Small Urban Areas Research Articles

Using GEOBIA and Vegetation Indices to Assess Small Urban Green Areas in Two Climatic Regions

The importance of small urban green areas has increased in the context of rapid urbanization and the densification of the urban tissue. The analysis of these areas through remote sensing has been limited due to the low spatial resolution of freely available satellite images. We propose a timeseries analysis on 3 m resolution Planet images, using GEOBIA and vegetation indices, with the aim of extracting and assessing the quality of small urban green areas in two different climatic and biogeographical regions: temperate (Bucharest, Romania) and mediterranean (Athens, Greece). Our results have shown high accuracy (over 91%) regarding the extraction of small urban green areas in both cities across all the analyzed images. The timeseries analysis showed consistency with respect to location for around 55% of the identified surfaces throughout the entire period. The vegetation indices registered higher values in the temperate region due to the vegetation characteristics and city plan of the two cities. For the same reasons, the increase in the vegetation density and quality, as a result of the distance from the city center, and the decrease in the density of built-up areas, is more obvious in Athens. The proposed method provides valuable insights into the distribution and quality of small urban green areas at the city level and can represent the basis for many analyses, which is currently limited by poor spatial resolution.

Bird Flight Resistance Analysis and Planning Strategies in Urban Regeneration Areas: A Case Study of a Certain Area in Shenzhen, China

At present, the sharp decline in urban biodiversity worldwide is severe. Conducting biological perspective analysis and proposing space construction solutions during urban regeneration can greatly alleviate the contradiction between urban construction and biodiversity conservation. In this study, birds were taken as biological representatives, and a certain area in Shenzhen with strong conservation needs was used as an example. Based on a thorough analysis of bird status, the minimum resistance model was applied to establish a resistance surface describing the real flight movement of the indicator species and to construct a bird conservation pattern from the flight process of birds. The results show that: (1) bird flight resistance is the lowest in the southern green space and northern woodland around the reservoir in the research region, and the resistance is higher in the central part, but the path of least resistance therein has the potential to become a corridor. (2) From the perspective of the community structure of green space vegetation, the sparse woodland and shrubland in the research region have low resistance and high richness, which are the most ideal green space forms for birds; from the perspective of architecture, bird flight resistance shows a negative correlation with building height and a positive correlation with building density. The final urban regeneration design plan is thus derived, and the validity of the method is verified based on the biodiversity index. This study reveals the possibility of applying bird flight resistance analysis based on the minimum resistance model to small and medium-scale urban regeneration areas, and also provides insight into the correlation between flight resistance and spatial design elements, which can assist decision-makers, planners and developers in spatial design and planning from a biological standpoint.

COVID-19′s impact on older adults’ cycling behaviors in a small, auto-centric urban area

Research has shown an increase in cycling during COVID-19. This study builds on previous work by exploring COVID’s impact on older cyclists (65+) residing in a small, auto-centric urban area. A survey (n = 198) demonstrated that, on average, cycling frequency decreased and average distance/trip increased. This suggests a less pronounced impact among older adults residing in a small urban area. However, interviews (n = 24) showed that cycling during the pandemic was associated with feelings of accomplishment, enjoyment, improved self-esteem, and increased freedom by allowing them to get out despite social distancing requirements. Further, among respondents reporting increased cycling (n = 76), most (79 %) plan to maintain cycling habits post-pandemic, citing reasons such as personal health, enjoyment, and the social aspect of cycling. These findings could support efforts promoting cycling among older adults, pointing to aspects for designing voluntary travel behavior change (VTBC) programs.

Physicochemical Characteristics of PM2.5 Based on Long-term Hourly Data at National Intensive Monitoring Sites in Korea

