2016
DOI: 10.5194/isprsarchives-xli-b2-471-2016
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Comparison of Urban Human Movements Inferring From Multi-Source Spatial-Temporal Data

Abstract: ABSTRACT: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 boar… Show more

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Cited by 3 publications
(2 citation statements)
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“…However, remote sensing images can only capture physical characteristics, the information they provide is limited. With the advent of the big data era, the technique of data collection and processing is improved, the social sensing data is growing rapidly, such as mobile phone data [8], [9], trajectory data [10], point of interests (POIs) [11], [12] and so on. Social sensing data always have a strong correlation with human activities, which can reflect the socio-economy information that remote sensing images lack [13].…”
Section: Introductionmentioning
confidence: 99%
“…However, remote sensing images can only capture physical characteristics, the information they provide is limited. With the advent of the big data era, the technique of data collection and processing is improved, the social sensing data is growing rapidly, such as mobile phone data [8], [9], trajectory data [10], point of interests (POIs) [11], [12] and so on. Social sensing data always have a strong correlation with human activities, which can reflect the socio-economy information that remote sensing images lack [13].…”
Section: Introductionmentioning
confidence: 99%
“…The answer of this question will provide us with a comprehensive understanding of urban travel. Recently, Cao et al (2016) investigated the relationship between taxi travel and human travel from mobile phone positing data. However, the relationship between each mode, like buses, metro, and taxi are not investigated.…”
Section: Introductionmentioning
confidence: 99%