Alice Hudson Award - Gallery of Best Interactive Map Awardees



311 flood calls in NYC and corresponding flooding prevention infrastructure
by Gowri Anand

As one of the most populated cities in the world with some of the countryʼs most antiquated infrastructure, New York City has been and will increasingly be vulnerable to countless number of flood related incidents with climate change effects rapidly taking effect. This is particularly true for certain parts of NYC that are closer to the coast or reside in areas that have poor stormwater infrastructure. The purpose of this project is to display and contrast the flood related service calls made by residents to 311 (per year and overall) and the flooding prevention infrastructure that the city has implemented, such as wetland street trees. The scope of this project focuses on NYC 311 calls from 2010 to 2020, and the NYC 2015 street tree census thus far. It is important to see if and which areas are at particular risk or are already struggling so that priority can go towards these places and mitigate the effects of flooding as much as possible. Essentially, the goal is to identify which neighborhoods have the most flooding within the past 11 years and if and how these neighborhoods have stayed consistent over time.

Intended Audience: NYC residents

Software Used: PostgreSQL, Microsoft Visual Studio Code

Data Sources: For this project I will be using 311 calls data from 2010 to the end of Dec 2020 on NYC Open Data as well as NTA shapefiles which is also located from NYC Open Data. For the 311 calls, I have filtered for the following descriptor types: Street Flooding (SJ), Sewer Backup (Use Comments) (SA), Highway Flooding (SH), Manhole Cover Missing (Emergency) (SA3), Manhole Overflow (Use Comments) (SA1), Possible Water Main Break (Use Comments) (WA1), Catch Basin Clogged/Flooding (Use Comments) (SC), and Excessive Water in Basement (WEFB). For the street trees, I will be using the NYC 2015 Street Tree Census and have filtered for alive trees that are considered wetland tree species.



The Brooklyn Health Map
by Sheena Philogene

This map was initially developed to answer the question, 'what areas of Brooklyn have a high prevalence of cancer cases?' and to inform the development of culturally competent and targeted healthcare outreach initiatives. As the map developed its purpose developed, since cancer is so closely linked to various health behaviors (e.g., smoking, drinking, obesity, etc.) and comorbidities (e.g., diabetes, heart disease, and kidney disease). As such, the purpose of this map is to provide local level information about a wide array of health conditions, including cancer and some of the commonly associated comorbidities and behaviors that may lead to cancer.

Intended Audience: This map is intended for a broad Brooklyn-based audience, which may include researchers, medical professionals, community organizations interested in developing community targeted health interventions, and individuals who are interested in community health but who don’t necessarily work in healthcare.

Software Used: This map was created using Visual Studio Code, and was built using JavaScript, CSS, and HTML. ArcGIS Pro was used to geocode data and export GeoJSON files. Microsoft Excel was used to calculate zip code level estimates of language data, using HUD-USPS 'ZIP-TRACT' ZIP Code Crosswalk ratios

Data Sources:



New York City Public School Explorer
by Horia Popa

The web map application provides information regarding public schools in New York City.

Intended Audience: Parents and students interested in the public schools in New York City.

Software Used: Visual Studio Code, Adobe Photoshop, Adobe Illustrator

Data Sources: NYC Open Data


New York City High School Explorer
by Horia Popa

The web mapping application aims to help parents and students in New York City chose a high school. It provides comprehensive information as well as links to their websites and the respective DOE snap-shot pages.

Intended Audience: New York City middle school students and their parents.

Software Used: Visual Studio Code, Adobe Photoshop, Adobe Illustrator

Data Sources: NYC Open Data



Visualizing School Closures in Puerto Rico (2019)
by Paul Bendernagel

The objective of this stdy was to utilize tools contained within the free and open source GIS stack to analyze school closure and performance data for Puerto Rico. Puerto Rico has been embarking on an ambitious school closure program to consolidate teaching resources and has increased the number of schools closed dramatically in the 2018-2019 school year. Using a variety of spatial and non-spatial data sources, this study attempted to examine the trends in school closure patterns, identify potential inequities in the distribution of school closures, and develop a WebGIS to disseminate the information and data developed in this study. Policy makers, researchers, and citizens are hindered by the lack of publicly available data pertaining to these far-reaching programs being implemented in Puerto Rico. Creating open data portals and Web GISs enables individuals to not only find out how these programs may be affecting them, but to critically understand, evaluate, and potentially fight back against legislation that could adversely be affecting them or their families and communities.

This webGIS provides an inherently simplified perspective on a complex socio-political issue. The utilization of the Social Vulnerability Index serves as a proxy for the wide range of socioeconomic, demographic, and environmental variables that can interact to marginalize populations on the Island. The five-mile buffer layers created for the open elementary schools, middle schools, and high schools function as a preliminary screening to find locations in which students may be subjected to disproportionately lengthy and disruptive school transfers. The complexity of the analysis and breadth of data included in this map could be scaled up and built upon in future iterations of development. The primary goal in building this application was to demonstrate a viability of a completely open-source methodology that utilizes only open-source data to empower citizens to collect, analyze and visualize complex and contentious spatial problems facing their communities.

Intended Audience: citizens, policy makers, educators, activists, and media

Software Used: QGIS, PostGIS, Leaflet.JS, MS Visual Code Studio

Data Sources:

  • School Closure Data, point locations, and facility data: Center For Puerto Rican Studies Hunter College Data Center:,15.9789,-62.5263,20.3927
  • Social Vulnerability Index: Center For Disease Control
  • Buffer boundaries were manually created in QGIS and exported as GeoJSON files