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	A comparison of multiple-point statistics and two-point statistics for spectral-spatial land cover classification
	Shi, Zhongkui ; Li, Peijun
	2016
英文摘要	Incorporating spatial information quantified by geostatistical tools to improve the classification of remotely sensed data is a promising method. Most existing studies only focused on the development of geostatistics-based spectral-spatial classification methods. This paper investigates primarily the advantages and disadvantages of two different types of geostatistical methods (two-point statistics and multiple-point statistics) for spectral-spatial land cover classification, by quantitatively comparing the classification results through an accuracy assessment. Two study areas were selected to evaluate the performance of two methods. Experimental results demonstrate that the classification result by including spatial information using multiple-point statistics obtained a higher accuracy than that by using two-point statistics. ? 2016 IEEE.; EI; 255-259
语种	英语
出处	4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016
DOI标识	10.1109/EORSA.2016.7552808
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/449409]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	Shi, Zhongkui,Li, Peijun. A comparison of multiple-point statistics and two-point statistics for spectral-spatial land cover classification. 2016-01-01.

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