a review and assessment of methodologies. International Journal of Solar Energy, 3(4/5): 203-240
  27. 27.
    Holben B N and Justice C O. 1980. The topographic effect on spectral response from nadir-pointing sensors. Photogrammetric Engineering and Remote Sensing, 46(9): 1191-1200
  28. 28.
    Huang W, Zhang L P and Li P X. 2005. An improved topographic correction approach for satellite image. Journal of Image and Graphics, 10(9): 1124-1128
  29. 29.
    Huang W, Zhang L P and Li P X. 2006. A topographic correction approach for radiation of RS images by using spatial context information. Acta Geodaetica Et Cartographica Sinica, 35(3): 285-290
  30. 30.
    Itten K I and Meyer P. 1993. Geometric and radiometric correction of TM data of mountainous forested areas. IEEE Transactions on Geoscience and Remote Sensing, 31(4): 764-770
  31. 31.
    Jiang K，Hu C M，Yu K and Zhao Y C． 2014． Landsat TM/ETM + topographic correction method based on smoothed terrain and semi-empirical model． Journal of Remote Sensing，18(2) : 287- 306
  32. 32.
    Kobayashi S and Sanga-Ngoie K. 2008. The integrated radiometric correction of optical remote sensing imageries. International Journal of Remote Sensing, 29(20): 5957-5985
  33. 33.
    Kondratyev K J and Manolova M P. 1960. The radiation balance of slopes. Solar Energy, 4(1): 14-19
  34. 34.
    Lenot X, Achard V and Poutier L. 2009. SIERRA: a new approach to atmospheric and topographic corrections for hyperspectral imagery. Remote Sensing of Environment, 113(8): 1664-1677
  35. 35.
    Li F Q, Jupp D L B, Reddy S, Lymburner L, Mueller N, Tan P and Islam A. 2010. An evaluation of the use of atmospheric and brdf correction to standardize landsat data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(3): 257-270
  36. 36.
    Li F Q, Jupp D L B, Thankappan M, Lymburner L, Mueller N, Lewis A and Held A. 2012. A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sensing of Environment, 124: 756-770
  37. 37.
    Li H F, Xu L M, Shen H F and Zhang L P, 2016. A general variational framework considering cast shadows for the topographic correction of remote sensing imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 117: 161-171
  38. 38.
    Liang S, Fang H and Chen M. 2001. Atmospheric correction of landsat ETM+ land surface imagery. I. Methods. IEEE Transactions on Geoscience and Remote Sensing, 39(11): 2490-2498
  39. 39.
    Liang S L, Lewis P, Dubayah R, Qin W H and Shirey D. 1997. Topographic effects on surface bidirectional reflectance scaling. Journal of Remote Sensing, 1(S1): 90-93, 101
  40. 40.
    Liang S L, Fang H L, Morisette J T, Chen M Z, Shuey C J, Walthall C L and Daughtry C S T. 2002. Atmospheric correction of landsat ETM+ land surface imagery. II: validation and applications. IEEE Transactions on Geoscience and Remote Sensing, 40(12): 2736-2746
  41. 41.
    Lin Q N, Huang H G, Chen L and Chen E X. 2017. Topographic correction method for steep mountain terrain images. Journal of Remote Sensing, 21(5): 776-784
  42. 42.
    Meyer P, Itten K I, Kellenberger T, Sandmeier S and Sandmeier R. 1993. Radiometric corrections of topographically induced effects on landsat TM data in an alpine environment. ISPRS Journal of Photogrammetry and Remote Sensing, 48(4): 17-28
  43. 43.
    Mishra V D, Sharma J K, Singh K K, Thakur N K and Kumar M. 2009. Assessment of different topographic corrections in AWiFS satellite imagery of Himalaya terrain. Journal of Earth System Science, 118(1): 11-26
  44. 44.
    Mousivand A, Verhoef W, Menenti M and Gorte B. 2015. Modeling top of atmosphere radiance over heterogeneous non-lambertian rugged terrain. Remote Sensing, 7(6): 8019-8044
  45. 45.
    Park S H, Jung H S, Choi J and Jeon S. 2017. A quantitative method to evaluate the performance of topographic correction models used to improve land cover identification. Advances in Space Research, 60(7): 1488-1503
  46. 46.
    Proy C, Tanré D and Deschamps P Y. 1989. Evaluation of topographic effects in remotely sensed data. Remote Sensing of Environment, 30(1): 21-32
  47. 47.
