Articles | Volume 21, issue 1
Research article
21 Jan 2021
Research article |  | 21 Jan 2021

A glimpse into the future of exposure and vulnerabilities in cities? Modelling of residential location choice of urban population with random forest

Sebastian Scheuer, Dagmar Haase, Annegret Haase, Manuel Wolff, and Thilo Wellmann

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Cited articles

Ali, L., Haase, A., and Heiland, S.: Gentrification through Green Regeneration? Analyzing the Interaction between Inner-City Green Space Development and Neighborhood Change in the Context of Regrowth: The Case of Lene-Voigt-Park in Leipzig, Eastern Germany, Land, 9, 24,, 2020. a
Andersson, E., Haase, D., Scheuer, S., and Wellmann, T.: Neighbourhood character affects the spatial extent and magnitude of the functional footprint of urban green infrastructure, Landscape Ecol., 35, 1605–1618,, 2020. a
Antipov, E. A. and Pokryshevskaya, E. B.: Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics, Expert Syst. Appl., 39, 1772–1778, 2012. a, b
Aslam, A., Masoumi, H., Naeem, N., and Ahmad, M.: Residential location choices and the role of mobility, socioeconomics, and land use in Hafizabad, Pakistan, Urbani Izziv, 30, 115–128, 2019. a, b
Balmes, J. R., Earnest, G., Katz, P. P., Yelin, E. H., Eisner, M. D., Chen, H., Trupin, L., Lurmann, F., and Blanc, P. D.: Exposure to traffic: Lung function and health status in adults with asthma, J. Allergy Clin. Immun., 123, 626–631, 2009. a, b
Short summary
The choice of residential location is one of the drivers shaping risks in cities. We model likely outcomes of this decision-making process for distinct socioeconomic groups in the city of Leipzig, Germany, using random forests and geostatistical methods. In so doing, we uncover hot spots and cold spots that may indicate spatial patterns and trends in exposure and vulnerabilities of urban population, to shed light on how residential location choice affects these risk components as a process.
Final-revised paper