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Exploring the Spatial Relationship Between Demographic Indicators and the Built Environment of a City

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Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation (SMC 2021)

Abstract

In addition to global and regional drivers of urbanization, neighborhood development in urban areas across the United States has been shown to be influenced by various local socio-economic factors. These factors, despite varying across socio-economic groups, have large implications regarding a population’s vulnerability to extreme climate events, including heat waves resulting in adverse health impacts. Additionally, the demographics of an urban area can shape its infrastructural characteristics, causing different populations groups to face varying levels of risks and benefits. As a result, the urban morphology and socio-economic characteristics of a city are deeply intertwined; however, their interactions on a finer scale are not yet fully understood. This research aims to better understand the relationships between various socio-economic factors and the built environment of a city, considering variability in building types, and temperature patterns. This research focuses on the city of Las Vegas, NV, and uses spatial data analysis to understand the correlation between of socio-economic characteristics, building morphology, building characteristics, and temperature data to understand the correlation between these various factors. Results of these research shows there is a distinct pattern of clustering of socio-economic characteristics with the city and there is a distinct correlation between age and cost, socio-economic characteristics, and locations of high heat distribution within the city.

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References

  1. UN Department of Economic and Social Affairs (UNDESA). 68% of the world population projected to live in urban areas by 2050, says UN (2018). Accessed https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html

  2. Hoffman, J.S., Shandas, V., Pendleton, N.: The effects of historical housing policies on resident exposure to intra-urban heat: a study of 108 US urban areas. Climate 8(1), 12 (2020)

    Article  Google Scholar 

  3. Mishra, V., Ganguly, A. R., Nijssen, B., Lettenmaier, D.P.: Changes in observed climate extremes in global urban areas. Environ. Res. Lett. 10(2), 024005 (2015)

    Google Scholar 

  4. Boampong, E., Çubukçu, K.: The organization of urban space and socio-economic characteristics: a graph theory-based empirical study using hierarchical cluster analysis. Planlama 29(3), 259–270 (2019). https://doi.org/10.14744/planlama.2019.61687

  5. Venerandi, A., Quattrone, G., Capra, L.: A scalable method to quantify the relationship between urban form and socio-economic indexes. EPJ Data Sci. 7(1), 1–21 (2018). https://doi.org/10.1140/epjds/s13688-018-0132-1

    Article  Google Scholar 

  6. US Census Bureau. QuickFacts: Las Vegas City, Nevada (n.d.). Accessed https://www.census.gov/quickfacts/lasvegascitynevada

  7. US Department of Energy and Pacific Northwest National Laboratory. Guide to determining climate regions by country. In: Building America Best Practices Series, vol. 7.3 (2015). Accessed https://www.energy.gov/sites/prod/files/2015/10/f27/ba_climate_region_guide_7.3.pdf

  8. US Census Bureau. Glossary (n.d.). Accessed https://www.census.gov/programs-surveys/geography/about/glossary.html

  9. Brelsford, C.: Las Vegags Block Group Buildings Data (2021). Accessed https://doi.ccs.ornl.gov/ui/doi/328

  10. Thornton, M.M., Shrestha, R., Wei, Y., Thornton, P.E., Kao, S., Wilson, B.E.: Daymet: daily surface weather data on a 1-km grid for North America, Version 4. ORNL DAAC, Oak Ridge, Tennessee, USA2020). https://doi.org/10.3334/ORNLDAAC/1840

  11. Hengl, T.: Long-term MODIS LST day-time and night-time temperatures, sd and differences at 1 km based on the 2000–2017 time series (1.0). Zenodo (2018). https://doi.org/10.5281/zenodo.1435938

  12. US Environmental Protection Agency. EJSCREEN (2020). Accessed https://www.epa.gov/ejscreen/download-ejscreen-data

  13. US Environmental Protection Agency. EJSCREEN technical documentation (2019). Accessed https://www.epa.gov/sites/default/files/2021-04/documents/ejscreen_technical_document.pdf

  14. Aksoezen, M., Daniel, M., Hassler, U., Kohler, N.: Building age as an indicator for energy consumption. Energy Build. 87, 74–86 (2015)

    Article  Google Scholar 

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Open-source code and visualizations can be accessed via the Github page: https://github.com/ridhima-singh/smcdc2021_challenge5.

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Singh, R., Dumas, M.A. (2022). Exploring the Spatial Relationship Between Demographic Indicators and the Built Environment of a City. In: Nichols, J., et al. Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation. SMC 2021. Communications in Computer and Information Science, vol 1512. Springer, Cham. https://doi.org/10.1007/978-3-030-96498-6_27

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  • DOI: https://doi.org/10.1007/978-3-030-96498-6_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-96497-9

  • Online ISBN: 978-3-030-96498-6

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