The objective of this study was to analyze the temporal and spatial characteristics of fine particulate matters by using huge hourly datasets of PM2.5, including chemical information monitored at the 6 national intensive monitoring sites (NIMSs) from 2013 to 2018 in Korea. Hourly PM2.5 raw datasets were obtained from the National Institute of Environmental Research (NIER) in Korea. Monitoring sites included urban, rural/agricultural, industrial, and marine environments. Since the PM2.5 concentration steadily decreased nationwide, each species concentration also decreased in general. One of key reasons for decreasing PM2.5 might be explained by the implementation of domestic fine dust reduction policies and external influences such as PM2.5 concentration reduction in China. It was observed that 45.0% of all datasets for 6 years were classified as good condition. The average sum of 14 elements over all sites in 2018 was calculated to be 501.5 ng/m3, and its mass ratio for PM2.5 (21.9 μg/m3) was 2.30%. The inorganic elements were generally higher in industrial/urban areas than in agricultural areas. In addition, the average TC (total carbon) over all 6 sites was 28.3% of PM2.5 with the range of 23.6% to 31.4%. The TC in small urban areas was much higher than that in marine areas or even that in large, populated urban area/industrial areas. It seemed that the latter areas were better controlled than the former area in terms of combustion activities of fossil fuels. It is suggested that these results could be play an important role as important basic data to manage ambient air quality and establish effective emission reduction strategies in each region.

Accessing drug treatment programs in Atlantic Canada: the experiences of people who use substances

People who use substances (PWUS) (e.g. inject substances) are at risk of many harms. Various services help reduce risks including drug treatment programs such as withdrawal management and opioid agonist treatment. Much of the research on PWUS’ experiences of treatment programs is set in large urban centers creating a knowledge gap of experiences in other places. Our study helps address this gap by exploring PWUS’ experiences of treatment programs in Atlantic Canada which is a region with many small urban centers and rural areas. One-on-one qualitative interviews were conducted with 55 PWUS focusing on their experiences of treatment program facilitators (or what helped with access and retention), and/or barriers to treatment access and retention (or what was not helpful). Data were analyzed for key themes/subthemes and organized using a slightly modified Rhodes’ risk environment framework. PWUS’ experiences of facilitators and barriers cross all four environments of treatment programs: policy and practice, physical, social, and resource environments. For some PWUS, barriers impacted their access to or retention in treatment, and hence are of serious concern given the current toxic illicit drug supply in Canada. Several barriers are shaped by drug criminalization and thus this research points to the need for decriminalization to help reduce barriers.

Spatial generalization in sketch maps: A systematic classification

Sketch maps are one of the most commonly used instruments to study people's perception of the environment. While previous research has focused on analyzing sketch maps with respect to their accuracy, completeness, or distortion, there is little study focusing on generalization (the level of geometric details of the depicted features) in sketch maps. Furthermore, when investigating people's mental representations of space, researchers compute the accuracy or completeness of sketch maps via a one-to-one comparison of sketched features with features in metric map data. The task of one-to-one comparison becomes problematic because features in sketch map often represent many features in a metric map. This paper identifies the frequently occurring generalizations in 108 sketch maps of small urban area by manually extracting generalized features such as streets and buildings and classifying them based on similarities. We found three generalization types in streets, two in junctions and four in buildings. To evaluate our classification, we created 10 sketch maps by systematically introducing the nine identified generalizations. A study was conducted wherein five raters were briefed about the different generalization types. Each of them classified the features in sketch maps as generalized and non-generalized. We found a high inter-rater agreement, implying the comprehensibility and clarity of the identified generalization types. We propose that such systematic view on the generalization in sketch maps would standardize the process of comparing them with metric map data as well as enable a new way of analyzing sketch maps with respect to generalization.

Urban Sustainability: Integrating Socioeconomic and Environmental Data for Multi-Objective Assessment

The large concentration of the world’s population in cities, along with rapid urbanization, have brought numerous environmental and socioeconomic challenges to sustainable urban systems (SUS). However, current SUS studies focus heavily on ecological aspects, rely on SUS indicators that are not supported by available data, lack comprehensive analytical frameworks, and neglect SUS regional differences. This paper develops a novel approach to assessing urban sustainability from regional perspectives using commonly enumerated socioeconomic statistics. It integrates land use and land cover change data and ecosystem service values, applies data mining analytics to derive SUS indicators, and evaluates SUS states as trade-offs among relevant SUS indicators. This synthetic approach is called the integrated socioeconomic and land-use data mining–based multi-objective assessment (ISL-DM-MOA). The paper presents a case study of urban sustainability development in cities and counties in Inner Mongolia, China, which face many environmental and sustainable development problems. The case study identifies two SUS types: (1) several large cities that boast well-developed economies, diversified industrial sectors, vital transportation locations, good living conditions, and cleaner environments; and (2) a few small counties that have a small population, small urban construction areas, extensive natural grasslands, and primary grazing economies. The ISL-DM-MOA framework innovatively synthesizes currently available socioeconomic statistics and environmental data as a unified dataset to assess urban sustainability as a total socio-environmental system. ISL-DM-MOA deviates from the current indicator approach and advocates the notion of a data-mining-driven approach to derive urban sustainability dimensions. Furthermore, ISL-DM-MOA diverges from the concept of a composite score for determining urban sustainability. Instead, it promotes the concept of Pareto Front as a choice set of sustainability candidates, because sustainability varies among nations, regions, and locations and differs between political, economic, environmental, and cultural systems.