    Qi X Y and Tian Q J. 2007. Modification of atmospheric correction model and surface reflectance retrieval from TM imagery in rugged terrain. Remote Sensing Information, (4): 3-8 (亓雪勇, 田庆久. 2007. 山地TM遥感影像大气辐射校正模型改进及地表反射率反演. 遥感信息, (4): 3-8) [10.3969/j.issn.1000-3177.2007.04.001]
  48. 48.
    Rahman H, Pinty B and Verstraete M M. 1993. Coupled surface-atmosphere reflectance (CSAR) model: 2.semiempirical surface model usable with NOAA advanced very high resolution radiometer data. Journal of Geophysical Research, 98(D11): 20791-20801
  49. 49.
    Reeder D H. 2002. Topographic Correction of Satellite Images: Theory and Application. Hanover: Dartmouth College: 5123-5123
  50. 50.
    Riano D, Chuvieco E, Salas J and Aguado I. 2003. Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types (2003). IEEE Transactions on Geoscience and Remote Sensing, 41(5): 1056-1061
  51. 51.
    Richter R. 1997. Correction of atmospheric and topographic effects for high spatial resolution satellite imagery. International Journal of Remote Sensing, 18(5): 1099-1111
  52. 52.
    Richter R. 1998. Correction of satellite imagery over mountainous terrain. Applied Optics, 37(18): 4004-4015
  53. 53.
    Richter R, Kellenberger T and Kaufmann H. 2009. Comparison of topographic correction methods. Remote Sensing, 1(3): 184-196
  54. 54.
    Richter R and 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
  55. 55.
    Sandmeier S and Itten K I. 1997. A physically -based model to correct atmospheric and illumination effects in optical satellite data of rugged terrain. IEEE Transactions on Geoscience and Remote Sensing, 35(3): 708-717
  56. 56.
    Sandmeier S, Meyer P and Itten K I. 1994. A shortwave radiation model for radiometric correction of optical satellite data in rugged terrain//Proceedings of 1994 IEEE International Geoscience and Remote Sensing Symposium. Pasadena, USA: IEEE: 53-57
  57. 57.
    Sandmeier S, Müller C, Hosgood B and Andreoli G. 1998. Physical mechanisms in hyperspectral BRDF data of grass and watercress. Remote Sensing of Environment, 66(2): 222-233
  58. 58.
    Schaaf C B, Li X W and Strahler A H. 1994. Topographic effects on bidirectional and hemispherical reflectances calculated with a geometric-optical canopy model. IEEE Transactions on Geoscience and Remote Sensing, 32(6): 1186-1193
  59. 59.
    Schaepman-Strub G, Schaepman M E, Martonchik J and Schaaf C. 2006. Whats in a satellite albedo product?//Proceedings of 2006 IEEE International Symposium on Geoscience and Remote Sensing. Denver, USA: IEEE: 2848-2852
  60. 60.
    Shepherd J D and Dymond J R. 2003. Correcting satellite imagery for the variance of reflectance and illumination with topography. International Journal of Remote Sensing, 24(17): 3503-3514
  61. 61.
    Smith J A, Lin T L and Ranson K J. 1980. The lambertian assumption and landsat data. Photogrammetric Engineering and Remote Sensing, 46(9): 1183-1189
  62. 62.
    Soenen S A, Peddle D R and Coburn C A. 2005. SCS+ C: a modified sun-canopy-sensor topographic correction in forested terrain. IEEE Transactions on Geoscience and Remote Sensing, 43(9): 2148-2159
  63. 63.
    Soenen S A, Peddle D R, Coburn C A, Hall R J and Hall F G. 2008. Improved topographic correction of forest image data using a 3‐D canopy reflectance model in multiple forward mode. International Journal of Remote Sensing, 29(4): 1007-1027
  64. 64.
    Sola I, González-Audícana M and Álvarez-Mozos J. 2016. Multi-criteria evaluation of topographic correction methods. Remote Sensing of Environment, 184: 247-262
  65. 65.
    Teillet P M, Guindon B and Goodenough D G. 1982. On the slope-aspect correction of multispectral scanner data. Canadian Journal of Remote Sensing, 8(2): 84-106
  66. 66.
    Temps R C and Coulson K L. 1977. Solar radiation incident upon slopes of different orientations. Solar Energy, 19(2): 179-184
  67. 67.
