This report explores the ongoing conversation around development and gentrification in Chicago, focusing on drivers such as the proliferation of short-term rental properties and green space development. By employing spatial analysis on variables like mortgage rates, Airbnb prices, and green space distribution, alongside a review of existing literature, this report examines housing affordability in the context of gentrification. Gentrification is a multifaceted and complex phenomenon. The aim of this report is not to attribute it to a single cause or to propose a definitive solution, but to explore how development relates to the experiences of residents. Green space development, in particular, plays a dual role in the discussion: it is necessary and beneficial to residents’ health and well-being, yet it is often contentious due to its potential association with gentrification and the displacement of long-term communities.

Data Sources

Data is sourced from the following platforms: Inside Airbnb (listing locations and associated pricing information), the U.S. Census Bureau and American Community Survey (socioeconomic data at the census tract level), OpenStreetMap (public park accessibility), Landsat (satellite bands converted to NDVI), the National Integrated Heat Health Information System and CAPA Strategies Chicago Heat Watch (temperature and heat mapping). I employed the maptiles package within R to create a light grey basemap, sourced from ESRI. All geospatial tranformations are performed in CRS EPSG 26916, suitable for city-level mapping that would minimize distortion in Chicago.

Airbnb Distribution and Pricing Across Cook County, Illinois

Since its founding in 2007, Airbnb has become a leader in the short-term rental market, earning its hosts over $5.7 billion in 2023 and offering 7.7 million active listings (Airbnb, 2024). Scholars consider it a key driver of gentrification, as buy-to-let properties pose significant risk to long-term residents by rising rents, house prices, and diminishing housing availability (Cocola-Gant & Gago, 2019; Hoffman & Heisler, 2021). In purchasing properties for short-term rentals, buy-to-let investors inevitably reshape the financial and cultural landscape of the neighborhoods (Cocola-Gant & Gago, 2019). Figures 1, 2 and 3 display Airbnb distribution and pricing across Cook County, Illinois, where Chicago is located. Notably, most listings are concentrated near downtown, indicating that tourists prefer to stay close to that area. Broadly, listings become sparse towards South Chicago and away from the border of Lake Michigan.

Figure 1

Figure 1 distinguishes between entire and partial units, revealing that many listings are likely buy-to-let properties. Entire-unit listings are more directly linked to gentrification, as they remove housing stock from the long-term rental market, diminishing housing availability and posing higher displacement risks on long-term residents.

Figure 2

The concentration of listings in northern Chicago and near downtown, as shown in Figures 1 and 2, highlights the importance of location in the market. For visualization clarity in Figure 2, I converted NA values in the number of listings per tract column to zero, they indicated an absence of listings.

Figure 3

Figure 3 reinforces the trend of desirability centered around downtown with a cluster in higher pricing in the same areas, though some anomalies in outlying tracts may reflect proximity to specific amenities or luxury properties. For this visual, I removed NA price values, as computing mean listing prices was not possible with missing data. Figure 3 then shows the mean listing prices across applicable tracts.

Census-tract Level Socio-Economic Analysis

Figure 4

Figure 4 is a side-by-side visualization of the pricing experience for long term residents of Chicago, accounting homeowners and renters. From the ACS (2018-2022), I extracted Median Mortgage Payment Rates and Median Gross Rent. I sought to display recent median costs of each to understand spatial distribution of long-term living costs, as buy-to-let gentrification impacts both rental and owner markets (Rabiei-Dastjerdi et al., 2022).

Interestingly, the upper limit for median rental costs exceeded the median mortgage costs, suggesting that rental prices in some areas may be more expensive than owning a home. The maps reveal common spatial distribution in high living costs, particularly in North Chicago and along the Chicago River, while mortgage rates in South Chicago remain relatively moderate, with higher rental costs in that area.

Figure 5

Figure 5 is a bivariate representation of the spatial relationship between housing affordability and Airbnb pricing across Cook County, Chicago. I took the natural log of the respective median values, as housing and Airbnb price distributions are often highly skewed. The natural log handles outliers and approximates a normal distribution, creating more meaningful spatial comparisons.