Community food insecurity predicts child maltreatment report rates across Illinois zip codes, 2011–2018

PurposeWe examined how longitudinal changes and inter-community differences of food insecurity rates were associated with child maltreatment report (CMR) rates at the zip code level. We assessed these associations overall, by urbanicity, and within subgroups of age, sex, and maltreatment type. MethodsWe used Illinois statewide zip code-level data from 2011 to 2018. We measured CMR rates based on Illinois child protective services records and food insecurity rates from Feeding America's Map the Meal Gap. We conducted spatial linear modeling to account for spatial dependence with controls for various socioeconomic, demographic, care burden, and instability conditions of communities. ResultsBoth longitudinal changes and inter-community differences of food insecurity rates were significantly associated with increased CMR rates overall and within all subgroups. These associations were significant among all large urban, small urban, and rural areas, while longitudinal changes of food insecurity rates had significantly stronger associations among small urban areas compared with other areas. ConclusionsCommunities experiencing higher food insecurity had higher CMR rates. Increases in food insecurity over time were associated with increases in CMR rates. These associations were reproduced within subgroups of child age, sex, maltreatment type, and urbanicity. Attention and collaborative efforts are warranted for high food insecure communities.

On the potential of commercial microwave link networks for high spatial resolution rainfall monitoring in urban areas

The considerable density of commercial microwave links (CMLs) in urban areas provides an unprecedented opportunity to reconstruct rain fields with high spatial resolution. The aim of this study was to investigate the potential advantages of CML measurements for rain field reconstruction. To this end, we compared the performance of equivalent sensor networks consisting of CMLs, rain gauges (RGs), or a mixture of CMLs and RGs (hybrid network) for near-ground rain field reconstruction under various hypothetical scenarios. Using simulated Gaussian-shaped rain fields and X-band radar rainfall maps as the ground truth, we synthesized CML and RG measurements, which were then used to reconstruct the rain fields. The results, in which the reconstructed rain fields were compared with the ground truth, showed that the CML and RG sensor networks perform similarly in terms of rainfall spatial distribution estimation in areas where dense CML networks are likely to exist. CMLs performed better than RGs in terms of areal rainfall estimation. With a given number of sensors, more CMLs in a hybrid network achieved better areal rainfall estimation. We also study the rain reconstruction performance when using an iterative method, which represents a link by several non-equal virtual rain gauges (VRGs), allowing rainfall intensities along a link to differ. We show that on average, in a small urban area where the density of CMLs is high, representing CMLs by a single VRG is sufficient for rainfall field reconstruction and there is no need to convert a link to multiple VRGs.

How do college students perceive future shared mobility with autonomous Vehicles? A survey of the University of Alabama students

University students are young, open to new technologies, and their perceptions of the Shared Autonomous Vehicles (SAVs) may indicate their travel behaviors in the future. College towns in small urban or suburban areas offer researchers a unique environment to understand the travel behaviors of future commuters, and test emerging mobility services, such as SAVs. The study performs a survey with the aim of understanding university student perception regarding SAVs. The survey was conducted among the University of Alabama students in Tuscaloosa. The key survey questions include their knowledge and attitudes about AV and shared mobility. The results showed 97% of respondents are aware of AVs, but only 41% know specific automation technologies. As for shared mobility services, 98% of respondents are familiar with Uber and Lyft services. The survey also asked survey participants to indicate their Willingness-To-Pay (WTP) for hypothetical SAV services in three price scenarios. The prices were assumed as relative to the cost of using ride-hailing services with human drivers such as Uber and Lyft. Random parameter ordered logit models were developed to uncover the correlates of the WTP for SAV services. The models identified significant relationships between the WTP and various factors related to respondents’ socio-demographics, awareness of AV companies, and experiences with human-driver ride-hailing services. The awareness of AV companies and ride-hailing services is positively related to the WTP for SAV services. Students who know more AV companies appear to have a greater WTP, and students who are heavy users of Uber or Lyft services are also likely to SAV users in the future. Significant variations were also found in model estimates, indicating that some relationships could vary significantly across observations due to the unobserved heterogeneity. The findings offer insights to decision-makers and investors trying to estimate the market potential of emerging mobility services with AVs.

