A METHOD FOR DETECTING CLOUD PIXELS ON NOAA-AVHRR IMAGE USING THREE-DIMENSION STATISTIC GRAPH AND SET DISCRIMINATION

doi:10.6046/gtzyyg.1997.04.09

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Abstract The detection of cloud pixels is the essential for monitoring resources and environment of the earth using NOAA-AVHRRimage. The paper analyses the feature of the clouds on NOAA-AVHRRdata by instances, draws 3D-statistic graph according to the feature indexes, and decides the thresholds of cloud pixels directly from the graph. The thresholds are regarded as the setting condition for detecting the cloud pixels automatically. The advantages of above method are higher sensitivity and better stability and that the viewing for the distribution of cloud pixels is more directly.

Keywords Three Gorges reservoir areas Airborne remote sensing “3S&rdquo technique Dynamic monitoring

Issue Date: 02 August 2011

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	LUO Yuan-Hua
	ZHANG Zhi-Feng
	LI Zhi-Zhong
	YANG Ri-Hong
	XU Yu
	DUAN Wei-Xing
	XU Wei-Xiu
	ZENG Wei-Hui

Cite this article:

LUO Yuan-Hua,ZHANG Zhi-Feng,LI Zhi-Zhong, et al. A METHOD FOR DETECTING CLOUD PIXELS ON NOAA-AVHRR IMAGE USING THREE-DIMENSION STATISTIC GRAPH AND SET DISCRIMINATION[J]. REMOTE SENSING FOR LAND & RESOURCES, 1997, 9(4): 54-55.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.1997.04.09 OR https://www.gtzyyg.com/EN/Y1997/V9/I4/54

[1] 刘多森、曾志远.土壤和环境研究中的数学方法与建模.北京:农业出版社,1987

[2] Coakley, J. A. . Claud Cover form High Resolution Scanner Data: Detecting and Allowing for Partially Filled Fields of View. Journal of Geophysical Research, 1982, 87:4917-4932

[3] Saunder, R. W. . An Automated Schene for the Removal of Cloud Contamination from AVHIRR Radiances Over Western Europe. International Journal of Remote Sensing,1986,7:867-886

[4] V. Thiermann. A Method for the Detection of Cloud Using AVHRR Infrared Observations. International Journal of Remote Sensing, 1992,13(10):1829-1841

[5] Takashi Yamanouchi. Cloud Distribution in Antarctic frarn AVHRR Data and Radiation Measurements at the Surface.International Journal of Remote Sensing, 1492,13 (1) :111-127

[6] 周红妹、杨星卫、陆贤NOAH气象卫星云检测方法的研究.环境遥感,1995,10(2):137-141

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