Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Development of Cloud Detection Algorithm for Extracting the Cloud-free Land Surface from Daytime NOAA/AVHRR Data

NOAA/AVHRR 주간 자료로부터 지면 자료 추출을 위한 구름 탐지 알고리즘 개발

  • Published : 1999.09.01
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Abstract

The elimination process of cloud-contaminated pixels is one of important steps before obtaining the accurate parameters of land and ocean surface from AVHRR imagery. We developed a 6step threshold method to detect the cloud-contaminated pixels from NOAA-14/AVHRR datime imagery over land using different combination of channels. This algorithm has two phases : the first is to make a cloud-free characteristic data of land surface using compositing techniques from channel 1 and 5 imagery and a dynamic threshold of brightness temperature, and the second is to identify the each pixel as a cloud-free or cloudy one through 4-step threshold tests. The merits of this method are its simplicity in input data and automation in determining threshold values. The threshold of infrared data is calculated through the combination of brightness temperature of land surface obtained from AVHRR imagery, spatial variance of them and temporal variance of observed land surface temperature. The method detected the could-comtaminated pixels successfully embedded inthe NOAA-14/AVHRR daytime imagery for the August 1 to November 30, 1996 and March 1 to July 30, 1997. This method was evaluated through the comparison with ground-based cloud observations and with the enhanced visible and infrared imagery.

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References

  1. J. Geophys. Res. v.87 Cloud cover from high resolution scanner data : Detection and allowing for partially filled fields pf view Coakley, J. A.;F. P. Bertherton
  2. Remote Sens. Environ. v.54 Global discnimanation of land cover types from metrics derived fromm AVHRR Pathfinder data DeFries, R. S.;M,, Hansen;J. R. Townshend
  3. Automatic cloud detection applied to NOAA-11/AVHRR imagery v.46 Derrien M.;B. Farki;L. Harang;H. LeGleau;A. Noyalet;D. Pochic;A. Sairouni
  4. J. Appl. Meteor. v.21 Automatic classification of clouds on Meteosat imagery : application to high level clouds Desbois, M. G.;Seze;G. Szejwach
  5. Int. J. Remote Sens. v.15 The 1-km AVHRR global land data set : first stages in implementation Eidenshink, J. C.;Faundeen, J. L.
  6. J. Appl. Meteor. v.35 Relationship among remotely sensed data, surface energy balance, and area-averaged fluxes over partially vegetated land surfaces Friedl
  7. Bull. Amer. Meteor. Soc. v.76 no.7 The enhanced NOAA global land dataset from the AVHRR Gutman G.;D. Tarpley;A. Ignatov;S. Olson
  8. Int. J. Remote Sens. v.7 Characteristics of maximum value composite images from temporal AVHRR data Holben, B. N.
  9. J. Meteor. Soc. v.63 On the temperature and effective emissivity determination of semi- transparent cirrus clouds by bi-spectral measurements in 10μu window region Inoue, T.
  10. J. Geophys. Res. v.92 A cloud type classification with NOAA-7 split-window measurements Inoue, T.
  11. NCDC/SDSD NOAA Polar Orbiter Data User's Guide Kidwell, K.
  12. J. Korean Forestry v.83 no.4 Vegetation cover type mapping over the Korean peninsula using multitemporal AVHRR data Lee, K. S.
  13. J. Appl. Meteor. v.32 Developing satellite-derived estimates of surface moisture status Nemani, R.;L. Pierce;S. Running
  14. Remote Sens. Environ. v.51 Algorithm for extracting information from remote thermal-IR observations of the Earth's surface Norman, J. M.;M. Divakarla;N. S. Goel
  15. Int. J. Remote Senging v.6 Cloud detection and classification over oceans at night with NOAA-7 Olesen, F. S.;Grassl, H.
  16. Mon. Wea. Rev. v.105 Abi-spectral method for cloud parameter determination Reynolds, D. W.;T. H. Vonder Haar
  17. Int. J. Remote Sensing v.9 An improved method for detecting clear sky and cloudy radiances from AVHRR data Saunders, R. W.;K. T. Kriebel
  18. Bull. Amer. Meteor. Soc. v.64 The ISCCP : The first project of the world climate research programme Schiffer, R. A.;W. B. Rossow
  19. Bull. Amer. Meteor. Soc. v.71 A review of satellite data algorithms for studies of the land surface Sellers, P. J.;S. I. Rasool;H. J. Bolle
  20. J. Climate Appl. Meteor. v.26 Cloud cover analysis from satellite imagery using spatial and temporal charcteristics of the data Seze, G.;M. Desbois
  21. Remote Sens. Enivron. v.55 Improved cloud detection for the daytime AVHRR scenes over land Simpson, J. J.;J. I. Gobat
  22. J. Korean Soc. Remote Sensing v.9 Cloud cover analysis from the GMS/S-VISSR imagery using bispectral thresholds technique Shu, M. S.;K. Y. Park https://doi.org/10.7780/kjrs.1993.9.1.1
  23. Geocarto International v.4 Consideration on problems of NOAA/GVI data for global land cover monitoring Tateishi R.;K. Kajiwara