Exploring the potential for sustainable accessibility across settlement types. A Swedish case

The potential for residents of smaller urban and rural areas to benefit from sustainable accessibility is an under-researched area. This paper explores accessibility to important every-day amenities within short travel times and how this differs across geography and mode of travel. The analysis draws on a combination of novel open-source data of the transport system and official Swedish register data of the total population of individuals and workplaces geocoded at a 100-meter resolution. The findings show considerable variation in accessibility to everyday amenities by travel mode for different settlement types. While the car provides good accessibility, short trips by bicycle are a very competitive alternative in urban and suburban areas. Access to every-day amenities by active travel modes is limited outside urban areas. Employing accessibility analysis by settlement type offers a powerful policy support tool for planners charged with developing measures to address sustainable accessibility for small urban and rural areas.

Neighboring Green Network and Landscape Metrics Explain Biodiversity within Small Urban Green Areas—A Case Study on Birds

Cities’ green areas are fragmented patches and are often confined to smaller sizes than the higher built-up proportions. Such small-sized green areas can be essential components of green infrastructure to compensate for biodiversity loss. As a proxy to biodiversity, we studied birds in nine small green area locations of Freiburg and eight area locations in Regensburg in Germany. We investigated the neighboring green networks (distance to the nearest water body and another green area) and landscape metrics (patch abundance and habitat heterogeneity at a 1 km radius) that might benefit and explain bird richness and composition in small green areas. We found that the variations in the observed species richness and composition at the surveyed locations were better explained solely by green networks in Freiburg and by green networks and landscape metrics in Regensburg. In general, it indicates that a small green area could be biodiverse if its spatial distribution considers a nearby water body and other green areas, allowing a higher abundance of similar patches and habitat heterogeneity in the neighborhood.

Comorbid Affective and Substance Use Disorders of Medicaid/Medicare Beneficiaries at an Opioid Treatment Program Serving Small Urban and Rural Communities.

ObjectivesIdentify rates and correlates of comorbid affective and substance use disorders among an understudied population, Medicaid/Medicare beneficiaries receiving care at an opioid treatment program serving patients from small urban and rural areas. Examine whether past-year non-medical opioid use status differentiates comorbidity status.MethodsA cross-sectional, venue-based design was used to recruit a convenience sample of patients treated with methadone for opioid use disorder. Measures were assessed across three domains: (1) demographic characteristics, (2) opioid use characteristics, and (3) comorbid disorders. Brief validated screeners categorized probable comorbid disorders. Bivariate analyses examined correlates of comorbid disorders and determined variable selection for multivariable analyses.ResultsIn this sample (N = 210; mean age = 38.5 years; female = 62.2%; Non-Hispanic White race/ethnicity = 86.1%), comorbid disorders were common. Rates were as follows: current anxiety (48.1%), depression (41.1%), and PTSD (33.7%), and past-year stimulant (27.6%), marijuana (19.0%), alcohol (14.9%), and sedative (7.6%). In bivariate analyses, past-year non-medical opioid use and a greater accumulation of opioid use consequences were associated with most disorders. When including demographic and opioid use characteristics in multivariable analyses, past-year non-medical opioid use was associated with anxiety, PTSD, stimulant use disorder, and sedative use disorder.ConclusionsFew studies have investigated comorbid disorders among this understudied population. This analysis highlights a high burden, especially for affective disorders. Our findings demonstrate that routine, ongoing assessment of non-medical opioid use may be a promising and feasible strategy to detect patients needing integrated care. Future research should investigate whether changes to assessment protocols at opioid treatment programs in small urban and rural settings facilitate care coordination.

