2019
DOI: 10.3390/rs12010027
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Exploring Spatial and Temporal Connection Patterns among the Districts in Chongqing Based on Highway Passenger Flow

Abstract: Investigating regional connections and their influencing factors from the perspective of "flow" space is one of the foundations of promoting regional development. In this article, the data we used includes actual highway passenger flow data, National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light remote sensing data, and socioeconomic data. We analyzed the spatial distribution pattern, connection intensity and spatial autocorrelation of highway passenger flow i… Show more

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Cited by 12 publications
(5 citation statements)
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“…Scholars made NTL as a proxy for freight traffic to predict traffic and freight volume [13]. NTL also can be used in research into the evaluation of highway traffic conditions [14] and the spatial distribution pattern of highways [15]. Electric power services are fundamental to prosperity and economic development, and increasing research effort has been made to relate electric energy consumption to NTL.…”
Section: Introductionmentioning
confidence: 99%
“…Scholars made NTL as a proxy for freight traffic to predict traffic and freight volume [13]. NTL also can be used in research into the evaluation of highway traffic conditions [14] and the spatial distribution pattern of highways [15]. Electric power services are fundamental to prosperity and economic development, and increasing research effort has been made to relate electric energy consumption to NTL.…”
Section: Introductionmentioning
confidence: 99%
“…When I i is less than 0, this suggests that the observed objects largely exhibit low-high and high-low clustering trends, and the spatial correlation is negative. When I i equals 0, the observed objects exhibit a random distribution, and no spatial correlation occurs [81].…”
Section: Methodsmentioning
confidence: 99%
“…In addition, population flow also reflects the similarities between regions. For example, Huang et al analyze the day-night patterns of public transportation data to determine population flow during different periods [8]. Fu et al develop a general collective learning method and show the correlation between regional function and residential mobility [9].…”
Section: Related Workmentioning
confidence: 99%