COVID-19 Pandemic Assessment by Night-Lights

Classification of Recreation Opportunity Spectrum Using Night Lights for Evidence of Humans and POI Data for Social Setting

Sustainability ◽

10.3390/su13147782 ◽

2021 ◽

Vol 13 (14) ◽

pp. 7782

Author(s):

Wenjing Zeng ◽

Yongde Zhong ◽

Dali Li ◽

Jinyang Deng

Keyword(s):

Large Scale ◽

Regional Scale ◽

Hunan Province ◽

Social Settings ◽

Recreation Opportunity Spectrum ◽

City District ◽

Night Lights ◽

Recreational Resources ◽

Metropolitan Counties ◽

Land Types

The recreation opportunity spectrum (ROS) has been widely recognized as an effective tool for the inventory and planning of outdoor recreational resources. However, its applications have been primarily focused on forest-dominated settings with few studies being conducted on all land types at a regional scale. The creation of a ROS is based on physical, social, and managerial settings, with the physical setting being measured by three criteria: remoteness, size, and evidence of humans. One challenge to extending the ROS to all land types on a large scale is the difficulty of quantifying the evidence of humans and social settings. Thus, this study, for the first time, developed an innovative approach that used night lights as a proxy for evidence of humans and points of interest (POI) for social settings to generate an automatic ROS for Hunan Province using Geographic Information System (GIS) spatial analysis. The whole province was classified as primitive (2.51%), semi-primitive non-motorized (21.33%), semi-primitive motorized (38.60%), semi-developed natural (30.99%), developed natural (5.61%), and highly developed (0.96%), which was further divided into three subclasses: large-natural (0.63%), small natural (0.27%), and facilities (0.06%). In order to implement the management and utilization of natural recreational resources in Hunan Province at the county (city, district) level, the province’s 122 counties (cities, districts) were categorized into five levels based on the ROS factor dominance calculated at the county and provincial levels. These five levels include key natural recreational counties (cities, districts), general natural recreational counties (cities, districts), rural counties (cities, districts), general metropolitan counties (cities, districts), and key metropolitan counties (cities, districts), with the corresponding numbers being 8, 21, 50, 24, and 19, respectively.

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Convergence across Subnational Regions of Bangladesh – What the Night Lights Data Say?

SSRN Electronic Journal ◽

10.2139/ssrn.3853803 ◽

2021 ◽

Author(s):

Syed Abul Basher ◽

Jobaida Behtarin ◽

Salim Rashid

Keyword(s):

Night Lights

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Night Lights

Patrick Moore’s Practical Astronomy Series - Lights in the Sky ◽

10.1007/978-1-84628-761-9_10 ◽

2007 ◽

pp. 125-160

Author(s):

Michael Maunder

Keyword(s):

Night Lights

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FORECASTING URBAN EXPANSION BASED ON NIGHT LIGHTS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b8-1049-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 1049-1054 ◽

Cited By ~ 2

Author(s):

D. Stathakis

Keyword(s):

Time Series ◽

Linear Regression ◽

Correlation Coefficient ◽

Urban Expansion ◽

Image Correlation ◽

Spatially Explicit ◽

Expansion Model ◽

Night Lights

Forecasting urban expansion models are a very powerful tool in the hands of urban planners in order to anticipate and mitigate future urbanization pressures. In this paper, a linear regression forecasting urban expansion model is implemented based on the annual composite night lights time series available from National Oceanic and Atmospheric Administration (NOAA). The product known as 'stable lights' is used in particular, after it has been corrected with a standard intercalibration process to reduce artificial year-to-year fluctuations as much as possible. Forecasting is done for ten years after the end of the time series. Because the method is spatially explicit the predicted expansion trends are relatively accurately mapped. Two metrics are used to validate the process. The first one is the year-to-year Sum of Lights (SoL) variation. The second is the year-to-year image correlation coefficient. Overall it is evident that the method is able to provide an insight on future urbanization pressures in order to be taken into account in planning. The trends are quantified in a clear spatial manner.

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Eyes of the Night Lights

The Value of Hawaii 2 ◽

10.1515/9780824840259-009 ◽

2017 ◽

pp. 49-51

Author(s):

Mailani Neal

Keyword(s):

Night Lights

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Southern Realism

Divine Programming ◽

10.1093/oso/9780190054373.003.0004 ◽

2020 ◽

pp. 77-98

Author(s):

Charlotte E. Howell

Keyword(s):

American South ◽

Television Drama ◽

Southern Culture ◽

Television Production ◽

Cultural Specificity ◽

Christian Culture ◽

The American South ◽

Night Lights ◽

Characteristic Part ◽

Friday Night

Friday Night Lights (NBC, 2006–2011) and Rectify (SundanceTV, 2013–2016) exemplified containing Christianity’s middlebrow appeal through displacement onto the cultural specificity of a realistically portrayed American South within a quality television drama. These two shows represent Christianity as both the dominant faith of their characters and as a characteristic part of Southern culture. Creatives used the milieu of an “authentic” American South to shift religion away from themselves and their quality-audience expectations, maintaining acceptability within the dominant non-Christian culture of television production. This displacement safely contained religion within the creatives’ production culture, allowing them to acknowledge Christianity’s religious content, but only within the peculiar particularity of the American South.

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