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Mapping Lightscapes: Spatial Patterning of Artificial Lighting in an Urban Landscape

Overview of attention for article published in PLOS ONE, May 2013
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Title
Mapping Lightscapes: Spatial Patterning of Artificial Lighting in an Urban Landscape
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0061460
Pubmed ID
Authors

James D. Hale, Gemma Davies, Alison J. Fairbrass, Thomas J. Matthews, Christopher D. F. Rogers, Jon P. Sadler

Abstract

Artificial lighting is strongly associated with urbanisation and is increasing in its extent, brightness and spectral range. Changes in urban lighting have both positive and negative effects on city performance, yet little is known about how its character and magnitude vary across the urban landscape. A major barrier to related research, planning and governance has been the lack of lighting data at the city extent, particularly at a fine spatial resolution. Our aims were therefore to capture such data using aerial night photography and to undertake a case study of urban lighting. We present the finest scale multi-spectral lighting dataset available for an entire city and explore how lighting metrics vary with built density and land-use. We found positive relationships between artificial lighting indicators and built density at coarse spatial scales, whilst at a local level lighting varied with land-use. Manufacturing and housing are the primary land-use zones responsible for the city's brightly lit areas, yet manufacturing sites are relatively rare within the city. Our data suggests that efforts to address light pollution should broaden their focus from residential street lighting to include security lighting within manufacturing areas.

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Geographical breakdown

Country Count As %
United States 3 2%
Switzerland 1 <1%
Australia 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Brazil 1 <1%
Unknown 168 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 16%
Student > Master 28 16%
Researcher 27 15%
Student > Bachelor 20 11%
Other 11 6%
Other 35 20%
Unknown 27 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 22%
Environmental Science 27 15%
Earth and Planetary Sciences 14 8%
Social Sciences 11 6%
Engineering 11 6%
Other 38 22%
Unknown 37 21%