5,698 results returned
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Title: 2016 (May) Mass Transit Spatial Layers for New York City Geodatabase
Contributors:- Multi-spectral data
- 2016
Summary: The layers in this Sqlite Geodatabase were created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA) to represent major routes and stops for buses and trains throughout New York City. A python script was written to take the data files as input and plot and save them in the local state plane coordinate reference system. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: New York City Bus Routes, Dec 2019
Contributors:- Line data
- 2019
Summary: This line layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA) to represent New York City local bus routes. A python script was written to take the data files as input, process, and save them as a spatial layer in the local state plane coordinate reference system. Lines in this layer represent individual bus routes over a roadway for a specific direction; they were generalized from the GTFS format where lines depicted individual services. The direction of a bus route is indicated with a 0 (the bus runs either northbound or eastbound) or a 1 (the bus runs either southbound or westbound). Bus route ids that have a plus symbol + as a suffix represent Select Bus services.The unique ID is route_dir, which is a combination of the bus route id and its direction. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: New York City Express Bus Routes, Dec 2019
Contributors:- Line data
- 2019
Summary: This line layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA) to represent New York City express bus routes. Express busses are long-distance coaches that take passengers from areas of the outer boroughs to midtown and downtown Manhattan and back, with limited stops. A python script was written to take the data files as input, process them and save them as a spatial layer in the local state plane coordinate reference system. Lines in this layer represent individual bus routes over a roadway for a specific direction; they were generalized from the GTFS format where lines depicted individual services. The direction of a bus route is indicated with a 0 (which means that the bus runs either northbound or eastbound) or a 1 (the bus runs either southbound or westbound). The unique ID is route_dir, which is a combination of the bus route id and its direction. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: New York City Express Bus Stops, Dec 2019
Contributors:- Point data
- 2019
Summary: This point layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA). It represents the express bus stop locations (individual locations where one or more buses make stops) for the MTA NYC Transit bus routes. Express busses are long-distance coaches that take passengers from areas of the outer boroughs to midtown and downtown Manhattan and back, with limited stops. A python script was written to take the data files as input and process them to create a spatial layer in the local state plane coordinate reference system. The unique ID is stop_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: New York City Bus Stops, Dec 2019
Contributors:- Point data
- 2019
Summary: This point layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA). It represents the local bus stop locations (individual locations where one or more buses make stops) for the MTA NYC Transit bus routes. A python script was written to take the data files as input and process them to create a spatial layer in the local state plane coordinate reference system. The unique ID is stop_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: Long Island Rail Road Routes, May 2019
Contributors:- Line data
- 2019
Summary: This line layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA) to represent the MTA Long Island Rail Road (LIRR) routes. A python script was written to take the data files as input , process them and save them as a spatial layer in the local state plane coordinate reference system. Lines in this layer represent individual train routes that follow physical track locations; they were generalized from the GTFS format where lines depicted individual train services. The unique ID is route_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: Metro-North Bronx Shuttle Bus Stops, May 2019
Contributors:- Point data
- 2019
Summary: This point layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA). It represents the bus stop locations for the Hudson Rail Link, which is a weekday shuttle bus service that connects residents of the NW Bronx to the Spuyten Duyvil and Riverdale Metro North train stations. A python script was written to take the data files as input, process them and create a spatial layer in the local state plane coordinate reference system. The unique ID is stop_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: New York City Subway Stops, May 2019
Contributors:- Point data
- 2019
Summary: This point layer was created using the GTFS data feeds from the Metropolitan Transportation Authority (MTA). It represents the stop locations for the MTA NYC Transit Subway, where a stop represents the center of platforms dedicated to serving specific trains in a subway station. A python script was written to take the data files as input, process them and save them as a spatial layer in the local state plane coordinate reference system. The unique ID is stop_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: Long Island Rail Road Stops, May 2019
Contributors:- Point data
- 2019
Summary: This point layer was created using the GTFS data feeds from the Metropolitan Transportation Authority (MTA). It represents the stop locations for the MTA Long Island Rail Road (LIRR), where a stop represents a train station (specifically the center point of the track in front of the station) that serves one or more routes. A python script was written to take the data files as input, process them and save them as a spatial layer in the local state plane coordinate reference system. The unique ID is stop_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: Metro-North Routes, May 2019
Contributors:- Line data
- 2019
Summary: This line layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA) to represent the MTA Metro North railroad routes that are east of the Hudson River. A python script was written to take the data files as input, process them and save them a spatial layer in the local state plane coordinate reference system. Lines in this layer represent individual train routes; they were generalized from the GTFS format where lines depicted individual train services. For the first time in this series, the lines in this file correspond with actual train tracks, as opposed to the generalizations in previous files (straight-lines drawn between stations). The unique ID is route_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: New York City Subway Routes, May 2019
