Urbanization in European regions based on night lights

Stathakis, Demetris; Tselios, Vassilis; Faraslis, Ioannis

doi:10.1016/j.rsase.2015.10.001

Cited by 51 publications

(35 citation statements)

References 28 publications

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“…A buffer was used to minimize any bias in eBird sampling protocols (e.g., mis-placement of eBird checklists by participants, and to account for travelling checklists throughout an area) and the size of the buffer has no discernible influence on the relative urban-score differences among species (Callaghan et al 2019a). We used the VIIRS night-time lights (Elvidge et al 2017) as a proxy for urbanization because it is correlated positively with impervious surface cover and human population density (Pandey et al 2013, Zhang and Seto 2013, Stathakis et al 2015) and because of its global availability and ease of use with Google Earth Engine (Gorelick et al 2017). For each buffer, raw radiance values were used -after filtering of the data to minimize the influence of fires, degraded data and other light source contamination (Elvidge et al 2017) -between 2013-2017 and the average raw radiance value was taken as an annual composite.…”

Section: Species-specific Scoresmentioning

confidence: 99%

A continental measure of urbanness predicts avian response to local urbanization

Callaghan¹,

Major²,

Cornwell³

et al. 2019

Preprint

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Understanding species-specific relationships with their environment is essential for ecology, biogeography, and conservation biology. Moreover, understanding how these relationships change with spatial scale is critical to mitigating potential threats to biodiversity. But methods which measure inter-specific variation in responses to environmental parameters, generalizable across multiple spatial scales, are lacking. We used broad-scale citizen science data, over a continental scale, integrated with remotely-sensed products, to produce a measure of response to urbanization for a given species at a continental-scale. We then compared these responses to modelled responses to urbanization at a local-scale, based on systematic sampling within a series of small cities. For 49 species which had sufficient data for modelling, we found a significant relationship (R2 = 0.51) between continental-scale urbanness and local-scale urbanness. Our results suggest that continental-scale responses are representative of small-scale responses to urbanization. We also found that relatively few citizen science observations (~250) are necessary for reliable estimates of continental-scale urban scores to predict local-scale response to urbanization. Our method of producing species-specific urban scores is robust and can be generalized to other taxa and other environmental variables with relative ease.

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Section: Species-specific Scoresmentioning

confidence: 99%

A continental measure of urbanness predicts avian response to local urbanization

Callaghan¹,

Major²,

Cornwell³

et al. 2019

Preprint

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“…Remote sensing provides raster data support. Due to the time issue of MODIS data and the classification difficulty of Landsat data, nighttime light remote sensing data have been widely used in urban and regional analysis [16,17]. For example, built-up areas that are extracted from nighttime light data can cover the parks within cities that are ignored by Landsat data [18].…”

Section: Of 24mentioning

confidence: 99%

Modeling Polycentric Urbanization Using Multisource Big Geospatial Data

Xie

Zheng

et al. 2019

Remote Sensing

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Understanding the dynamics of polycentric urbanization is important for urban studies and management. This paper proposes an analytical model that uses multisource big geospatial data to characterize such dynamics to facilitate policy making. There are four main steps: 1) main centers and subcenters are identified using spatial cluster analysis and geographically weighted regression (GWR) based on Visible Infrared Imaging Radiometer Suite (VIIRS)/NPP and social media check-in data; 2) the built-up areas are extracted by using Defense Meteorological Satellite Program – Operational Linescan System (DMSP/OLS) gradient images; 3) the economic corridors that connect the main center and subcenters are constructed using road network data from Open Street Map (OSM) with the least-cost distance method; and 4) the major urban development direction is identified by analyzing the changes in built-up areas within the economic corridors. The model is applied to three major cities in northeastern, central, and northwestern China (Shenyang, Wuhan, and Xi'an) from 1992 to 2012.

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“…mis-placement of eBird checklists by participants, and to account for travelling checklists throughout an area) and the size of the buffer has no discernible influence on the relative urban-score differences among species (Callaghan et al 2019a). We used the VIIRS night-time lights (Elvidge et al 2017) as a proxy for urbanization because it is correlated positively with impervious surface cover and human population density (Pandey et al 2013, Zhang and Seto 2013, Stathakis et al 2015 and because of its global availability and ease of use with Google Earth Engine (Gorelick et al 2017). For each buffer, raw radiance values were used -after filtering of the data to minimize the influence of fires, degraded data and other light source contamination (Elvidge et al 2017) -between 2013 and 2017 and the average raw radiance value was taken as an annual composite.…”

Section: Species-specific Scoresmentioning

confidence: 99%

A continental measure of urbanness predicts avian response to local urbanization

et al. 2019

View full text Add to dashboard Cite

Understanding species‐specific relationships with their environment is essential for ecology, biogeography and conservation biology. Moreover, understanding how these relationships change with spatial scale is critical to mitigating potential threats to biodiversity. But methods which measure inter‐specific variation in response to environmental parameters that are also generalizable across multiple spatial scales are scarce. We used broad‐scale avian citizen science data, over continental Australia, integrated with remotely‐sensed products, to produce a measure of urban‐tolerance for a given species at a continental‐scale. We then compared these urban‐tolerances to modelled responses to urbanization at a local‐scale, based on systematic sampling within four small cities. For 49 species which had sufficient data for modelling, we found a significant relationship (R2 = 0.51) between continental‐scale urbanness and local‐scale urbanness. We also found that relatively few citizen science observations (~250) are necessary for reliable estimates of continental‐scale species‐specific urban scores to predict local‐scale response to urbanization. Our approach demonstrates the applicability of broad‐scale citizen science data, contrasting both the spatial grain and extent of standard point‐count surveys generally only conducted at small spatial scales. Continental‐scale responses in Australia are representative of small‐scale responses to urbanization among four small cities in Australia, suggesting that our method of producing species‐specific urban scores is robust and may be generalized to other locations lacking appropriate data.

show abstract

Urbanization in European regions based on night lights

Cited by 51 publications

References 28 publications

A continental measure of urbanness predicts avian response to local urbanization

A continental measure of urbanness predicts avian response to local urbanization

Modeling Polycentric Urbanization Using Multisource Big Geospatial Data

A continental measure of urbanness predicts avian response to local urbanization

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