Atmospheric correction

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Short description: Photographic image processing tecnhique

Atmospheric correction is the process of removing the effects of the atmosphere on the reflectance values of images taken by satellite or airborne sensors.[1][2] Atmospheric effects in optical remote sensing are significant and complex, dramatically altering the spectral nature of the radiation reaching the remote sensor.[3] The atmosphere both absorbs and scatters various wavelengths of the visible spectrum which must pass through the atmosphere twice, once from the sun to the object and then again as it travels back up the image sensor. These distortions are corrected using various approaches and techniques, as described below.[4]

Examples of Atmospheric Correction Methods

Examples of atmospheric correction techniques for multispectral remote-sensing images, ordered chronologically to show the historical development of atmospheric correction methods in remote-sensing.
Sensor Approach
MSS band-to-band regression [5]
MSS all-band spectral covariance [6]
airborne MSS band-to-band regression [7]
AVHRR iterative estimation [8]
MSS, TM DOS with exponential scattering model [9]
TM DOS with exponential scattering model, downwelling atmospheric radiance measurements [10]
TM pixel-by-pixel tasseled cap haze parameter [11]
AVHRR DOS, NDVI, AVHRR band 3 [12]
airborne TMS, Landsat TM ground and airborne solar measurements, atmospheric modeling code [13]
TM comparison of ten DOS and atmospheric modeling code variations with field data [14]
TM dark target, modeling code [15]
TM (all bands) atmospheric modeling code, region histogram matching [16]
TM DOS with estimated atmospheric transmittance [17]
TM dark target, atmospheric modeling code
TM, ETM+ empirical line method, single target, ground measurements
TM water reservoirs, comparison of 7 methods for 12 dates
AVHRR 2-band PCT used to separate aerosol components

See also

References

  1. Pacifici, F.; Longbotham, N.; Emery, W. J. (2014-10-01). "The Importance of Physical Quantities for the Analysis of Multitemporal and Multiangular Optical Very High Spatial Resolution Images". IEEE Transactions on Geoscience and Remote Sensing 52 (10): 6241–6256. doi:10.1109/TGRS.2013.2295819. Bibcode2014ITGRS..52.6241P. 
  2. "Atmospheric Correction". University of Maryland Institute for Advanced Computer Studies. http://www.umiacs.umd.edu/research/GC/atmo/index.html. 
  3. Schowengerdt, Robert (2007). Remote Sensing: Models and Methods for Image Processing. Elsevier Inc. p. 337. ISBN 0-12-369407-8. 
  4. Schowengerdt, Robert (2007). Remote Sensing: Models and Methods for Image Processing. Elsevier Inc. p. 338. ISBN 0-12-369407-8. 
  5. Potter, J. F.; Mendolowitz, M. (1975). "On the determination of the haze levels from Landsat data". 10th International Symposium on Remote Sensing of Environment. NASA United States. pp. 695–703. 19760052102. 
  6. Switzer, P.; Kowalik, W. S.; Lyon, R. J. (1981). "Estimation of atmospheric path radiance by the covariance matrix method". Photogrammetric Engineering and Remote Sensing 47: 1469–1476. 
  7. Potter, J. F. (1984). "The channel correlation method for estimating aerosol levels from multispectral scanner data". Photogrammetric Engineering and Remote Sensing 50: 43–52. 
  8. Singh, S. M.; Cracknell, A. P. (1986). "The estimation of atmospheric effects for SPOT using AVHRR channel-1 data". International Journal of Remote Sensing 7 (3): 361–377. 
  9. Chavez, P. S. (1988). "An improved dark-object substraction technique for atmospheric scattering correction of multispectral data". Remote Sensing of Environment 24: 459–479. 
  10. Chavez, P. S. (1989). "Radiometric calibration of Landsat Thematic Mapper multispectral images". Photogrammetric Engineering and Remote Sensing 55 (9): 1285–1294. 
  11. Lavreau, J. (1991). "De-hazing Landsat Thematic Mapper images". Photogrammetric Engineering and Remote Sensing 57 (10): 1297–1302. 
  12. Holben, B.; Vermote, E.; Kaufman, Y. J.; Tanre, D.; Kalb, V. (1992). "Aerosol retrieval over land from AVHRR data - application for atmospheric correction". IEEE Transactions on Geoscience and Remote Sensing 30 (2): 212–222. 
  13. Wrigley, R. C.; Spanner, M. A.; Slye, R. E.; Pueschel, R. F.; Aggarwal, H. R. (1992). "Atmospheric correction of remotely sensed image data by a simplified model". Journal of Geophysical Research 97 (D17): 18797–18814. 
  14. Moran, M. S.; Jackson, R. D.; Slater, P. N.; Teillet, P. M. (1992). "Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output". Remote Sensing of Environment 41: 169–184. 
  15. Teillet, P. M.; Fedosejevs, G. (1995). "On the dark target approach to atmospheric correction of remotely sensed data". Canadian Journal of Remote Sensing 21 (4): 374–387. 
  16. Richter, R. (1996). "A spatially adaptive fast atmospheric correction algorithm". International Journal of Remote Sensing 17 (6): 1201–1214. 
  17. Chavez, P. S. Jr. (1996). "Image-based atmospheric corrections-revisited and improved". Photogrammetric Engineering and Remote Sensing 62 (9): 1025–1036. 

External links