    Vanonckelen S, Lhermitte S and van Rompaey A. 2013. The effect of atmospheric and topographic correction methods on land cover classification accuracy. International Journal of Applied Earth Observation and Geoinformation, 24: 9-21
  68. 68.
    Vanonckelen S, Lhermitte S and van Rompaey A. 2015. The effect of atmospheric and topographic correction on pixel-based image composites: improved forest cover detection in mountain environments. International Journal of Applied Earth Observation and Geoinformation, 35: 320-328
  69. 69.
    Vincini M, Reeder D and Frazzi E. 2002. An empirical topographic normalization method for forest TM data//Proceedings of IEEE International Geoscience and Remote Sensing Symposium. Toronto, Ontario, Canada: IEEE: 2091-2093
  70. 70.
    Wen J G, Liu Q H and Xiao Q. 2007. Assessment of different topographic correction methods and validation, Journal of Beijing Normal University (Natural Science), 43(3),255-263
  71. 71.
    Wen J G. 2008. Study on Retrieval of Land Surface BRDF/Albedo and its Scale Effects in Complex Terrain. Beijing: Remote Sensing Chinese Academic of Science
  72. 72.
    Wen J G, Liu Q, Tang Y, Dou B C, You D Q, Xiao Q, Liu Q H and Li X W. 2015. Modeling land surface reflectance coupled BRDF for HJ-1/CCD data of rugged terrain in Heihe River Basin, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(4): 1506-1518
  73. 73.
    Wen J G, Liu Q H, Liu Q, Xiao Q and Li X W. 2009. Parametrized BRDF for atmospheric and topographic correction and albedo estimation in Jiangxi rugged terrain, China. International Journal of Remote Sensing, 30(11): 2875-2896
  74. 74.
    Wen J G, Liu Q, Liu Q H, Xiao Q and Li X W. 2015. Land Surface BRDF/Albedo Modeling and Retrieval. Beijing: Science Press
  75. 75.
    Wen J G, Liu Q, Xiao Q, Liu Q H, You D Q, Hao D L, Wu S B and Lin X W. 2018. Characterizing land surface anisotropic reflectance over rugged terrain: a review of concepts and recent developments. Remote Sensing, 10(3): 370
  76. 76.
    Yan G J, Tong Y Y, Yan K, Mu X H, Chu Q, Zhou Y J, Liu Y N, Qi J B, Li L Y, Zeng Y L, Zhou H M, Xie D H and Zhang W M. 2018. Temporal extrapolation of daily downward shortwave radiation over cloud-free rugged terrains. part 1: analysis of topographic effects. IEEE Transactions on Geoscience and Remote Sensing, 56(11): 6375-6394
  77. 77.
    Yin G F, Li A N, Wu S B, Fan W L, Zeng Y L, Yan K, Xu B D, Li J and Liu Q H. 2018. PLC: a simple and semi-physical topographic correction method for vegetation canopies based on path length correction. Remote Sensing of Environment, 215: 184-198
  78. 78.
    Yin G F, Li A N, Zhao W, Jin H A, Bian J H and Wu S B. 2017. Modeling canopy reflectance over sloping terrain based on path length correction. IEEE Transactions on Geoscience and Remote Sensing, 55(8): 4597-4609
  79. 79.
    Yu K, Liu S H and Zhao Y C. 2016. CPBAC: a quick atmospheric correction method using the topographic information. Remote Sensing of Environment, 186: 262-274
  80. 80.
    Zhang W C, Zhu Y F, Qin Z H and Fu C B. 2005. Auto-retrieval of surface reflectance and albedo from landsat TM/+ETM over rugged terrain with an advanced atmospheric correction algorithm//Proceedings of 2005 IEEE International Geoscience and Remote Sensing Symposium. Seoul, South Korea: IEEE: 4172-4176
  81. 81.
    Zhang W C and Gao Y N. 2011. Topographic correction algorithm for remotely sensed data accounting for indirect irradiance, International Journal of Remote Sensing, 32:7, 1807-1824
  82. 82.
    Zhang Y L, Bai Y L and Li C H. 2014. Topographic normalization of landsat TM images in rugged terrain//Proceedings of the 2014 7th International Congress on Image and Signal Processing. Dalian, China: IEEE: 580-585
  83. 83.
    Zhang Y L, Li X, Wen J G, Liu Q H and Yan G L. 2015. Improved topographic normalization for landsat TM images by introducing the MODIS surface BRDF. Remote Sensing, 7(6): 6558-6575

قراءة النص الكامل

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website