Improved cloud detection for daytime AVHRR scenes over land

Remote Sensing of Environment

Volumn 55, Issue 1, 1996, Pages 21-49

  Simpson, James J ^a   Gobat, Jason I ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; AVHRR DATA; CLOUD DETECTION; CLUSTERING;

EID: 0029772173     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/0034-4257(95)00188-3     Document Type: Article

References (35)

1. Choudhury, B. J. (1990), Monitoring arid lands using AVHRR-observed visible reflectance and SMMR-37 GHz polarization difference, Int. J. Remote Sens. 11:1949-1956.
2. Coakley, J. A., Jr., and Bretherton, F. P. (1982), Cloud cover from high resolution scanner data: Detecting and allowing for partially filled fields of view, J. Geophys. Res. 87:4917-4932.
3. Earth Observing System (1989), From patterns to processes: The strategy of the Earth Observing System. EOS Science Steering Committee Report, Volume II and Appendices a-h. NASA 140 pp.
4. Gallaudet, T. C., and Simpson, J. J. (1991), Automated cloud screening of AVHRR imagery using split-and-merge clustering, Remote Sens. Environ. 38:77-121.
5. Gallegos, S. C., Hawkins, J. D., and Cheng, C. F. (1993), A new automated method of cloud masking for Advanced Very High Resolution Radiometer full-resolution data over the ocean, J. Geophys. Res. 98:8505-8516.
6. Gutman, G. G. (1991), Vegetation indices from AVHRR: An update and future prospects, Remote Sens. Environ. 35:121-136.
7. Gutman, G. G. (1992), Satellite daytime image classification for global studies of earth's surface parameters from polar orbiters, Int. J. Remote Sens. 13:209-234.
8. Gutman, G., Tarpley, D., and Ohring, G. (1987), Cloud screening for land surface characteristics in a reduced resolution satellite data set, Int. J. Remote Sens. 8:859-870.
9. Haralick, R. M., Shanmugan, K., and Dinsteu, Its' Hak (1973), Texture features for image classification, IEEE Trans. Syst. Man. Cybern. SMC-3:610-621.
10. Justice, C. O., Townshend, J. R. G., Holben, B. N., and Tucker, C. J. (1985), Analysis and phenology of global vegetation using meteorological satellite data, Int. J. Remote Sens. 6: 1271-1318.
11. Kaufman, Y. J., and Sendra, Y. (1988), Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery, Int. J. Remote Sens. 9:1357-1381.
12. Lauritson, L., Nelson, G. G., and Porto, R. W. (1979), Data extraction and calibration of TIROS-N / NOAA A-G radiometers, NOAA Tech. Memo. NESS 107, U.S. Department of Commerce, Washington D.C.
13. NOAA (1985), Polar Orbiter Data Users Guide, U.S. Dept of Commerce, NOAA, National Environmental Satellite, National Climatic Data Center, Satellite Data Service Division, Washington DC.
14. Ohring, G. A., Gruber, A., and Ellingson, R. (1985), Satellite determination of the relationship between total longwave radiative flux and infrared window radiances, J. Clin. Appl. Meteor. 23:416-425.
15. Pairman, D., and Kittler, J. (1986), Cluster algorithms for use with images of clouds, Int. J. Remote Sens. 7:855-866.
16. Rand McNally (1977), The International Atlas, Section on World Scene Climate Regions pp. 306-307, New York, p. 533.
17. Rossow, W. B., Mosher, F., Kinsella, E. et al. (1985), ISCCP cloud algorithm intercomparison. J. Clim. Appl. Meteor. 24: 877-903.
18. Saunders, R. W., and Kriebel, K. T. (1988a), An improved method for detecting clear sky and cloudy radiances form AVHRR data, Int. J. Remote Sens. 9:123-150.
19. Saunders, R. W., and Kriebel, K. T. (1988b), Errata (i.e., An improved method for detecting clear sky and cloudy radiances from AVHRR data. Int. J. Remote Sens. 9:123-150,
20. Int. J. Remote Sens. 9:1393-1394.
21. Sellers, P. J., Rasool, S. I., and Bolle, H. J. (1990), A review of satellite data algorithms for studies of the land surface. Bull. Am. Meteor. Soc. 71:1429-1447.
22. Simpson, J. J. (1992), Image masking using polygon fill and morphological operations, Remote Sens. Environ. 40:161-183.
23. Simpson, J. J., and Humphrey, C. (1990), An automated cloud screening algorithm for daytime Advanced Very High Resolution Radiometer imagery, J. Geophys. Res. 95:13,459-13,481.
24. Simpson, J. J., and Harkins, D. N. (1993), The Scripps satellite archive and browse for localized environments (SSABLE) system. IEEE Trans. Geosci. Remote Sens. 31:515-525.
25. Simpson, J. J., and Yhann, S. R. (1994), Reduction of noise in AVHRR channel 3 data with minimum distortion, IEEE Trans. Geo. Remote Sens. 32:315-328.
26. Simpson, J. J., and Gobat, J. I. (1995a), Improved cloud detection in GOES scenes over land, Remote Sens. Environ. 52: 36-54.
27. Simpson, J. J., and Gobat, J. I. (1995b), Improved cloud detection in GOES scenes over oceans, Remote Sens. Environ. 52: 79-94.
28. Simpson, J. J., and Keller, R. H. (1995), An improved fuzzy logic segmentation of sea ice, clouds and ocean in remotely sensed arctic imagery. Remote Sens. Environ. 54:290-312.
29. Singh, S. M. (1988), Simulation of solar zenith angle effect on global vegetation index (GVI) data, Int. J. Remote Sens. 9: 237-248.
30. Spanner, M. A., Pierce, L. L., Running, S. W., and Peterson, D. L. (1990), The seasonality of AVHRR data of temperate coniferous forests: Relationships with leaf area index, Remote Sens. Environ. 33:97-112.
31. Stowe, L. L., McClain, E. P., Carey, R., et al. (1991), Global distribution of cloud cover derived from NOAA / AVHRR operational satellite data, Adv. Space Res. 11:51-54.
32. Tarpley, J. D., Schneider, S. R., and Money, R. L. (1984), Global vegetation indices from the NOAA-7 meteorological satellite, J. Clim. Appl. Meteorol. 23:491-493.
33. Taylor, B. F., Dini, P. W., and Kidson, J. W. (1985), Determination of seasonal and interannual variation in New Zealand pasture growth from NOAA-7 data, Remote Sens. Environ. 18:177-192.
34. Welch, R. M., Navar, M. S., and Sengupta, S. K. (1989), The effect of spatial resolution upon texture-based cloud field classification, J. Geophys. Res. 94:14767-14781.
35. Yhann, S. R., and Simpson, J. J. (1995), Application of neural networks to AVHRR cloud segmentation, IEEE Trans. Geo. Remote Sens. 33:590-604.