Data Integration
We create an extensive database of information on street trees, air quality, and respiratory illness (asthma hospitalization rate), as well as ancillary data including neighborhood demographic and land use profiles. The NYC tree census dataset (cleaned n=652,169) provides each street tree’s location (latitude and longitude), species, diameter at breast height, surrounding sidewalk condition (during survey), Neighborhood Tabulation Area (NTA), and zip code.
Tree Species
The top 20 species represent more than 80% of all street trees and include many species with moderate or severe pollen allergen. Maple (Acer), linden (Tilia), and oak (Quercus) are the most popular genera with moderate or severe pollen allergenicity.
Hover on the bar chart to see where allergenic species are located.
Spatial-temporal Pollen Patterns
Spring is the peak season with the most active pollen across the city as a whole, while there are more concentrated hot-spots of pollen activity during the summer months. Manhattan has relatively less pollen activity, in part due to the fewer number of street trees. Brooklyn and Queens experience pollen outbreaks during the spring and summer, while the Bronx has its most intense pollen activity during the fall.
Spatial Disparities of Environmental Health
Exploratory data visualization reveal the spatial disparity of asthma prevalence and related environmental factors across neighborhoods in NYC. From left to right: (1) Asthma Emergency Department (ED) visits per thousand population by zip code; (2) Annual average air quality (PM 2.5 level); (3) Percentage of vulnerable population (age <=17 or >=65).
The availability of data resources from numerous agencies and activities in cities provides new opportunities for improved urban management decision-making and more efficient and equitable services for citizens. This type of hyper-local knowledge could help individuals understand the ecology of their neighborhood and take steps to more effectively manage underlying health conditions. This process requires the collective efforts of city agencies, domain experts, data scientists, and local communities.
Authors
Constantine E. Kontokosta, PhD, PE, is an Associate Professor of Urban Science and Planning and Director of the Civic Analytics program at the NYU Marron Institute of Urban Management. He also directs the Urban Intelligence Lab and holds cross-appointments at the Center for Urban Science and Progress (CUSP) and the Dept. of Civil and Urban Engineering.
Data visualization and web developement by Yuan Lai.