Development and Application of a Rainfall Temporal Disaggregation Method to Project Design Rainfalls

A climate model is essential for hydrological designs considering climate change, but there are still limitations in employing raw temporal and spatial resolutions for small urban areas. To solve the temporal scale gap, a temporal disaggregation method of rainfall data was developed based on the Neyman–Scott Rectangular Pulse Model, a stochastic rainfall model, and future design rainfall was projected. The developed method showed better performance than the benchmark models. It produced promising results in estimating the rainfall quantiles for recurrence intervals of less than 20 years. Overall, the analysis results imply that extreme rainfall events may increase. Structural/nonstructural measures are urgently needed for irrigation and the embankment of new water resources.

Revealing influences on carsharing users’ trip distance in small urban areas

Carsharing is an essential part of the transformation towards sustainable mobility in smaller urban areas. To expand their services and the positive social and environmental benefits, carsharing operators must understand their users' travel behavior. To accelerate this understanding, we analyze usage data of a station-based carsharing service from a small city in Germany with machine learning and explainable artificial intelligence to reveal influencing factors on the trip distance. The resulting four overarching groups are personal characteristics, time-related, car-related, and environmental features. We further analyze the driving distance of several subgroups split by personal and time-related features. Our findings highlight the importance of time-related features for the trip distance of carsharing users in all subgroups. We also discuss the influence of non-time-related features on the user groups. With these results, we derive valuable insights for research and carsharing operators by understanding patterns in individual user behavior in smaller urban areas.

Association of Bone Mineral Density Testing With Risk of Major Osteoporotic Fractures Among Older Men Receiving Androgen Deprivation Therapy to Treat Localized or Regional Prostate Cancer

Bone health screening is recommended for patients with prostate cancer who are initiating treatment with androgen deprivation therapy (ADT); however, bone mineral density screening rates in the US and their association with fracture prevention are unknown. To assess dual-energy x-ray absorptiometry (DXA) screening rates and their association with fracture rates among older men with prostate cancer initiating treatment with androgen deprivation therapy. This retrospective nationwide population-based cohort study used data from the Surveillance, Epidemiology, and End Results database and the Texas Cancer Registry linked with Medicare claims. Participants comprised 54 953 men 66 years or older with prostate cancer diagnosed between January 2005 and December 2015 who initiated treatment with ADT. Data were censored at last enrollment in Medicare and analyzed from January 1 to September 30, 2021. Dual-energy x-ray absorptiometry screening within 12 months before and 6 months after the first ADT claim. Frequencies of DXA screening and fracture (any fracture and major osteoporotic fracture) and overall survival were calculated. The association between DXA screening and fracture was evaluated using a multivariable Cox proportional hazards model with propensity score adjustment. Among 54 953 men (median age, 74 years; range, 66-99 years) with prostate cancer, 4689 (8.5%) were Hispanic, 6075 (11.1%) were non-Hispanic Black, 41 453 (75.4%) were non-Hispanic White, and 2736 (5.0%) were of other races and/or ethnicities (including 121 [0.2%] who were American Indian or Alaska Native; 1347 [2.5%] who were Asian, Hawaiian, or Pacific Islander; and 1268 [2.3%] who were of unknown race/ethnicity). Only 4362 men (7.9%) received DXA screening. The DXA screening rate increased from 6.8% in 2005 to 8.4% in 2015. Lower screening rates were associated with being single (odds ratio [OR], 0.89; 95% CI, 0.81-0.97; P = .01) and non-Hispanic Black (OR, 0.80; 95% CI, 0.70-0.91; P < .001), living in small urban areas (OR, 0.77; 95% CI, 0.66-0.90; P = .001) and areas with lower educational levels (OR, 0.75; 95% CI, 0.67-0.83; P < .001), and receiving nonsteroidal androgens (OR, 0.57; 95% CI, 0.39-0.84; P = .004). Overall, 9365 patients (17.5%) developed fractures after initial receipt of ADT. The median time to first fracture was 31 months (IQR, 15-56 months). In the multivariable model with propensity score adjustment, DXA screening was not associated with fracture risk at any site (hazard ratio [HR], 0.96; 95% CI, 0.89-1.04; P = .32) among men without previous fractures before receipt of ADT. However, previous DXA screening was associated with a decreased risk of major fractures (HR, 0.91; 95% CI, 0.83-1.00; P = .05) after propensity score adjustment. In this study, low DXA screening rates were observed among older men with localized or regional prostate cancer after initiation of treatment with ADT. Despite low rates of screening, evaluation of bone mineral density with a DXA scan was associated with lower risk of major fractures. These findings suggest that DXA screening is important for the prevention of major fractures among older men with prostate cancer and that implementation strategies are needed to adopt bone health screening guidelines in clinical practice.

