A global map of urban extent from nightlights

By Yuyu Zhou, Steven J. Smith, Kaiguang Zhao, M. Imhoff, Allison M. Thomson, B. Bond‐Lamberty, Ghassem R. Asrar, Xuesong Zhang, Chunyang He, Christopher D. Elvidge. 2015

291 citations recorded by the source corpus.

Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering not just water and carbon cycling, biodiversity, and climate, but also demography, public health, and economy. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. We developed a method to map the urban extent from the defense meteorological satellite program/operational linescan system nighttime stable-light data at the global level and created a new global 1 km urban extent map for the year 2000. Our map shows that globally, urban is about 0.5% of total land area but ranges widely at the regional level, from 0.1% in Oceania to 2.3% in Europe. At the country level, urbanized land varies from about 0.01 to 10%, but is lower than 1% for most (70%) countries. Urbanization follows land mass distribution, as anticipated, with the highest concentration between 30° N and 45° N latitude and the largest longitudinal peak around 80° W. Based on a sensitivity analysis and comparison with other global urban area products, we found that our global product of urban areas provides a reliable estimate of global urban areas and offers the potential for producing a time-series of urban area maps for temporal dynamics analyses.

Subfields: Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/0f7ac3217841adcad8f60695b1349169a7dbc717

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Jun-cheng Yang
2. Xiaoping Liu
3. Chenghu Zhou
4. W. Cai

In Global and Planetary Change

1. Xi Li
2. Xiaoping Liu
3. Xun Li
4. Chunyang He
5. Christopher D. Elvidge
6. Marc T. J. Johnson

Citations in the corpus

• Mapping global urban boundaries from the global artificial impervious area (GAIA) data (2020, methodology): “Additionally, given that there exists a saturation effect inNTLdata, the urban extent is mapped using pre-calibrated optimal thresholds, which are determined based on high-resolution land cover maps (Zhou et al 2014, 2015).”
• Evolution of life in urban environments (2017, background): “Although many of these examples are likely adaptive, changes in selection are rarely quantified directly (71, 72), and nonadaptive processes such as genetic drift and restricted gene flow are pervasive and may explain divergence across a single city (2, 37).”
• Applications of Satellite Remote Sensing of Nighttime Light Observations: Advances, Challenges, and Perspectives (2019, methodology): “In the first dataset, the global urban area in 2000 was mapped using the DMSP-OLS NTL data and an optimized threshold method [71,72].”