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来源类型Peer-reviewed Article
规范类型其他
Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation
Brian JOHNSON
发表日期2016-07
出版者SPIE
出版年2016
页码036004
语种英语
概述Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. The major contribution...
摘要

Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. The major contribution of this research is the
development of rule sets and the identification of major features for satellite image classification
where the rule sets are transferable and the parameters are tunable for different types of imagery.
Additionally, the individual objectwise classification and principal component analysis help to
identify the required object from an arbitrary number of objects within images given ground truth
data for the training.

主题Adaptation
区域Worldwide
URLhttps://pub.iges.or.jp/pub/rule-based-land-cover-classification-very-high
来源智库Institute for Global Environmental Strategies (Japan)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/311020
推荐引用方式
GB/T 7714
Brian JOHNSON. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation. 2016.
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