Classifying Urban Functional Zones by Integrating POIs, Place2vec, and LDA-Reference-Cited by-同舟云学术

Classifying Urban Functional Zones by Integrating POIs, Place2vec, and LDA

Published:2023-12 Issue:4 Volume:149 Page:
ISSN:0733-9488
Container-title:Journal of Urban Planning and Development
language:en
Short-container-title:J. Urban Plann. Dev.

Author:

Yang Xin¹,Yang Yilai²,Zheng Xinqi³

Affiliation:

1. Lecturer, School of Information and Control Engineering, Qingdao Univ. of Technology, Shandong 266520, China (corresponding author).

2. Master’s Student, School of Information and Control Engineering, Qingdao Univ. of Technology, Shandong 266520, China.

3. Professor, School of Information Engineering, China Univ. of Geosciences (Beijing), Beijing 10083, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Urban Studies,Development,Geography, Planning and Development,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JUPDDM.UPENG-4541

Reference38 articles.

1. POI mining for land use classification: A case study;Andrade R.;ISPRS Int. J. Geo-Inf.,2020

2. DFCNN-Based Semantic Recognition of Urban Functional Zones by Integrating Remote Sensing Data and POI Data

3. Computer Network Information Center Chinese Academy of Sciences. 2020. “Gaofen-1 WFV data product.” Geospatial Data Cloud. Accessed June 8 2023. https://bjdl.gscloud.cn/sources/download/428/GF1_WFV2_4752002?sid=4Fopcv-_I8mn7bZLvJU5SQnLp4ZzJXhQYmlrLA0JbiPpkg&uid=22651.

4. Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach;Du S. H.;Remote Sens. Environ.,2021

5. A SOE-based learning framework using multi-source big data for identifying urban functional zones;Feng Y.;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2021

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