A Review on Urban Modelling for Future Smart Cities

被引:1
作者
Zhang, Han [1 ,2 ]
Gong, Zhaoya [1 ,2 ]
Thill, Jean-Claude [3 ]
机构
[1] Peking Univ, Sch Urban Planning & Design, Shenzhen Grad Sch, Shenzhen, Guangdong, Peoples R China
[2] Peking Univ, Key Lab Earth Surface Syst & Human Earth Relat, Minist Nat Resources China, Shenzhen Grad Sch, Shenzhen, Guangdong, Peoples R China
[3] Univ N Carolina, Dept Geog & Earth Sci, Charlotte, NC 27599 USA
来源
SPATIAL DATA AND INTELLIGENCE, SPATIALDI 2024 | 2024年 / 14619卷
关键词
Smart city; Urban modelling; Urban informatics; Big data;
D O I
10.1007/978-981-97-2966-1_25
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The rapid development of information technology has brought about the emergence of urban multi-source big data and the improvement of computing power, and promoted the emergence of new technologies such as artificial intelligence, making the study paradigm of urban modelling face change. Based on the concept of smart city, this paper sorts out the types of urban big data in the information age, and puts forward new opportunities and challenges brought by big data to urban modelling research; Secondly, this paper lists a number of cases for reference on how big data can provide services to the public in the form of network and infrastructure; Finally, the latest progress in the innovation of new technologies such as artificial intelligence, deep learning, data mining, etc. caused by the improvement of computing power is discussed.
引用
收藏
页码:346 / 355
页数:10
相关论文
共 5 条
[1]   Future smart cities requirements, emerging technologies, applications, challenges, and future aspects [J].
Javed, Abdul Rehman ;
Shahzad, Faisal ;
Rehman, Saif Ur ;
Bin Zikria, Yousaf ;
Razzak, Imran ;
Jalil, Zunera ;
Xu, Guandong .
CITIES, 2022, 129
[2]   Implementing Data-Driven Smart City Applications for Future Cities [J].
Kaluarachchi, Yamuna .
SMART CITIES, 2022, 5 (02) :455-474
[3]   Understanding 'smart cities': Intertwining development drivers with desired outcomes in a multidimensional framework [J].
Yigitcanlar, Tan ;
Kamruzzaman, Md ;
Buys, Laurie ;
Ioppolo, Giuseppe ;
Sabatini-Marques, Jamile ;
da Costa, Eduardo Moreira ;
Yun, JinHyo Joseph .
CITIES, 2018, 81 :145-160
[4]   Deep learning in environmental remote sensing: Achievements and challenges [J].
Yuan, Qiangqiang ;
Shen, Huanfeng ;
Li, Tongwen ;
Li, Zhiwei ;
Li, Shuwen ;
Jiang, Yun ;
Xu, Hongzhang ;
Tan, Weiwei ;
Yang, Qianqian ;
Wang, Jiwen ;
Gao, Jianhao ;
Zhang, Liangpei .
REMOTE SENSING OF ENVIRONMENT, 2020, 241
[5]   Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network [J].
Yuan, Qiangqiang ;
Zhang, Qiang ;
Li, Jie ;
Shen, Huanfeng ;
Zhang, Liangpei .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (02) :1205-1218