Issue |
E3S Web Conf.
Volume 237, 2021
3rd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2020)
|
|
---|---|---|
Article Number | 04019 | |
Number of page(s) | 5 | |
Section | Ecological Environment, Urban Planning and Construction | |
DOI | https://doi.org/10.1051/e3sconf/202123704019 | |
Published online | 09 February 2021 |
Prediction of Underground Space Development Function of Existing Industrial District in City Based on CA-Markov Model
1
School of mechanics and civil engineering, China university of mining and technology, Xuzhou 211116, China
2
Jiangsu collaborative innovation center for building energy saving and construction technology, Xuzhou 211116, China
* Corresponding author: hongxiaochun00@163.com
Scientific analysis of the spatial evolution of existing industrial areas in cities and prediction of future development needs will help to rationally allocate land resources in existing industrial areas in urban renewal, scientifically and rationally develop underground space, and promote the sustainable development of existing industrial areas. First of all, the development mode and leading function type of the existing industrial zone in the city are sorted out, and its corresponding underground space development function is further sorted out. It is found that the underground space development of the existing industrial zones in the city is closely related to the dominant functions and location of the ground renewal. To scientifically guide the development of underground space in existing industrial areas in cities, this study proposes a method based on the dynamics model and the CA-Markov model to predict the functions of underground space development in existing industrial areas in cities, which will improve the efficiency and Benefits to promote the rational allocation of land resources is of great significance.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.