Contextual Adjustment of the Institute of Transportation Engineers Trip Generation Rates for Small and Medium Urban Areas in Louisiana

The Institute of Transportation Engineers (ITE) Trip Generation Handbook has been in common use since the 1970s to estimate vehicle trips generated by more than 172 land use categories as a function of establishment size. However, observed trip rates display a huge error range across different land use categories and urban contexts. Although contextual adjustment factors can ameliorate the error in the ITE trip generation estimates considerably, local site-specific trip generation rates should be collected for this purpose. Given the huge time and monetary costs of data collection, adjusting the ITE trip generation rate is mainly done in large metropolitan areas such as Portland, OR, Baltimore, MD, and San Francisco, CA, while it is ignored by many jurisdictions in small to medium-sized metropolitan areas. Here, the ITE trip generation rates for strip mall land use in Louisiana are adjusted by considering the extent to which the built environment characteristics can improve the accuracy of estimated vehicle trip generation rates in smaller urban areas. Vehicle trip data were collected for two consecutive days at 40 strip malls across eight different urban areas of Louisiana to develop whole day and afternoon peak hour contextual adjustment factors for the given land use category across the study area. The results of this study show noticeable improvement for whole day analysis compared with the ITE method by producing a 42% reduction in root mean square error .

Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area.

Transmission chains within small urban areas (accommodating ∼30 per cent of the European population) greatly contribute to case burden and economic impact during the ongoing coronavirus pandemic and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in a European urban area, Basel-City (Switzerland). We combined detailed epidemiological, intra-city mobility and socio-economic data sets with whole-genome sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44 per cent of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60 per cent of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare system burden (intensive care unit (ICU) occupancy). Transmissions were driven by socio-economically weaker and highly mobile population groups with mostly cryptic transmissions which lacked genetic and identifiable epidemiological links. Amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60–90 per cent transmission reduction and 70–90 per cent reduction of severe cases showed that prioritising mobile, socio-economically weaker populations for vaccination would effectively reduce case numbers. However, long-term ICU occupation would also be effectively reduced if senior population groups were prioritised, provided there were no changes in testing and prevention strategies. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area.

Transit Ridership Growth in Small Urbanized Areas: Lessons from Seven US Transit Systems

Abstract This study examines seven small urbanized areas (UZAs) in the United States where public transit ridership increased between 2005 and 2017 in order to identify lessons for other similarly ...

Experiences of discrimination and its impacts on well-being among racialised LGBTQ+ newcomers living in Waterloo region, Ontario, Canada.

Discrimination (i.e. racism, homo/bi/transphobia) at both the individual and systemic levels may negatively impact the well-being of racialised LGBTQ+ newcomers living in Waterloo Region, Ontario, Canada. Current research about the experiences of LGBTQ+ newcomers focuses predominantly on homogeneous samples of gay men living in large metropolitan city centres. The present study aims to extend the current literature by exploring the experiences of discrimination and its impacts on well-being among racialised LGBTQ+ newcomers living in a small urban area and representing a variety of intersecting identities (i.e. ethno-racial background, LGBTQ+ identity, newcomer status). Using a qualitative method, 10 individuals were invited to complete a semistructured interview between fall 2019 and summer 2020 about their experiences of discrimination in Waterloo Region, and how such experiences impact their well-being. Using an intersectional lens, a thematic analysis revealed that racialised LGBTQ+ newcomers experienced discrimination before and after settlement in Waterloo Region. Prior to settlement, participants spoke predominantly about experiences of homo/biphobia and the associated feelings of internalised oppression. Alternatively, upon settling in Waterloo Region, experiences of discrimination were predominantly racism, and, in particular, systemic racism, which manifested as an inability to access adequate services and a lack of representation in various spaces throughout Waterloo Region. These results extend previous research by identifying the service barriers experienced by racialised LGBTQ+ newcomers living in a small urban area and can be used to inform best practices for addressing these barriers in Waterloo Region and other small urban areas with similar demographics. Implications and limitations are discussed.