Normalization of time series DMSP-OLS nighttime light images for urban growth analysis with Pseudo Invariant Features

Wei, Ye; Liu, Hongxing; Song, Wei; Yu, Bailang; Xiu, Chunliang

doi:10.1016/j.landurbplan.2014.04.015

Cited by 114 publications

(72 citation statements)

References 37 publications

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“…This makes our work different from other studies in the literature from three aspects: (1) growth patterns were examined at the metropolitan level instead of at the urban level [27,47]; (2) growth patterns were examined by employing all lit-pixels instead of the urban-pixels [4,32,38]; (3) growth …”

Section: On Growth Patterns In Terms Of Intensification and Expansionmentioning

confidence: 97%

“…On one hand, previous findings had suggested strong relationships between digital number (DN) values with urban population density [16], built area density [17], house vacancy rate [18], and other socio-economic indicators [19][20][21][22][23]; On the other hand, they have a relative high temporal frequency of observation. Previous studies mainly focused on the dynamics of urbanization in general [24][25][26][27][28] or urban expansion itself in particular [29][30][31], and they ignored the influence from the non-urban lit-pixels [3,8,32,33]. In addition, there were many other studies focusing on the dynamics of urbanization or urban expansion from the pixel perspective [26], for individual megacities [34,35], at a local or region level [13,36], at a country level [27,37], or even in a long time period [38].…”

Section: Introductionmentioning

confidence: 99%

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Characterizing the Growth Patterns of 45 Major Metropolitans in Mainland China Using DMSP/OLS Data

2017

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Abstract:Understanding growth patterns at the metropolitan level is instructive for better planning and policy making on sustainable urban development. Using DMSP/OLS data from 1992 to 2013, this article aims to investigate growth patterns of major metropolitans in Mainland China from the aspects of intensification and expansion. We start by calibrating the DMSP/OLS data and selecting 45 major metropolitans. On intensification, results suggest that aggregately, metropolitans displayed cyclical pattern over time and large metropolitans tended to have higher levels of intensification than moderate or small ones. Individually, metropolitans with similar intensification over time could be clustered together using Dendrogram, and evolution pattern of the clusters exhibited similarity to the aggregated one. On expansion, results show that aggregately metropolitans displayed a decreasing trend over time, and moderate or small metropolitans tended to have higher levels of expansion than large ones. Particularly, moderate metropolitans were more likely to expand adjacently, and small ones were more likely to experience scatter or corridor expansion. Each metropolitan can be represented by a mixed expansion model over time, which might tell where and how much expansion occurred in the current year. Furthermore, intensification is highly correlated with expansion over time for small metropolitans, but they are poorly correlated for large or moderate ones. Lastly, the high correlation of intensification and expansion with the change of GDP in each year indicates the reliability of our work.

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Section: On Growth Patterns In Terms Of Intensification and Expansionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Characterizing the Growth Patterns of 45 Major Metropolitans in Mainland China Using DMSP/OLS Data

2017

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“…Alternatively, we can directly use the night light data [42] to describe the urban scale; the night light data can reflect the spatial geographic information and intensity change procession, which can reflect the urban area, population, GDP, and other perspectives of the city scale [43]. We can also use the average time between two cities (taking the train or the highway) instead of considering the two cities by the straight line distance analysis.…”

Section: Uncertainty Analysis and Improvementmentioning

confidence: 99%

Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China

Fan

Zhang²,

et al. 2018

Discrete Dynamics in Nature and Society

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The spatial pattern and evolution of urban system have been hot research issues in the field of urban research. In this paper, the network analysis method based on the gravity model and the related measurements were used to reveal the properties of the spatial pattern and evolution of the urban system in the HRB (Huaihe River Basin) of China. The findings of this study are as follows: During the period from 2006 to 2014, the economic contact between the HRB cities has been strengthened, but the differences between cities have been expanding. In general, the HRB cities have not yet formed a close network structure, and a trend of economic integration has not been found. This paper expresses the spatial pattern and evolution of urban system in an intuitive way and helps to explain the evolution mechanism of urban system. The method was confirmed by empirical research. Because of the operational and visual expression, this method has broad application prospects in the urban system research.

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“…In our review, we found that the release of different datasets derived from the DMSP/OLS database increased the extent and depth of studies. However, even the latest Version 4 dataset has apparent limitations in terms of data comparability and consistency [23,79]. Thus, a new rigorous and robust dataset of long-term nighttime images after systematic inter-annual and inter-satellite calibrations could stimulate relevant studies.…”

Section: Major Challengesmentioning

confidence: 99%

Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review

et al. 2014

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Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) nighttime light data in 1992, a variety of datasets based on this database have been produced and applied to monitor and analyze human activities and natural phenomena. However, differences among these datasets and how they have been applied may potentially confuse researchers working with these data. In this paper, we review the ways in which data from DMSP/OLS nighttime light images have been applied over the past two decades, focusing on differences in data processing, research trends, and the methods used among the different application areas. Five main datasets extracted from this database have led to many studies in various research areas over the last 20 years, and each dataset has its own strengths and limitations. The number of publications based on this database and the diversity of authors and institutions involved have shown promising growth. In addition, researchers have accumulated vast experience OPEN ACCESS Remote Sens. 2014, 6 6845 retrieving data on the spatial and temporal dynamics of settlement, demographics, and socioeconomic parameters, which are "hotspot" applications in this field. Researchers continue to develop novel ways to extract more information from the DMSP/OLS database and apply the data to interdisciplinary research topics. We believe that DMSP/OLS nighttime light data will play an important role in monitoring and analyzing human activities and natural phenomena from space in the future, particularly over the long term. A transparent platform that encourages data sharing, communication, and discussion of extraction methods and synthesis activities will benefit researchers as well as public and political stakeholders.

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Normalization of time series DMSP-OLS nighttime light images for urban growth analysis with Pseudo Invariant Features

Cited by 114 publications

References 37 publications

Characterizing the Growth Patterns of 45 Major Metropolitans in Mainland China Using DMSP/OLS Data

Characterizing the Growth Patterns of 45 Major Metropolitans in Mainland China Using DMSP/OLS Data

Spatial Pattern and Evolution of Urban System Based on Gravity Model and Whole Network Analysis in the Huaihe River Basin of China

Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review

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