Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata-Reference-Cited by-同舟云学术

Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata

Published:2020-01-14 Issue:7 Volume:34 Page:1475-1499
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Zhai Yaqian¹²^ORCID,Yao Yao¹²^ORCID,Guan Qingfeng¹²^ORCID,Liang Xun¹²,Li Xia³^ORCID,Pan Yongting¹²^ORCID,Yue Hanqiu¹²^ORCID,Yuan Zehao¹²,Zhou Jianfeng¹²

Affiliation:

1. School of Geography and Information Engineering, China University of Geosciences, Wuhan, Hubei, China

2. National Engineering Research Center of GIS, China University of Geosciences, Wuhan, Hubei, China

3. Key Lab of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2020.1711915

Reference58 articles.

1. From raster to vector cellular automata models: A new approach to simulate urban growth with the help of graph theory

2. From Cells to Cities

3. Implementation of a vector-based cellular automata model for simulating land-use changes

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