A maps-to-maps approach for simulating urban land expansion based on convolutional long short-term memory neural networks

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-01-03 DOI:10.1080/13658816.2023.2298296

Zihao Zhou, Yimin Chen, Xiaoping Liu, Xinchang Zhang, Honghui Zhang

引用次数: 0

Abstract

Cellular automata (CA) have been prevalently used for the simulation of urban land change. However, how to effectively learn the spatial-temporal dynamics of urban development from time-series data...

查看原文本刊更多论文

基于卷积长短期记忆神经网络的 "地图到地图 "模拟城市土地扩张方法

细胞自动机（CA）已被广泛用于模拟城市土地变化。然而，如何从时间序列数据中有效地学习城市发展的时空动态...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.