{"title":"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","authors":"Zihao Zhou, Yimin Chen, Xiaoping Liu, Xinchang Zhang, Honghui Zhang","doi":"10.1080/13658816.2023.2298296","DOIUrl":null,"url":null,"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...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A maps-to-maps approach for simulating urban land expansion based on convolutional long short-term memory neural networks\",\"authors\":\"Zihao Zhou, Yimin Chen, Xiaoping Liu, Xinchang Zhang, Honghui Zhang\",\"doi\":\"10.1080/13658816.2023.2298296\",\"DOIUrl\":null,\"url\":null,\"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...\",\"PeriodicalId\":14162,\"journal\":{\"name\":\"International Journal of Geographical Information Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-01-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Geographical Information Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/13658816.2023.2298296\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Geographical Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/13658816.2023.2298296","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A maps-to-maps approach for simulating urban land expansion based on convolutional long short-term memory neural networks
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...
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
