This is a breakdown of every collision in NYC by location and injury. This data is collected because the NYC Council passed Local Law #11 in 2011. This data is manually run every month and reviewed by the TrafficStat Unit before being posted on the NYPD website. Each record represents a collision in NYC by city, borough, precinct and cross street. This data can be used by the public to see how dangerous/safe intersections are in NYC. The information is presented in pdf and excel format to allow the casual user to just view the information in the easy to read pdf format or use the excel files to do a more in-depth analysis.
High resolution land cover data set for New York City. This is the 3ft version of the high-resolution land cover dataset for New York City. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at 3 square feet. The primary sources used to derive this land cover layer were the 2010 LiDAR and the 2008 4-band orthoimagery. Ancillary data sources included GIS data (city boundary, building footprints, water, parking lots, roads, railroads, railroad structures, ballfields) provided by New York City (all ancillary datasets except railroads); UVM Spatial Analysis Laboratory manually created railroad polygons from manual interpretation of 2008 4-band orthoimagery. The tree canopy class was considered current as of 2010; the remaining land-cover classes were considered current as of 2008. Object-Based Image Analysis (OBIA) techniques were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. More than 35,000 corrections were made to the classification. Overall accuracy was 96%. This dataset was developed as part of the Urban Tree Canopy (UTC) Assessment for New York City. As such, it represents a 'top down' mapping perspective in which tree canopy over hanging other features is assigned to the tree canopy class. At the time of its creation this dataset represents the most detailed and accurate land cover dataset for the area. This project was funded by National Urban and Community Forestry Advisory Council (NUCFAC) and the National Science Fundation (NSF), although it is not specifically endorsed by either agency. The methods used were developed by the University of Vermont Spatial Analysis Laboratory, in collaboration with the New York City Urban Field Station, with funding from the USDA Forest Service.
The New York City (NYC) Community Air Survey (NYCCAS) is a study of street level air pollution across NYC neighborhoods. Measurements are taken at 150 locations throughout NYC each season of the year. This downloadable set contains CSV data, metadata, and reports from the survey
This dataset contains building information for all buildings that have completed a WiredNYC survey. This includes buildings that have opted-out from displaying their profiles publicly. Therefore, the building-specific data (e.g. building address) provided is anonymous and only linked to the borough the building is located in.
Facilities in New York City, by agency and site, that offer the following after-school job and internship programs: Summer Youth Employment, In-School Youth Employment (ISY), Out-of-School Youth Employment (OSY), Youth Employment, and Adult Employment Programs for children in age groups 14 to 24, 16 to 21, children in all grades, and adults.
The Voting Information Project (VIP) offers cutting edge technology tools to provide voters with access to customized election information to help them navigate the voting process and cast an informed vote. VIP works with election officials across the nation to ensure this information is official and reliable. We answer voters’ basic questions like “Where is my polling place?” “What’s on my ballot?” and “How do I navigate the voting process?”
Mapbox makes it easy to find bars on foursquare, search for hotels on Hipmunk, and organize notes in Evernote. With Mapbox, design and publish maps that tell stories, integrate with apps, and represent brands. For questions or comments, contact: firstname.lastname@example.org
LinkUp only indexes jobs that are found on corporate career websites. Today, our U.S site lists roughly 1,500,000 jobs from over 40,000 company websites. Since we don't allow jobs to be manually posted to LinkUp, and because of the sources we index (real companies), we have the cleanest and highest quality dataset of jobs on the web - no job scams, lead-gen pollution, or fraudulent postings. For questions or comments, contact: email@example.com
Facilities in New York City, by agency and site, that offer “NDA Neighborhood Development Area Youth Employment Program” after-school job and internship programs for children and young adults ages 14 to 21 in Middle School, in High School, or in all grades.
The Lehman College Bronx Information Portal is a map-based open data platform with a focus on all things Bronx. Developed by Lehman College/CUNY with Socrata, the portal brings together Bronx-related open data all in one place. Data sets include education, health, population, environment and sustainability, among others. Join us to engage students, researchers and communities in connecting the Bronx to enrich teaching, learning and community service initiatives. For questions or comments, contact: firstname.lastname@example.org