This ArcGIS StoryMap is a series of maps and charts created to visualize the spatial relationship among litter basket inventory, 311 litter basket-related complaints, income, and population across various geographic areas of New York City. Please explore it through ArcGIS here!
Introduction
New York City’s relationship with sanitation infrastructure and services is complex and fraught. I first began to examine this relationship when living in East New York, Brooklyn. I noticed many blocks had black trash bags attached to trees that neighbors or building superintendents regularly emptied and replaced. When I asked my roommate about it, she said that she called 311 to request a basket at the end of our block, but the New York Department of Sanitation (DSNY) rejected her claim because the area was residential.
When I noticed the same trash bag placements where I live now in East Flatbush, I began to wonder why I didn’t directly observe the same thing in other residential neighbhorhoods like Kensington or Bed Stuy. I also wondered if the amount of trash on the streets I saw in East New York and Flatbush was related to the availability of litter baskets, which are often overflowing or non-existent in my neighborhood.
Many communities through New York are facing similar sanitation issues, no doubt influenced by DeBlasio’s COVID-related budget cuts that reduced DSNY’s budget by about $100 million in 2020. According to Politico , “that [meant] nearly $38 million less for residential trash collection and street cleaning and a $5.6 million cut for crews emptying litter baskets that dot street corners” (Goldenberg, Dunn). These cuts reportedly had a direct effect on the quality of litter basket throughout the city and led to “led to a massive increase in citywide 311 complaints for overflowing litter baskets — from 58 by Feb. 2020 to 790 by July,” according to Hogan and Morphet from the NY Post.
New York mayor Eric Adams has noted these issues, no doubt pressured by the increase in 311 trash-related complaints since he has taken office. He vowed to increase DSNY budget to $101 billon, with $22 million of that dedicated to litter basket services. Even more, Adams “[promised] the city’s approximately 23,000 trash bins will be emptied “50,000 times more” than ex-Mayor Bill de Blasio’s administration,” according to Shen-Berro of Politico .
Research on these issues reveals often complex and layered causes of the issues above — attributing its roots to DSNY operational constraints, waste hauling privatization, equipment limitations, neighborhood proximity to transfer waste zones, and more. But how can we understand New York City’s relationship to trash spatially?
This project explores this question through an examination of the City’s litter baskets and socioeconomic factors like income and population density. What patterns emerge when we examine the spatial relationship between population density, income, litter basket inventory, and litter basket-related complaints?
Methodology
To examine the spatial and social characteristics of 311 litter basket-related complaints, I have created a series of maps and charts that offer a visual story of where such complaints are taking place by location and complaint type with increasing levels of granularity. The visualizations are can be examined alongside population density and median household income for the geographic area specified. It is my hope that the combination of visualizations throughout the story allows a deep exploration of 311 complaints as they relate to space, each other, and the socioeconomic variables listed above.
Datasets used in this project came from the American Community Survey, the United States Census Bureau, NYC OpenData, the New York Department of Planning, and various ArcGIS users who published their findings for public use. Software used includes Tableau Public for chart visualizations and data exploration, ArcGIS for map creation and story map development, and R and Google Sheets for data exploration and cleaning.
To create the series of maps and charts below, I first began by exploring the “311 Service Requests from 2010 to Present” dataset from NYC OpenData. Because the dataset is large, I filtered for complaints starting January 1st, 2017. I thought this date would provide enough pre-pandemic data so that my analysis would not contain a large number of outliers. I then explored the many different types of complaints related to the New York Department of Sanitation (DSNY). I decided to focus only on complaints related explicitly to litter baskets because the data was more manageable and provided a more focused analysis directly related to my research questions. I also downloaded a dataset named “DSNY Litter Basket Inventory” that provided a map and figures of all DNSY litter baskets in New York City.
All the sections below begin with visualizing the number of 311 complaints by the specified geographic region. To construct these maps, I performed spatial joins of the 311 data to the geographic data, enabling me to visualize the total count of 311 complaints per community district, neighborhood tabulation area, and census tract. The same process was repeated to visualize the spatial distribution of each type of litter basket complaint per geographic area. These maps required the extra step of filtering the 311 data for specific complaint types and joining these results to the geographic area that served as my point of exploration. I chose choropleth maps to visualize the amount and frequency of the variables, whether number of complaints, number of complaints by type, population density, or median household income. I chose the specific geographic areas of community district, neighborhood tabulation area, and census tract to allow users to explore as granularly as they would like. Additionally, I thought broader areas like districts and neighborhoods might be more understandable and useful for many users. I still include complaint visualization by census tract, however, because the socioeconomic data I used was from the ACS and so collected via census tract.
The charts and graphs created with Tableau offer a visual breakdown of complaint type per community district as well as a breakdown of the most frequent complaint type across all of New York City. With these visualizations, users can easily compare complaint type by community district and by neighborhood. The neighborhood data were calculated via the “calculated” field function in Tableau using the “community board” values in the 311 datasets. As such, the neighborhoods are broken down per community board and function as neighborhood “groups.” I chose to visualize the data this way after class feedback that community board information was not understandable to users without previous knowledge.
Lastly, the visualizations are presented via an ArcGIS Storymap to create a narrative of the visualizations. The Storymap allows additional context and a way to navigate through the visualizations in an interactive way.
Please explore the rest of the StoryMap through ArcGIS here!