The Cluster of City Buildings Based on the SOM Neural Network

International Symposium on Earth Observation for One Belt and One Road

地球科学;政治学;社会学;经济学

Wang, Z.^1 ; Liu, Q.^1

School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu

611731, China^1

关键词: Automatic clustering;    Automatic clustering algorithm;    Cartographic generalization;    Integrated decision makings;    Interactive features;    Som neural networks;    Transformation process;    Visualization software;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/57/1/012047/pdf
DOI  :  10.1088/1755-1315/57/1/012047

来源: IOP

【 摘 要 】

The clustering of buildings on the city map is an important field of cartographic and the main step to resolve issues related to the scale of the city map transformation process. The development of computer technology promotes the studies of cartographic and modelling algorithms. In order to achieve automatic clustering of map elements, the domestic and foreign scholars have proposed numerous automatic clustering algorithms. Although each algorithm works for specific problems, all algorithms are based on the graphical analysis transformation of building polygons on the map. By reading and analyzing current development of domestic and foreign researches, we find out that map building clustering needs more inspiring interactive features and automatic integrated decision-making simulation functions. It needs to improve the visualization software and integrated automatic intelligence, increase the proportion of the batch to support implementation of automated cartographic generalization to a higher level.