Understanding urbanization: A study of census and satellite-derived urban classes in the United States, 1990-2010

Most of future population growth will take place in the world's cities and towns. Yet, there is no well-established, consistent way to measure either urban land or people. Even census-based urban concepts and measures undergo frequent revision, impeding rigorous comparisons over time and place. This study presents a new spatial approach to derive consistent urban proxies for the US. It compares census-designated urban blocks with proxies for land-based classifications of built-up areas derived from time-series of the Global Human Settlement Layer (GHSL) for 1990-2010. This comparison provides a new way to understand urban structure and its changes: Most land that is more than 50% built-up, and people living on such land, are officially classified as urban. However, 30% of the census-designated urban population and land is located in less built-up areas that can be characterized as mainly suburban and peri-urban in nature. Such insights are important starting points for a new urban research program: creating globally and temporally consistent proxies to guide modelling of urban change.

[1]  Stefan Leyk,et al.  Descriptor : HISDAC-US , historical settlement data compilation for the conterminous United States over 200 years , 2018 .

[2]  C. Small,et al.  A global analysis of urban reflectance , 2005 .

[3]  J. Mennis Generating Surface Models of Population Using Dasymetric Mapping , 2003, The Professional Geographer.

[4]  Huadong Guo,et al.  A Global Human Settlement Layer From Optical HR/VHR RS Data: Concept and First Results , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[5]  Claude N. Williams,et al.  Quantifying the effect of urbanization on U.S. Historical Climatology Network temperature records , 2013 .

[6]  José I. Barredo,et al.  Are European Cities Becoming Dispersed? A Comparative Analysis of 15 European Urban Areas , 2006 .

[7]  D. Haase,et al.  Endless Urban Growth? On the Mismatch of Population, Household and Urban Land Area Growth and Its Effects on the Urban Debate , 2013, PloS one.

[8]  N. Wrigley,et al.  Statistical applications in the spatial sciences , 1981 .

[9]  Julea Andreea Maria,et al.  Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014 , 2016 .

[10]  Vincent V. Salomonson Encyclopedia of Remote Sensing , 2014 .

[11]  M. Montgomery The Urban Transformation of the Developing World , 2008, Science.

[12]  D. Lu,et al.  Use of impervious surface in urban land-use classification , 2006 .

[13]  M. Friedl,et al.  A new map of global urban extent from MODIS satellite data , 2009 .

[14]  Manuel Wolff,et al.  Compact or spread? A quantitative spatial model of urban areas in Europe since 1990 , 2018, PloS one.

[15]  R. Stott,et al.  The World Bank , 2008, Annals of tropical medicine and parasitology.

[16]  Gilbert Shapiro,et al.  The Linkage of Data Describing Overlapping Geographical Units , 1973 .

[17]  D A Plane,et al.  Migration up and down the urban hierarchy and across the life course , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[18]  Bicheron Patrice,et al.  GlobCover - Products Description and Validation Report , 2008 .

[19]  Executive Summary World Urbanization Prospects: The 2018 Revision , 2019 .

[20]  Barbara P. Buttenfield,et al.  Dasymetric Modeling and Uncertainty , 2014, Annals of the Association of American Geographers. Association of American Geographers.

[21]  S I Hay,et al.  Determining global population distribution: methods, applications and data. , 2006, Advances in parasitology.

[22]  Jacqueline Nivard,et al.  Redefining urban: a new way to measure metropolitan areas , 2012 .

[23]  P. Kareiva,et al.  Open Space Loss and Land Inequality in United States' Cities, 1990–2000 , 2010, PloS one.

[24]  Pierre Soille,et al.  Assessment of the Added-Value of Sentinel-2 for Detecting Built-up Areas , 2016, Remote. Sens..

[25]  Karen C. Seto,et al.  Futures of global urban expansion: uncertainties and implications for biodiversity conservation , 2013 .

[26]  Duncan Black,et al.  Urban evolution in the USA , 2003 .

[27]  J. Bongaarts,et al.  United Nations Department of Economic and Social Affairs, Population Division World Family Planning 2020: Highlights, United Nations Publications, 2020. 46 p. , 2020 .