The spatial distribution of high costs in both parameters, shown in dark purple where they intersect, reveal that living in or close to downtown Chicago is expensive for Airbnb renters and homeowners alike. The map also reveals neighborhoods where mortgage costs are high but Airbnb prices are relatively low, and vice versa. These areas of negative correlation suggest unique market dynamics, where long-term residents might be attracted to areas with good schools, for example; this is less important to a tourist, which would influence the placement of short-term rental properties.

Further analysis of these parameters over time would be valuable to determine how the spatial relationship has evolved; it could guide housing policy or regulation of short-term rentals. This type of visualization underscores the importance of comprehensive access to Airbnb data, as a temporal analysis would reveal change over time.

Public Park Access and Green Space Distribution

Figure 6

Utilizing OpenStreetMap (OSM), I extracted points from a set of amenities typically open to the public for outdoor recreation. The classification, which I named “parks,” included amenities with the following tags: park, nature reserve, recreation ground, playground, pitch, and garden. I produced a heat map of these amenities using points created by the centroid of each. The heatmap reveals a high density of public park space in the western zone of Cook County, clustered mainly around Downtown Chicago. South Chicago is relatively barren, as is Northeast Chicago.

Figure 7

Relating park distribution to Airbnb distribution, Figure 7 represents every Airbnb listing within Cook County and reveals which are within a 200-meter radius of a park. Airbnb listings within 200 meters of a park, represented by the blue marks, are heavily clustered around downtown Chicago. Evidenced by the heatmap, there are fewer public parks located in South Chicago. Correspondingly, there are fewer Airbnb listings in South Chicago, and the majority of listings present fall outside of the 200-meter threshold.

Figure 8 (Part B, Option 3)

Green development is often cited as a gentrification driver. Though recognized as an essential component of a healthy city, literature suggests that urban greening can trigger gentrification. Anguelovski et al. state that the degree to which greening plays a role in gentrification can be classified by “lead”, “integrated”, or “subsidiary”, dependent on a city’s scope of other amenities that might drive gentrification more than greening (2022). In subsidiary green gentrification cities, green space is a likely driver of gentrification, but to a lesser extent than other changes in the built environment. Chicago-level analysis suggests that it falls within this classification. Green space has the potential to play a role in gentrification, but other neighborhood characteristics (such as the distance to downtown) were more predictive (Stuhlmacher et al., 2022).

To explore this relationship, I chose to implement a Normalized Difference Vegetation Index (NDVI) analysis to compare average values with the report’s proxy for housing affordability, the natural log of median mortgage costs. NDVI is a calculation derived from red and near-infrared bands in Landsat data that utilizes the reflective and absorbent properties of vegetation. NDVI values approaching +1 are likely to correspond with areas of high vegetation. From the Landsat data, I calculated the average NDVI value per census tract and created a bivariate map to visualize how NDVI spatially relates to mortgage costs across the city. The minimal presence of deep purple, indicating high values in each parameter, suggests that vegetation and mortgage costs are not strongly correlated. The broad patch of light blue, for instance, marks an area of very high mortgage costs and very low NDVI.

The figure suggests that increased vegetation cover in lower-cost areas may not significantly affect housing prices, which may mitigate concerns about green gentrification in Chicago. The results are consistent with those of Stuhlmacher et al., who did not determine a strong empirical association between green space of any type and gentrification in Chicago (2022). With this conclusion, policies could focus on creating green space in historically underserved communities without drastically inflating mortgage costs.

The findings derived from this figure, however, are limited; a more reliable approach to analysing the relationship between green space development and housing costs would be to employ a temporal analysis to track changes in each parameter over time. Moreover, conducting the same analysis using other proxies for home affordability would provide a more comprehensive understanding, such as rent prices and income. While this figure suggests a very weak relationship between the two factors, I would encourage policy makers to first conduct deeper analysis before arriving at a conclusion that informs decisions on green space development.

Figure 9

I sought to analyze the role of vegetation in mitigating the extreme heat, an important factor for residents’ health in urban environments like Chicago. Vegetation limits concrete heat absorption and radiation while offering shade that can make a person feel less hot by more than 10°C (World Health Organization).

