Historical Evolution and Characteristics of Villages Based on ArcGIS Core Density Analysis
A Case Study of Shandong Province, China
- DOI
- 10.2991/978-2-38476-062-6_153How to use a DOI?
- Keywords
- ArcGIS; nuclear density analysis; historical space; evolution characteristics
- Abstract
The village is the witness of the development of Chinese civilization and the carrier of cultural heritage. The study of the diachronic evolution of the village can deeply reveal the evolution mechanism of the development of Chinese civilization and the laws and characteristics of village development. Based on the core density analysis function of ArcGIS, taking Shandong Province as an example, on the basis of fully mining historical data, this paper analyzes the spatial distribution characteristics of villages in different time sections, analyzes the laws and dynamic mechanism of village development and evolution, and obtains a clear pattern of village evolution in Shandong Province. The research results show that the spatial analysis function of ArcGIS can play a great role in dealing with spatial analysis problems with a large time span.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yong Fan AU - De-ke Zhang PY - 2023 DA - 2023/07/11 TI - Historical Evolution and Characteristics of Villages Based on ArcGIS Core Density Analysis BT - Proceedings of the 2023 2nd International Conference on Social Sciences and Humanities and Arts (SSHA 2023) PB - Atlantis Press SP - 1192 EP - 1200 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-062-6_153 DO - 10.2991/978-2-38476-062-6_153 ID - Fan2023 ER -