[28]  T. Buettner,et al.  Urban Estimates and Projections at the United Nations: The Strengths, Weaknesses, and Underpinnings of the World Urbanization Prospects , 2015 .

[29]  Jonathan P. Schroeder Target-Density Weighting Interpolation and Uncertainty Evaluation for Temporal Analysis of Census Data , 2007 .

[30]  Michael F. Goodchild,et al.  Areal interpolation: A variant of the traditional spatial problem , 1980 .

[31]  R. R. Vatsavai,et al.  Complex settlement pattern extraction with multi-instance learning , 2013, Joint Urban Remote Sensing Event 2013.

[32]  H. Overman,et al.  Causes of Sprawl: A Portrait from Space , 2006 .

[33]  Yu Zhu In Situ Urbanization in Rural China: Case Studies from Fujian Province , 2000 .

[34]  Martino Pesaresi,et al.  A New Method for Earth Observation Data Analytics Based on Symbolic Machine Learning , 2016, Remote. Sens..

[35]  Budhendra L. Bhaduri,et al.  Estimating urban areas: New insights from very high-resolution human settlement data , 2018 .

[36]  S. Openshaw A million or so correlation coefficients : three experiments on the modifiable areal unit problem , 1979 .

[37]  C. Elvidge,et al.  VIIRS night-time lights , 2017, Remote Sensing of Night-time Light.

[38]  C. Mellander,et al.  Night-Time Light Data: A Good Proxy Measure for Economic Activity? , 2015, PloS one.

[39]  Son V. Nghiem,et al.  Up and out: A multifaceted approach to characterizing urbanization in Greater Saigon, 2000–2009 , 2019, Landscape and Urban Planning.

[40]  Son V. Nghiem,et al.  Urban Environments, Beijing Case Study , 2014, Encyclopedia of Remote Sensing.

[41]  K. Seto,et al.  A Meta-Analysis of Global Urban Land Expansion , 2011, PloS one.

[42]  Gernot Wagner,et al.  Night-time lights: A global, long term look at links to socio-economic trends , 2017, PloS one.

[43]  C. Revenga,et al.  Urban growth, climate change, and freshwater availability , 2011, Proceedings of the National Academy of Sciences.

[44]  Richard L. Morrill,et al.  METROPOLITAN, URBAN, AND RURAL COMMUTING AREAS: TOWARD A BETTER DEPICTION OF THE UNITED STATES SETTLEMENT SYSTEM , 1999 .

[45]  Chunyang He,et al.  How much of the world’s land has been urbanized, really? A hierarchical framework for avoiding confusion , 2014, Landscape Ecology.

[46]  Graeme Hugo,et al.  Toward a New Conceptualization of Settlements for Demography , 2003 .

[47]  I. MacGregor‐Fors Misconceptions or misunderstandings? On the standardization of basic terms and definitions in urban ecology , 2011 .

[48]  Stefan Leyk,et al.  Assessing the Accuracy of Multi-Temporal Built-Up Land Layers across Rural-Urban Trajectories in the United States. , 2018, Remote sensing of environment.

[49]  Barbara P. Buttenfield,et al.  Comparing the effects of an NLCD-derived dasymetric refinement on estimation accuracies for multiple areal interpolation methods , 2015 .

[50]  Thomas Esch,et al.  Urban Footprint Processor—Fully Automated Processing Chain Generating Settlement Masks From Global Data of the TanDEM-X Mission , 2013, IEEE Geoscience and Remote Sensing Letters.

[51]  Sérgio Freire,et al.  Remote sensing derived continental high resolution built-up and population geoinformation for crisis management , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[52]  K. Seto,et al.  The New Geography of Contemporary Urbanization and the Environment , 2010 .

[53]  B. Anderson,et al.  The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones , 2007 .

[54]  B. Cohen,et al.  Cities Transformed: Demographic Change and Its Implications in the Developing World , 2003 .

[55]  K. Seto,et al.  Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools , 2012, Proceedings of the National Academy of Sciences.