Mining hourly population dynamics by activity type based on decomposition of sequential snapshot data-Reference-Cited by-同舟云学术

Mining hourly population dynamics by activity type based on decomposition of sequential snapshot data

Published:2022-08-16 Issue:1 Volume:15 Page:1395-1416
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Shi Qingli¹^ORCID,Zhuo Li¹²³^ORCID,Tao Haiyan¹²^ORCID,Li Qiuping¹²

Affiliation:

1. Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, People’s Republic of China

2. Guangdong Provincial Engineering Research Centre for Public Security and Disaster, Guangzhou, People’s Republic of China

3. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, People’s Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province for Distinguished Young Scholars

Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2022.2110290

Reference51 articles.

1. LandScan USA: a high-resolution geospatial and temporal modeling approach for population distribution and dynamics

2. An Endmember Initialization Scheme for Nonnegative Matrix Factorization and Its Application in Hyperspectral Unmixing

3. Emerging social media data on measuring urban park use

4. Mapping monthly population distribution and variation at 1-km resolution across China

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