Authors: Michelle Stuhlmacher*, Arizona State University, Matei Georgescu, Arizona State University, Yina Hu, Peking University, Ran Goldblatt, New Light Technologies, B.L. Turner II, Arizona State University, Sarthak Gupta, Arizona State University, Amy Frazier, Arizona State University, Nicholas Clinton, Google, Robert C Balling, Arizona State University
Topics: Urban Geography, Remote Sensing, Land Use and Land Cover Change
Keywords: urbanization, urban, pattern, remote sensing, Google Earth Engine, United States, India, China, urban sustainability, LULC
Session Type: Paper
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As the proportion of the world’s population living in urban areas grows, so too do the opportunities to design urban systems that enhance sustainability, resilience, and other desired socio-ecological outcomes. An essential first step, and a growing area of research, is understanding the underlying patterns and processes of urban system change. Much of this research, however, focuses on a single city or set of cities at one point in time. In the era of globalization and global environmental change, there is a need for greater understanding of urban patterns and processes over time. Employing remote sensing computational innovations, we examine long-term patterns and processes across multiple cities and countries. Specifically, we ask: are the patterns of built-up lands in large urban areas in China, India, and the United States becoming more homogeneous? Using Nighttime Lights and Landsat satellite imagery, we classified urbanization in 150 cities from 1995-2015 in five-year time steps. We find that cities in each country are following a similar trend in shape, connectedness and size (i.e., more circular, more connected, larger). This homogenization has consequences for a variety of socio-ecological processes. We evaluate the implications of homogenization in terms of the day and nighttime surface urban heat island intensity, and find that measures related to sprawl (shape, adjacency) are most strongly related. Daytime and nighttime surface urban heat island intensity, however, have opposite relationships with urban form; any alterations made to urban form to ameliorate the surface urban heat island must make trade-offs between daytime and nighttime.
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