A bare-earth, hydro-flattened, digital-elevation surface model derived from 2010 Light Detection and Ranging (LiDAR) data. Surface models are raster representations derived by interpolating the LiDAR point data to produce a seamless gridded elevation data set. A Digital Elevation Model (DEM) is a surface model generated from the LiDAR returns that correspond to the ground with all buildings, trees and other above ground features removed. The cell values represent the elevation of the ground relative to sea level. The DEM was generated by interpolating the LiDAR ground points to create a 1 foot resolution seamless surface. Cell values correspond to the ground elevation value (feet) above sea level. A proprietary approach to surface model generation was developed that reduced spurious elevation values in areas where there were no LiDAR returns, primarily beneath buildings and over water. This was combined with a detailed manual QA/QC process, with emphasis on accurate representation of docks and bare-earth within 2000ft of the water bodies surrounding each of the five boroughs.

NYC 1foot Digital Elevation Model:
A bare-earth, hydro-flattened, digital-elevation surface model derived from 2010 Light Detection and Ranging (LiDAR) data. Surface models are raster representations derived by interpolating the LiDAR point data to produce a seamless gridded elevation data set. A Digital Elevation Model (DEM) is a surface model generated from the LiDAR returns that correspond to the ground with all buildings, trees and other above ground features removed. The cell values represent the elevation of the ground relative to sea level. The DEM was generated by interpolating the LiDAR ground points to create a 1 foot resolution seamless surface. Cell values correspond to the ground elevation value (feet) above sea level. A proprietary approach to surface model generation was developed that reduced spurious elevation values in areas where there were no LiDAR returns, primarily beneath buildings and over water. This was combined with a detailed manual QA/QC process, with emphasis on accurate representation of docks and bare-earth within 2000ft of the water bodies surrounding each of the five boroughs.

Please see the following link for additional documentation- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_DigitalElevationModel.md

A Civil Service List consists of all candidates who passed an exam, ranked in score order. An established list is considered active for no less than one year and no more than four years from the date of establishment. For more information visit DCAS’ “Work for the City” webpage at: https://www1.nyc.gov/site/dcas/employment/take-an-exam.page

A List Certification includes the names of eligible candidates on an Active Civil Service List that has been established. The Certification may contain part of a list, the whole list, or multiple lists at the request of an appointing agency, to fill vacancies and/or replace provisionals. Eligible candidates on a Certification may be considered for probable appointment at the appointing Agency. For more information visit DCAS’ “Work for the City” webpage at: https://www1.nyc.gov/site/dcas/employment/take-an-exam.page

The City Record Online (CROL) is a fully searchable database of notices published in the City Record newspaper, including, but not limited to: public hearings and meetings, public auctions and sales, solicitations and awards and official rules proposed and adopted by city agencies.

The Civil List reports the agency code (DPT), first initial and last name (NAME), agency name (ADDRESS), title code (TTL #), pay class (PC), and salary (SAL-RATE) of individuals who were employed by the City of New York at any given time during the indicated year.

The Green Book Online is a fully searchable database which gives New Yorkers the opportunity to search for the agencies, offices, boards and commissions that keep our City running. It includes listings for all levels of New York City government, County, and the unified Courts system.

The Office of Citywide Purchasing (OCP) solicits and awards contracts for a wide variety of goods and services on behalf of all City agencies.

These data were prepared in compliance with the requirements of Local Law 24 of 2016 (LL24). Under LL24, the Department of Citywide Administrative Services (DCAS) is required to assess the solar photovoltaic (PV) potential of all City-owned buildings over 10,000 gross square feet once every two years. Special focus is given to identifying and quantifying potential capacity at solar-ready buildings, which are defined as buildings that have roofs that are no more than 10 years old and are in fair or good condition. The 2022 Solar-Readiness Assessment is the fourth biennial assessment pursuant to LL24. The full report is available at https://www1.nyc.gov/assets/dcas/downloads/pdf/energy/reportsandpublication/local24_2022.pdf

This dataset contains current job postings available on the City of New York’s official jobs site (http://www.nyc.gov/html/careers/html/search/search.shtml). Internal postings available to city employees and external postings available to the general public are included.