In this paper,improvement on man-computer interactive classification of clouds based on hispeetral satellite imagery has been synthesized by using the maximum likelihood automatic clustering(MLAC)and the unit feature ...In this paper,improvement on man-computer interactive classification of clouds based on hispeetral satellite imagery has been synthesized by using the maximum likelihood automatic clustering(MLAC)and the unit feature space classification(UFSC)approaches.The improved classification not only shortens the time of sample-training in UFSC method,but also eliminates the inevitable shortcomings of the MLAC method.(e.g.,1.sample selecting and training is confined only to one cloud image:2.the result of clustering is pretty sensitive to the selection of initial cluster center:3.the actual classification basically can not satisfy the supposition of normal distribution required by MLAC method;4.errors in classification are difficult to be modified.) Moreover,it makes full use of the professionals'accumulated knowledge and experience of visual cloud classifications and the cloud report of ground observation,having ensured both the higher accuracy of classification and its wide application as well.展开更多
This paper presents the automated pixel-scale neural network classification methods being developed at National Satellite Meteorological Center(NSMC)of China to classify clouds by using NOAA/AVHRR and GMS-5 satellite ...This paper presents the automated pixel-scale neural network classification methods being developed at National Satellite Meteorological Center(NSMC)of China to classify clouds by using NOAA/AVHRR and GMS-5 satellite imageries.By using Terra satellite MODIS imageries,an automated pixel-scale threshold technique has been developed to detect and classify clouds.The study focuses on applications of these cloud classification techniques to the Huaihe River and the Changjiang(Yangtze)River drainage basin.The different types of clouds show more clearly on this cloud classification image than single band image.The results of the cloud classifications are the basis of studying cloud amount,cloud top height and cloud top pressure.Cloud mask methods are widely used in SST,LST,and TPW retrieval schemes.Some case studies about cloud mask and cloud classification in satellite imageries,which are related with the study of Global Energy and Water Cycle Experiment(GEWEX)in the Huaihe River and the Changjiang River drainage basin are illustrated.展开更多
文摘In this paper,improvement on man-computer interactive classification of clouds based on hispeetral satellite imagery has been synthesized by using the maximum likelihood automatic clustering(MLAC)and the unit feature space classification(UFSC)approaches.The improved classification not only shortens the time of sample-training in UFSC method,but also eliminates the inevitable shortcomings of the MLAC method.(e.g.,1.sample selecting and training is confined only to one cloud image:2.the result of clustering is pretty sensitive to the selection of initial cluster center:3.the actual classification basically can not satisfy the supposition of normal distribution required by MLAC method;4.errors in classification are difficult to be modified.) Moreover,it makes full use of the professionals'accumulated knowledge and experience of visual cloud classifications and the cloud report of ground observation,having ensured both the higher accuracy of classification and its wide application as well.
基金the National Natural Science Foundation of China(49794030).
文摘This paper presents the automated pixel-scale neural network classification methods being developed at National Satellite Meteorological Center(NSMC)of China to classify clouds by using NOAA/AVHRR and GMS-5 satellite imageries.By using Terra satellite MODIS imageries,an automated pixel-scale threshold technique has been developed to detect and classify clouds.The study focuses on applications of these cloud classification techniques to the Huaihe River and the Changjiang(Yangtze)River drainage basin.The different types of clouds show more clearly on this cloud classification image than single band image.The results of the cloud classifications are the basis of studying cloud amount,cloud top height and cloud top pressure.Cloud mask methods are widely used in SST,LST,and TPW retrieval schemes.Some case studies about cloud mask and cloud classification in satellite imageries,which are related with the study of Global Energy and Water Cycle Experiment(GEWEX)in the Huaihe River and the Changjiang River drainage basin are illustrated.
