微型电脑应用2025，Vol.41Issue(3)：200-204,5.
神经网络支持下的跨比例尺线状水系目标变化检测
Linear River Target Change Detection Cross-scale Supported by Neural Networks
吴超超 1张崇善 1姜楠1
作者信息
- 1. 正元地理信息集团股份有限公司,北京 101300
- 折叠
摘要
Abstract
Change detection is a key part of implementing cross-scale spatial data updates,and is also a difficult issue.The difference between the old and new data includes not only the change of real geographical entities,but also the difference in rep-resentation caused by map generalization.The screening of the two types of change information in the spatial data updating process is a complex decision-making process that requires a combination of distance,area,shape,direction and other indica-tors for judgement and analysis.Considering the above issues,this paper takes the update of linear river elements as the object,introduces BP neural network to build a model for identifying changes across scales of old and new data.The difficult problem of detecting changes in linear river targets under multi-indicator decision making is solved by gaining knowledge of change rec-ognition through machine learning.Using real data for experimental analysis,it was found through cross validation that the recognition accuracy of most cases in the 5 experiments was higher than 90％,proving the effectiveness of the proposed meth-od.关键词
跨比例尺更新/变化检测/BP神经网络/线状水系Key words
cross-scale update/change detection/BP neural network/linear river分类
社会科学引用本文复制引用
吴超超,张崇善,姜楠..神经网络支持下的跨比例尺线状水系目标变化检测[J].微型电脑应用,2025,41(3):200-204,5.
