Distribution and Accessibility of Churches in New York City

In New York City, known for its diverse people and neighborhoods, churches are more than just places for prayer; they're important parts of the community, providing an indispensable aid to the city's economic and spiritual development. This study analyzes the relationship between the location of churches in cities and population density and income status, and of course the effect of the extent of transportation routes on site selection. By examining the patterns of population distribution and income in the vicinity of churches, we were able to visualize and visualize this information in the form of maps, and to delve deeper into potential trends in these areas. It is hoped that based on our findings we can help shape the social and economic patterns that characterize New York City.

1) There is a positive correlation between the number of churches in NYC and its population density. This suggests that areas with higher population density in New York City are likely to have a greater number of churches.

2) There is a low or negligible relationship between the income status of an area and the number of churches present. This implies that the distribution of churches across New York City is not significantly influenced by the economic status of the residents in different neighborhoods.

3) Churches in New York City generally have good accessibility via public transportation.

Intersect Tool : To filter out the location data within New York City.

Join and Relates (Join): To joint population and income status data into census tracts

Field Calculator: To calculate the density

Symbology (Quantities): Showed difference in spatial data

Buffer Tool: To create buffer polygons around stations

Select by Location: Find the intersect

This map serves as an initial overview for readers to understand the distribution of churches in New York City. From the visualization, we can observe that churches are more densely distributed across the Bronx, Manhattan, Brooklyn, and the northern regions of Queens, while the distribution of churches in Staten Island appears relatively sparse.

From Map 2, it's evident that Bronx, Manhattan, and Brooklyn exhibit higher population densities, while in Queens, only specific census tracts show higher population density, and Staten Island, overall, has lower population density. Concerning church density, noticeable higher values are observed in certain census tracts in Bronx, Manhattan, Brooklyn, and some parts of Queens, unlike population density, where numerous tracts exhibit high density. According to calculations, the Pearson correlation coefficient between church density and population density in NYC is 0.2647. This indicates a certain degree of positive correlation between church density and population density, although the correlation is not particularly strong. The relatively low Pearson correlation coefficient suggests that the relationship between church density and population density isn't straightforwardly linear. The distribution of churches might be influenced by various factors such as community development history, religious culture, land planning disparities, and local service needs. This implies that the presence and growth of churches aren't solely determined by population numbers; they more deeply reflect social, cultural, and religious characteristics and demands within a community.

Map 3 highlights the prevalence of higher-income households in Manhattan, Queens, and Staten Island. In Brooklyn, higher-income households are mainly concentrated in the northwestern region, while in the Bronx, they tend to be situated along the eastern and western peripheries. However, the computed Pearson correlation coefficient between church density and median household income stands at a mere 0.0346, indicating an almost negligible linear relationship between the two. This suggests that the distribution of churches isn't solely dictated by the local income levels. It possibly reflects the intricate influence of diverse factors such as religious practices, community planning, and cultural needs on church distribution. Even in affluent areas, a higher church density isn't a certainty, potentially owing to differences in regional characteristics or societal and cultural demands. This faint correlation hints at a more complex and diversified relationship between church density and income levels, warranting further consideration of societal and cultural factors.

According to Map 4, there's a relatively dense distribution of bus stations, while Staten Island has fewer of them. Statistically, within the 500-meter buffer zone around the bus stops, there are 1,872 churches was involved. Therefore, these buffer zone account for 93.32% of the total. This indicates relatively high transportation convenience around the churches in New York City. It might imply a certain significance of religious locations within the city's transportation network.

Map 4b shows that subway stations in New York City are most concentrated in Manhattan. Out of 2,006 total churches, 1,138 are within a 500-meter radius of churches, making up 56.72% of the total. This indicates that churches are highly accessible by subway especially in real estate areas, emphasizing the ease of traveling to these locations via the city's subway network.

The analysis of various maps and data points provides a comprehensive understanding of the distribution and accessibility of churches in New York City in relation to population density, income levels, and public transportation access.

Map 1 shows a denser distribution of churches in the Bronx, Manhattan, Brooklyn, and northern Queens, with fewer in Staten Island. Map 2's correlation between church and population density (Pearson value 0.2647) suggests a moderate but not strong relationship. Map 3, examining the link between church density and median household income, shows an almost negligible correlation (0.0346), suggesting that church distribution is not significantly impacted by local income levels and that churches are accessible to various economic groups. Maps 4a and 4b strongly support the hypothesis of good public transport accessibility to churches, with a high percentage of bus and subway stations located within a 500-meter radius of churches. This highlights the integration of churches into the city's transit network and their accessibility to a wide urban population.

