全球智库信息集成服务系统(G2TT): Spectral Pattern Recognition and Fuzzy Artmap Classification: Design Features, System Dynamics and Real World Simulation.

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来源类型	Monograph (IIASA Working Paper)
规范类型	论文
	Spectral Pattern Recognition and Fuzzy Artmap Classification: Design Features, System Dynamics and Real World Simulation.
	Fischer MM; Gopal S
发表日期	1996
出版者	IIASA, Laxenburg, Austria: WP-96-063
出版年	1996
语种	英语
摘要	Classification of terrain cover from satellite radar imagery represents an area of considerable current interest and research. Most satellite sensors used for land applications are of the imaging type. They record data in a variety of spectral channels and at a variety of ground resolutions. Spectral pattern recognition refers to classification procedures utilizing pixel-by-pixel spectral information as the basis for automated land cover classification. A number of methods have been developed in the past to classify pixels [resolution cells] from multispectral imagery to a priori given land cover categories. Their ability to provide land cover information with high classification accuracies is significant for work where accurate and reliable thematic information is needed. The current trend towards the use of more spectral bands on satellite instruments, such as visible and infrared imaging spectrometers, and finer pixel and grey level resolutions will offer more precise possibilities for accurate identification. But as the complexity of the data grows, so too does the need for more powerful tools to analyse them.
主题	Methodology of Decision Analysis (MDA)
URL	http://pure.iiasa.ac.at/id/eprint/4964/
来源智库	International Institute for Applied Systems Analysis (Austria)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/124596
推荐引用方式 GB/T 7714	Fischer MM,Gopal S. Spectral Pattern Recognition and Fuzzy Artmap Classification: Design Features, System Dynamics and Real World Simulation.. 1996.

条目包含的文件
文件名称/大小	资源类型	版本类型	开放类型	使用许可
WP-96-063.pdf（1003KB）	智库出版物		限制开放	CC BY-NC-SA	浏览