COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA

The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide huma...

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Main Authors: R. Cao, W. Tu, J. Cao, Q. Li
Format: Article
Language:English
Published: Copernicus Publications 2016-06-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/471/2016/isprs-archives-XLI-B2-471-2016.pdf
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spelling doaj-a8a8a92e69914405a7e55db4f0be94012020-11-25T00:42:40ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342016-06-01XLI-B247147610.5194/isprs-archives-XLI-B2-471-2016COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATAR. Cao0R. Cao1W. Tu2W. Tu3J. Cao4Q. Li5Q. Li6Q. Li7Shenzhen Key Lab of Spatial Smart Sensing and Service, College of Civil Engineering, Shenzhen University, Shenzhen 518060, ChinaKey Lab for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, ChinaShenzhen Key Lab of Spatial Smart Sensing and Service, College of Civil Engineering, Shenzhen University, Shenzhen 518060, ChinaKey Lab for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, ChinaState Key Lab of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, PR ChinaShenzhen Key Lab of Spatial Smart Sensing and Service, College of Civil Engineering, Shenzhen University, Shenzhen 518060, ChinaKey Lab for Geo-Environment Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, ChinaState Key Lab of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, PR ChinaThe quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ) level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/471/2016/isprs-archives-XLI-B2-471-2016.pdf
collection DOAJ
language English
format Article
sources DOAJ
author R. Cao
R. Cao
W. Tu
W. Tu
J. Cao
Q. Li
Q. Li
Q. Li
spellingShingle R. Cao
R. Cao
W. Tu
W. Tu
J. Cao
Q. Li
Q. Li
Q. Li
COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet R. Cao
R. Cao
W. Tu
W. Tu
J. Cao
Q. Li
Q. Li
Q. Li
author_sort R. Cao
title COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA
title_short COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA
title_full COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA
title_fullStr COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA
title_full_unstemmed COMPARISON OF URBAN HUMAN MOVEMENTS INFERRING FROM MULTI-SOURCE SPATIAL-TEMPORAL DATA
title_sort comparison of urban human movements inferring from multi-source spatial-temporal data
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2016-06-01
description The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ) level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/471/2016/isprs-archives-XLI-B2-471-2016.pdf
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