Figure 9 explores the spatial relationship between vegetation and urban heat extremes, with an added layer of public park access boundaries for further analysis. It incorporates three datasets: NDVI derived from Landsat, split into a binary of +/- 0.15; Average High Temperature calculations from the Chicago Heat Watch, split into a binary of +/- 90 °F to indicate extreme heat; and a shapefile of park boundaries derived from an OSM query. As Chicago is highly urbanized, I set a low threshold for “vegetated” areas to ensure that even sparse vegetation was included amidst the city’s concrete coverage. The park boundaries extracted from OSM are overlaid with the purpose of highlighting public spaces with high NDVI and low heat.

The resulting figure reveals a strong negative correlation between NDVI and Average High Temperature. This is consistent with existing studies that reveal inverse correlations between surface radiation temperature and NDVI, further classifying green space as a distinct player in mitigating the heat island effect (Zhang et al., 2012). Moreover, the map displays several park boundaries that contain “high” NDVI values and “low” temperature values. This suggests that parks, particularly those with more vegetation, can play a vital role in heat reduction in high-temperature cities like Chicago.

I would recommend that Chicago decision-makers invest in green space development to improve the lived experience of their residents, while incorporating measures to protect them from gentrification. Though literature review and Figure 8 reveal that green space does not appear to be a strong driver of gentrification in Chicago, it should not be discarded in the development of new built environments. Appropriate anti-displacement measures might include zoning protections around new park developments, or affordable housing measures like rent control or property tax incentives.

Conclusion

This report analysis socio-economic, Landsat, and Airbnb data to explore development and gentrification trends as they relate to short-term rentals and green space. Airbnb listings are densely clustered in North Chicago and near downtown, where high prices reveal high desirability. Median mortgage and rent costs also trend high in these areas. Park presence is most concentrated in central Chicago and near Lake Michigan. An NDVI analysis shows a weak correlation with housing affordability, suggesting green development is not a primary driver of gentrification in Chicago. Chicago policy-makers may consider creating more green space to improve environmental health, paired with anti-displacement measures like rent control or property tax incentives to protect long-term residents.

References

Airbnb. “Airbnb Q4-2023 and Full-Year Financial Results.” Airbnb Newsroom, 13 Feb. 2024, news.airbnb.com/airbnb-q4-2023-and-full-year-financial-results/.

Anguelovski, Isabelle, et al. “Green Gentrification in European and North American Cities.” Nature Communications, vol. 13, no. 1, 2 July 2022, www.nature.com/articles/s41467-022-31572-1, https://doi.org/10.1038/s41467-022-31572-1.

CAPA, and NIHHIS. Chicago, Illinois: Heat Watch Report. Chicago.gov, Oct. 2023. https://www.chicago.gov/content/dam/city/depts/cdph/environment/heat_watch/Summary-Report-Heat-Watch-Chicago_CAPA-12.15.2023.pdf

Cocola-Gant, Agustin, and Ana Gago. “Airbnb, Buy-To-Let Investment and Tourism-Driven Displacement: A Case Study in Lisbon.” Environment and Planning A: Economy and Space, vol. 53, no. 7, 19 Aug. 2019, pp. 1671–1688, https://doi.org/10.1177/0308518x19869012.

Hoffman, Lily M., and Barbara Schmitter Heisler. Airbnb, Short-Term Rentals and the Future of Housing. Routledge, 3 Nov. 2020.

Rabiei-Dastjerdi, Hamidreza, et al. “Which Came First, the Gentrification or the Airbnb? Identifying Spatial Patterns of Neighbourhood Change Using Airbnb Data.” Habitat International, vol. 125, July 2022, p. 102582, https://doi.org/10.1016/j.habitatint.2022.102582.

Stuhlmacher, Michelle, et al. “The Role of Green Space in Chicago’s Gentrification.” Urban Forestry & Urban Greening, vol. 71, May 2022, p. 127569, https://doi.org/10.1016/j.ufug.2022.127569.

World Health Organization. “Heat and Health.” World Health Organization, 28 May 2024, www.who.int/news-room/fact-sheets/detail/climate-change-heat-and-health.

Zhang, Yang, et al. “Study on Urban Heat Island Effect Based on Normalized Difference Vegetated Index:A Case Study of Wuhan City.” Procedia Environmental Sciences, vol. 13, 2012, pp. 574–581, https://doi.org/10.1016/j.proenv.2012.01.048. Accessed 31 Dec. 2019