Contributors:- Line data
- 2019
Summary: This line layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA) to represent the MTA NYC Transit Subway routes. A python script was written to take the data files as input, process and save them as a spatial layer in the local state plane coordinate reference system. Lines in this layer represent individual subway routes that follow physical track locations; they were generalized from the GTFS format where lines depicted individual services. Each line represents the route that a specific train takes during normal weekday rush hour service. The unique ID is route_id, a field created by the MTA that uses the familiar letter or number designation for trains, with distinct ids for each of the three shuttle (S) trains. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: Metro-North Stops, May 2019
Contributors:- Point data
- 2019
Summary: This point layer was created using the GTFS data feeds from the Metropolitan Transportation Authority (MTA). It represents the stop locations for the MTA Metro North railroad east of the Hudson River, where a stop represents a train station (specifically the center point of the track in front of the station) that serves one or more routes. A python script was written to take the data files as input, process them and save them as a spatial layer in the local state plane coordinate reference system. The unique ID is stop_id, a field created by the MTA.The unique ID is stop_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: New York City Real Estate Sales, 2018
Contributors:- Point data
- 2019
Summary: This point layer was created from Detailed Annual Sales Reports by Borough published by New York City Department of Finance. It represents locations of all properties sold in New York City. Several Python scripts were written to read-in each borough's sales data and combine them into sales for New York City as whole. NYC Geoclient API, developed by NYC DOITT, was used in a script to geocode locations of the properties sold. Locations geocoded by the script were matched by property address or by property block and lot information, if the address was missing or incomplete. For some properties lot information has changed from the year of the property sale (e.g. lot has been split and renumbered) and doesn’t exist in the city's current property and address database. Manual matching was performed for those records by examining archival tax maps. Due to the vertical nature of the real estate market in New York, multiple points / transactions may coincide in the same location. The coordinate reference system for this layer is NY State Plane Long Island in feet. The unique identifier of the dataset is Sale_id. Bbl_id is a unique identifier for the property and may repeat in the dataset if the property was sold more than once in the same year. The user should be cautious of sales with values less than $10 or equal to $0, which are marked as non-usable in this dataset. These sales are transfers of property and are not considered representative of true market conditions. This layer was created as a part of the NYC Geocoded Real Estate Sales data series.
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Title: NYC Geocoded Real Estate Sales Geodatabase, Open Source Version, 2018
Contributors:- Multi-spectral data
- 2019
Summary: This Geodatabase is comprised of point layers created from Detailed Annual Sales Reports by Borough published by New York City Department of Finance. It represents locations of all properties sold in New York City between the years of 2003 - 2018. Several Python scripts were written to read-in each borough's sales data and combine them into sales for New York City as whole. NYC Geoclient API, developed by NYC DOITT, was used in a script to geocode locations of the properties sold. Locations geocoded by the script were matched by property address or by property block and lot information, if the address was missing or incomplete. For some properties lot information has changed from the year of the property sale (e.g. lot has been split and renumbered) and doesn’t exist in the city's current property and address database. Manual matching was performed for those records by examining archival tax maps. Due to the vertical nature of the real estate market in New York, multiple points / transactions may coincide in the same location. The coordinate reference system for this layer is NY State Plane Long Island in feet. The unique identifier of the dataset is Sale_id. Bbl_id is a unique identifier for the property and may repeat in the dataset if the property was sold more than once in the same year. The user should be cautious of sales with values less than $10 or equal to $0, which are marked as non-usable in this dataset. These sales are transfers of property and are not considered representative of true market conditions. This layer was created as a part of the NYC Geocoded Real Estate Sales data series.
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Title: New York City Real Estate Sales, 2017
Contributors:- Point data
- 2018
Summary: This point layer was created from Detailed Annual Sales Reports by Borough published by New York City Department of Finance. It represents locations of all properties sold in New York City. Several Python scripts were written to read-in each borough's sales data and combine them into sales for New York City as whole. NYC Geoclient API, developed by NYC DOITT, was used in a script to geocode locations of the properties sold. Locations geocoded by the script were matched by property address or by property block and lot information, if the address was missing or incomplete. For some properties lot information has changed from the year of the property sale (e.g. lot has been split and renumbered) and doesn’t exist in the city's current property and address database. Manual matching was performed for those records by examining archival tax maps. Due to the vertical nature of the real estate market in New York, multiple points / transactions may coincide in the same location. The coordinate reference system for this layer is NY State Plane Long Island in feet. The unique identifier of the dataset is Sale_id. Bbl_id is a unique identifier for the property and may repeat in the dataset if the property was sold more than once in the same year. The user should be cautious of sales with values less than $10 or equal to $0, which are marked as non-usable in this dataset. These sales are transfers of property and are not considered representative of true market conditions. This layer was created as a part of the NYC Geocoded Real Estate Sales data series.