Overall, the analysis of church distribution and accessibility in New York City reveals that while population density has a moderate influence, income levels appear to have no significant impact. The distribution of churches in New York City is influenced by a complex mix of social, cultural, and infrastructural factors, reflecting the city's diverse and dynamic character.

• The study relies on available data of Church, which might not capture every church in NYC
• The study uses median household income as a measure, which might not fully represent the economic diversity and disparity within neighborhoods.
• There could be external factors affecting church distribution and accessibility, like zoning laws, real estate prices and social trends, which are not fully addressed in the study.
• Have tried to add a high-way shapefile to better explore the accessibility of the church, but did not find any relevant data

The fact is that we are still missing a lot of important factors in this project. In future research we will need to analyze data on church density in different areas and create maps of cities with similar levels of church density. Of course, in the future, more churches will choose to utilize GIS to select sites, so the distribution of churches will gradually change due to more factors. In addition, with the development of society, transportation, and economic changes, the degree to which churches are affected by population density, income level, and access to transportation will also change. Therefore, our research is a long-lasting and ever-changing topic that requires the addition of new data to keep the maps accurate. This is a very interesting topic and hopefully we can learn more about changes in other areas in the future using data reflected in the distributional factors of churches in the map. This is not only a study of the distribution patterns of churches in New York City, but also a research that looks at the impact of trends in society as a whole on churches.

In the process of investigating the influence of income level, population density and some geographic factors on the distribution of churches, we also found some relevant GIS studies from other perspectives, and some of these perspectives or data also provided direction for our overall project.

In research paper “Locational Analysis for Church Planting in Pierce and King County” primarily explored the Pierce and King areas of Washington State regarding how churches are distributed. Although this article focuses on site selection considerations through the lens of churches, it actually provides another perspective for us to think about regarding the analysis of church distribution, and the author's use of GIS to produce maps of the distribution of churches in the two main areas provides us with samples for analogies to New York City. Firstly, the main aim of the research team in this case was to find a suitable location for the siting of a church that has an active community service at its core, so the probing questions were mainly about what areas could be better served for a wider range of people. Thus, the first map shows primarily the distribution of churches within the city boundaries of Pierce and King Counties. The database shows that the density of churches in the cities is clearly greater than in the rural areas, but it would clearly be unwise to plant a new church in an area of extremely high church density, so the first criterion for site selection was moderate to low church density. After that, the article analyzes the data on the distribution area of church members and the population density and income level around the target area mainly through GIS view. Of course, the rent and location of the land are also important parameters to analyze. After determining the parameters, the researchers rasters the membership and church densities with the census demographic data to determine the areas that fit the parameters. Finally the entire team used this land data to target alternative areas for new churches.

GIS data was also used in the article "Using Science to Find the Faithful" for the Church site. To begin with, the pastor noticed that the church membership was declining and the once thriving church was empty during services, so they realized that the traditional methods were not able to build up their audience, so they chose to analyze the data through GIS in order to find a better location for the church. They then compiled the data and used the location intelligence from GIS to analyze information such as community demographics, driving times to places of worship, and the lifestyles and personal interests of nearby residents to find more possibilities for a new church. Not only that, Rev. Ken Howard, Founder and Executive Director of FaithX, believes science based tools can help religious leaders understand demographic changes. For example, GIS might show that the Hispanic population has spiked within a 15-minute drive of a particular church. That knowledge might prompt a congregation to post signs in both English and Spanish, offer literature and Bibles in Spanish, and conduct services in both languages. All of this information has helped Maryland pastors grasp more opportunities to build churches in more new areas.

Although these two cases seem to be different from what we studied, they actually used GIS to help us validate some of our conjectures and research from another angle. The first case looks at the distribution of churches from the developer's point of view, and they also use the GIS view to consider factors such as population density, church density, and the income level of the residents to select a site for a new church. This shows that the overall direction we explored in the map was correct, and GIS did help them find the target area that best met their requirements. The second case describes the process of considering the distribution of churches directly from the church's point of view, and GIS even went further in this case to analyze driving times, routes to churches, and the interests of the surrounding residents. All of this data is on the map to provide new ideas for church development. All in all, all of these Case Studies reverse the patterns of church distribution that we have studied through GIS through the developer's point of view.