Abstract
As the EM radiation passes through the atmosphere, it undergoes modification in intensity due to atmospheric interaction, viz. selective scattering, absorption and emission. The main objective of atmospheric corrections is to retrieve the realistic surface reflectance or emittance values of a target from remotely sensed image data. In the solar reflection region, atmospheric scattering is the dominant cause of path radiance. In the thermal infrared region, atmospheric window is used to minimize the effect of atmospheric emission. Different types of procedures are used for atmospheric correction that include empirical-statistical procedures and radiative transfer modelling.
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References
Aspinall RJ, Marcus WA, Boardman JW (2002) Considerations in collecting, processing, and analysing high spatial resolution hyperspectral data for environmental investigations. J Geograph Syst 4:15–29
Ben-Dor E, Kindel B, Goetz AFH (2004) Quality assessment of several methods to recover surface reflectance using synthetic imaging spectroscopy data. Remote Sens Environ 90:389–404
Berk A, Anderson G, Acharya P, Shettle E (2008) MODTRAN 5.2.0.0 user’s manual. Air Force Geophysics Laboratory, Hanscom, AFB, MA, US
Berk A, Bernstein LS, Robertson DC (1989) MODTRAN: a moderate resolution model for LOWTRAN7. Tech Rep GL-TR-89-0122, Geophysics Laboratory, Bedford, Mass
Berk A, Conforti P, Kennett R, Perkins T, Hawes F, van den Bosch J (2014) MODTRAN6: a major upgrade of the MODTRAN radiative transfer code. Proceedings SPIE 9088, algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XX, 90880H (13 June 2014). doi:10.1117/12.2050433
Chavez PS Jr (1988) An improved dark object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sens Environ 24:459–479
Chavez PS Jr (1996) Image-based atmospheric corrections revisited and improved. Photogramm Eng Remote Sens 62:1025–1036
Crippen RE (1987) The regression intersection method of adjusting image data for band ratioing. Int J Remote Sens 9:767–776
Farrand WH, Singer RB, Merényi E (1994) Retrieval of apparent surface reflectance from AVIRIS data—a comparison of empirical line, radiative-transfer and spectral mixture methods. Remote Sens Environ 47(3):311–321
Gao BC, Heidebrecht KB, Goetz AFH (1993) Derivation of scaled surface reflectances from AVIRIS data. Remote Sens Environ 44:165–178
Gao BC, Montes MJ, Davis OC, Goetz AFH (2009) Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean. Remote Sens Environ 113:S17–S24
Gordon HR (1978) Removal of atmospheric effects from the satellite imagery of the oceans. Appl Opt 17:1631–1636
Hadjimitsis DG (2009) Aerosol optical thickness (AOT) retrieval over land using satellite image-based algorithm. Air Qual Atmos Health 2:89–97
Kruse FA (1988) Use of airborne imaging spectrometer data to map minerals associated with hydrothermally altered rocks in the northern Grapevine Mountains, Nevada and California. Remote Sens Environ 24:31–51
Rahman H, Dedieu G (1994) SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum. Int J Remote Sens 15:123–143
Richter R, Schläpfer D (2016) Atmospheric/topographic correction for airborne imagery. ATCOR-4 User Guide, Version 7.1.0, Nov 2016
Roberts DA, Yamaguchi Y, Lyon R (1986) Comparison of various techniques for calibration of AIS data. In: Vane G, Goetz AFH (eds) Proceedings of the 2nd airborne imaging spectrometer data analysis workshop, JPL Publication, vol 86–35, pp 21−30, Jet Propulsion Lab, Pasadena, CA
Schott JR, Salvaggio C, Volchok WJ (1988) Radiometric scene normalization using pseudoinvariant features. Remote Sens Environ 26(1):1–14
Schroeder TA, Cohen WB, Song C, Canty MJ, Yang Z (2006) Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon. Remote Sens Environ 103:16–26
Smith GM, Milton EJ (1999) The use of the empirical line method to calibrate remotely sensed data to reflectance. Int J Rem Sens 20(13):2653–2662
Tanre D et al (1990) Description of a computer code to simulate the satellite signal in the solar spectrum: the 5S code. Int J Rem Sensing 11:659–668
Vermote EF, Tanre D, Denze JL, Herman M, Morcette JJ (1997) Second simulation of the satellite signal in the solar spectrum 6S: an overview. IEEE Trans Geosci Remote Sens 35(3):675–686
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Gupta, R.P. (2018). Atmospheric Corrections. In: Remote Sensing Geology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-55876-8_10
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DOI: https://doi.org/10.1007/978-3-662-55876-8_10
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