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Spatial-Temporal Characteristic Analysis of Ethnic Toponyms Based on Spatial Information Entropy at the Rural Level in Northeast China

School of Earth Science, Yunnan University, Kunming 650091, Yunnan, China
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Entropy 2020, 22(4), 393; https://doi.org/10.3390/e22040393
Received: 21 February 2020 / Revised: 25 March 2020 / Accepted: 28 March 2020 / Published: 30 March 2020
(This article belongs to the Special Issue Information Theory for Human and Social Processes)
As a symbol language, toponyms have inherited the unique local historical culture in the long process of historical development. As the birthplace of Manchu, there are many toponyms originated from multi-ethnic groups (e.g., Manchu, Mongol, Korean, Hui, and Xibe) in Northeast China which possess unique cultural connotations. This study aimed to (1) establish a spatial-temporal database of toponyms in Northeast China using a multi-source data set, and identify their ethnic types and origin times; and (2) explore the geographical distribution characteristics of ethnic toponyms and the evolution of rural settlements by comparing the spatial analysis and spatial information entropy methods. The results found that toponyms reflect not only the spatial distribution characteristics of the density and direction of ethnic groups, but also the migration law of rural settlements. Results also confirm that toponyms contain unique cultural connotations and provide a theoretical basis for the protection and promotion of the cultural connotations of toponyms. This research provides an entropic perspective and method for exploring the spatial-temporal evolutionary characteristics of ethnic groups and toponym mapping. View Full-Text
Keywords: geographical distribution; Manchu culture; rural settlements migration; spatial information entropy geographical distribution; Manchu culture; rural settlements migration; spatial information entropy
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Zhao, F.; Fu, Y.; Luan, G.; Zhang, S.; Cai, J.; Ding, J.; Qian, J.; Xie, Z. Spatial-Temporal Characteristic Analysis of Ethnic Toponyms Based on Spatial Information Entropy at the Rural Level in Northeast China. Entropy 2020, 22, 393.

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