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Title: New York City Real Estate Sales, 2015
Contributors:- Point data
- 2017
Summary: This point layer was created from Detailed Annual Sales Reports by Borough published by New York City Department of Finance. It represents locations of all properties sold in New York City. Several Python scripts were written to read-in each borough's sales data and combine them into sales for New York City as whole. NYC Geoclient API, developed by NYC DOITT, was used in a script to geocode locations of the properties sold. Locations geocoded by the script were matched by property address or by property block and lot information, if the address was missing or incomplete. For some properties lot information has changed from the year of the property sale (e.g. lot has been split and renumbered) and doesn’t exist in the city's current property and address database. Manual matching was performed for those records by examining archival tax maps. Due to the vertical nature of the real estate market in New York, multiple points / transactions may coincide in the same location. The coordinate reference system for this layer is NY State Plane Long Island in feet. The unique identifier of the dataset is Sale_id. Bbl_id is a unique identifier for the property and may repeat in the dataset if the property was sold more than once in the same year. The user should be cautious of sales with values less than $10 or equal to $0, which are marked as non-usable in this dataset. These sales are transfers of property and are not considered representative of true market conditions. This layer was created as a part of the NYC Geocoded Real Estate Sales data series.
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Title: New York City Real Estate Sales, 2016
Contributors:- Point data
- 2017
Summary: This point layer was created from Detailed Annual Sales Reports by Borough published by New York City Department of Finance. It represents locations of all properties sold in New York City. Several Python scripts were written to read-in each borough's sales data and combine them into sales for New York City as whole. NYC Geoclient API, developed by NYC DOITT, was used in a script to geocode locations of the properties sold. Locations geocoded by the script were matched by property address or by property block and lot information, if the address was missing or incomplete. For some properties lot information has changed from the year of the property sale (e.g. lot has been split and renumbered) and doesn’t exist in the city's current property and address database. Manual matching was performed for those records by examining archival tax maps. Due to the vertical nature of the real estate market in New York, multiple points / transactions may coincide in the same location. The coordinate reference system for this layer is NY State Plane Long Island in feet. The unique identifier of the dataset is Sale_id. Bbl_id is a unique identifier for the property and may repeat in the dataset if the property was sold more than once in the same year. The user should be cautious of sales with values less than $10 or equal to $0, which are marked as non-usable in this dataset. These sales are transfers of property and are not considered representative of true market conditions. This layer was created as a part of the NYC Geocoded Real Estate Sales data series.
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Title: PATH Train Routes, Jan 2017
Contributors:- Line data
- 2017
Summary: This line layer is an extract from NJ TRANSIT Rail, Light Rail, and Subway Currently Operated Right-of-Way lines, with connecting PATH and PATCO Rail downloaded from NJ Office of Information Technology , Office of Geographic Information Systems. It represents the The Port Authority Trans-Hudson Corporation (PATH) Train routes. PATH Train is a rail transit system that connects several cities in New Jersey to New York City. The unique id is route_shor, which represents a shortened version of the route's name. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: PATH Train Stops, Jan 2017
Contributors:- Point data
- 2017
Summary: This point layer is an extract from the NJ TRANSIT, PATH and PATCO Passenger Rail Station points downloaded from NJ Office of Information Technology, Office of Geographic Information Systems. It represents the The Port Authority Trans-Hudson Corporation (PATH) Train stations. PATH Train is a rail transit system that connects several cities in New Jersey to New York City. The unique id is station_id. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.
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Title: 2016 (May) Long Island Rail Road Routes
Contributors:- Line data
- 2016
Summary: This line layer was created from the GTFS data feeds from the Metropolitan Transportation Authority (MTA) to represent the MTA Long Island Rail Road (LIRR) routes. A python script was written to take the data files as input and plot and save them as a spatial layer in the local state plane coordinate reference system. Lines in this layer represent individual train routes that follow physical track locations; they were generalized from the GTFS format where lines depicted individual train services. The unique ID is route_id, a field created by the MTA. This dataset is intended for researchers, policy makers, students, and educators for basic geographic analysis and mapping purposes. It was created by the GIS Lab at the Newman Library at Baruch College CUNY as part of the NYC Mass Transit Spatial Layers series, so that members of the public could have access to well-documented and readily-usable GIS layers of NYC mass transit features.