节点文献
IMPROVED MAN-COMPUTER INTERACTIVE CLASSIFICATION OF CLOUDS BASED ON BISPECTRAL SATELLITE IMAGERY
【摘要】 <正> In this paper,improvement on man-computer interactive classification of clouds based onhispeetral satellite imagery has been synthesized by using the maximum likelihood automaticclustering(MLAC)and the unit feature space classification(UFSC)approaches.The improvedclassification not only shortens the time of sample-training in UFSC method,but also eliminatesthe inevitable shortcomings of the MLAC method.(e.g.,1.sample selecting and training isconfined only to one cloud image:2.the result of clustering is pretty sensitive to the selection ofinitial cluster center:3.the actual classification basically can not satisfy the supposition of normaldistribution 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 visualcloud classifications and the cloud report of ground observation,having ensured both the higheraccuracy of classification and its wide application as well.
【Abstract】 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.
【Key words】 bispectral satellite imagery; cloud classification; maximum likelihood automatic clustering(MLAC); unit feature space classification(UFSC); man-computer interactive method;
- 【文献出处】 Acta Meteorologica Sinica ,气象学报(英文版) , 编辑部邮箱 ,1998年03期
- 【分类号】P426.5
- 【被引频次】8
- 【下载频次】20