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Author Li, H.; Jia, Y.; Zhou, Y. url  doi
  Title Urban Expansion Pattern Analysis and Planning Implementation Evaluation Based on using Fully Convolution Neural Network to Extract Land Range Type Journal Article
  Year 2018 Publication NeuroQuantology Abbreviated Journal  
  Volume 16 Issue 5 Pages 814-822  
  Keywords Remote Sensing  
  Abstract In recent years, due to the rapid development of China’s urban, it is significant for effective implementation of urban science development and planning that grasp the process of urban development, analyze the potential of subsequent development, and evaluate the matching degree of the development status and the planning. Thereinto, an effective way we exercise today is to evaluate urban expansion pattern analysis and planning implementation. According to research results of the urban land range extraction method based on the support vector machine (SVM) and fully convolution neural network (FCN) of the depth learning method for the night light image data, this paper describes an integration of remote sensing (RS) and geographic information system (GIS) and analyzes the urban expansion pattern of Beijing based on the computed results of landscape pattern indices. The results unveil that from 1990s to 2010s, Beijing took on a circle expansion mode on the ground the spatial agglomeration degree gradually increases and the expansion potential has spatial distinctions, which basically meets the requirements of the overall planning.  
  Corporate Author Thesis  
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  Language English Summary Language (up) Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number NC @ ehyde3 @ Serial 2088  
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