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Street surface condition of wealthy and poor neighborhoods: the case of Los Angeles

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Abstract

Are wealthy neighborhoods visually more attractive than poorer neighborhoods? Past studies provided a positive answer to this question for characteristics such as green space and visible pollution. The condition of streets is one of the characteristics that can not only contribute to neighborhoods’ aesthetics, but can also affect residents’ health and mobility. In this study, we investigate whether street condition of wealthy neighborhoods is different from poorer neighborhoods. We resolved the difficulty of data collection using a dataset that utilized artificial intelligence and laser imaging techniques to collect the data of street condition from 98 zip codes in Los Angeles, CA, and later, we conducted correlations between the metrics of neighborhood affluence and their street condition. Our results showed no positive correlation between neighborhood affluence and the condition of streets. On the contrary, the results favored a negative correlation, indicating that poorer neighborhoods had better streets than wealthy neighborhoods. By discussing possible reasons for these results, we call for future research that would show the direction and the extent of correlation between neighborhood affluence and street condition for other cities and in larger scales. Additionally, we discuss how artificial intelligence and automatic data collection techniques enable us to gather data of street condition for urban planning and management.

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Source: Google Street View

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The sources of data for street surface condition and affluence status of neighborhoods are specified in the text and References section.

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  1. College of Information Sciences and Technology, The Pennsylvania State University, State College, USA

    Pooyan Doozandeh, Limeng Cui & Rui Yu

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  1. Pooyan Doozandeh
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  2. Limeng Cui
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Correspondence to Pooyan Doozandeh.

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Appendix A

Appendix A

List of the 98 zip codes in the Los Angeles metropolitan area that were used in the analysis: 90003, 90004, 90005, 90006, 90007, 90008, 90010, 90011, 90012, 90013, 90014, 90015, 90016, 90017, 90018, 90019, 90020, 90021, 90023, 90024, 90025, 90026, 90027, 90028, 90029, 90030, 90031, 90032, 90033, 90034, 90035, 90036, 90037, 90038, 90039, 90041, 90042, 90043, 90045, 90046, 90047, 90048, 90049, 90057, 90059, 90060, 90062, 90064, 90065, 90066, 90067, 90068, 90069, 90070, 90071, 90077, 90094, 90095, 90210, 90248, 90272, 90291, 90293, 90402, 90502, 90710, 90744, 91040, 91303, 91304, 91306, 91311, 91316, 91324, 91325, 91326, 91331, 91335, 91343, 91344, 91345, 91352, 91356, 91364, 91367, 91401, 91402, 91403, 91405, 91406, 91411, 91423, 91436, 91601, 91602, 91604, 91606, 91607.

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Doozandeh, P., Cui, L. & Yu, R. Street surface condition of wealthy and poor neighborhoods: the case of Los Angeles. AI & Soc 38, 1185–1192 (2023). https://doi.org/10.1007/s00146-022-01603-y

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