5 datasets found
  1. K

    Montgomery County, Pennsylvania Parcels

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Jul 8, 2022
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    Montgomery County, Pennsylvania (2022). Montgomery County, Pennsylvania Parcels [Dataset]. https://koordinates.com/layer/109583-montgomery-county-pennsylvania-parcels/
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    pdf, shapefile, kml, geopackage / sqlite, mapinfo mif, csv, dwg, geodatabase, mapinfo tabAvailable download formats
    Dataset updated
    Jul 8, 2022
    Dataset authored and provided by
    Montgomery County, Pennsylvania
    Area covered
    Description

    Vector polygon map data of property parcels from Montgomery County, Pennsylvania containing 307,283 features.

    Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

    Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

    Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

  2. d

    Crystal Rock and Trib. 104 Histogram Data, 2016, Montgomery County, MD

    • search.dataone.org
    • catalog.data.gov
    Updated Sep 7, 2017
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    Stephanie Sparkman (2017). Crystal Rock and Trib. 104 Histogram Data, 2016, Montgomery County, MD [Dataset]. https://search.dataone.org/view/1bfab21e-c584-46f1-a44c-b2a5e0767f3c
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    Dataset updated
    Sep 7, 2017
    Dataset provided by
    USGS Science Data Catalog
    Authors
    Stephanie Sparkman
    Variables measured
    LID_TN_kgkmyr, LID_TP_kgkmyr, LID_Sed_kgkmyr, TRAD_TN_kgkmyr, TRAD_TP_kgkmyr, TRAD_Sed_kgkmyr
    Description

    This data release includes the data used to generate histograms that compared total watershed pollutant removal efficiency (TWPRE) in the two study watersheds Crystal Rock (traditional watershed) and Tributary (Trib.) 104 low impact development (LID watershed) to determine if LID BMP design offered an improved water quality benefit. Input/calibrants data used in the model (Monte Carlo) are described in the manuscript as mentioned in the list below: -BMP Name and Type: references in the manuscript -BMP Connectivity: Proprietary (derived from Montgomery County GIS Data) -BMP Drainage Areas: Proprietary (derived from Montgomery County GIS Data) -BMP Efficiency Ranges: referenced in manuscript -Baseline Pollutant Loadings: referenced in manuscript Stormwater runoff and associated pollutants from urban areas in the Chesapeake Bay Watershed represent a serious impairment to local streams and downstream ecosystems, despite urbanized land comprising only 7% of the Bay watershed area. Excess nitrogen, phosphorus, and sediment affect local streams in the Bay watershed by causing problems ranging from eutrophication and toxic algal blooms to reduced oxygen levels and loss of biodiversity. Traditional management of urban stormwater has primarily focused on directing runoff away from developed areas as quickly as possible. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner on the landscape to treat stormwater runoff closer to its source.The objective of this research was to use a modeling approach to compare total watershed pollutant removal efficiency (TWPRE) of two watersheds with differing spatial patterns of SW BMP design (traditional and LID), and determine if LID SW BMP design offered an improved water quality benefit.

  3. d

    Crystal Rock and Trib. 104 Sewershed Data, 2016, Montgomery County, MD

    • search.dataone.org
    • data.usgs.gov
    • +1more
    Updated Sep 7, 2017
    + more versions
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    Stephanie Sparkman (2017). Crystal Rock and Trib. 104 Sewershed Data, 2016, Montgomery County, MD [Dataset]. https://search.dataone.org/view/af1bdfaa-faf7-433a-9b92-acfc90556c8d
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    Dataset updated
    Sep 7, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Stephanie Sparkman
    Variables measured
    Types, No_BMPs, BMP_Name, Area_sqkm, TN_Removal_kgsqkm, TP_Removal_kgsqkm, Sediment_Removal_kgsqkm
    Description

    This data release includes the data used to generate sewershed "bubble plots" that compared pollutant removal efficiency (PRE) in each sewershed in the two study watersheds Crystal Rock (traditional watershed) and Tributary (Trib.) 104 low impact development (LID watershed) to determine if LID BMP design offered an improved water quality benefit as compared on a sewershed basis. Input/calibrants data used in the model (Monte Carlo) are described in the manuscript as mentioned in the list below: -BMP Name and Type: references in the manuscript -BMP Connectivity: Proprietary (derived from Montgomery County GIS Data) -BMP Drainage Areas: Proprietary (derived from Montgomery County GIS Data) -BMP Efficiency Ranges: referenced in manuscript -Baseline Pollutant Loadings: referenced in manuscript Stormwater runoff and associated pollutants from urban areas in the Chesapeake Bay Watershed represent a serious impairment to local streams and downstream ecosystems, despite urbanized land comprising only 7% of the Bay watershed area. Excess nitrogen, phosphorus, and sediment affect local streams in the Bay watershed by causing problems ranging from eutrophication and toxic algal blooms to reduced oxygen levels and loss of biodiversity. Traditional management of urban stormwater has primarily focused on directing runoff away from developed areas as quickly as possible. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner on the landscape to treat stormwater runoff closer to its source.The objective of this research was to use a modeling approach to compare total watershed pollutant removal efficiency (TWPRE) of two watersheds with differing spatial patterns of SW BMP design (traditional and LID), and determine if LID SW BMP design offered an improved water quality benefit.

  4. a

    Ride On Routes

    • opendata-mcgov-gis.hub.arcgis.com
    • hub.arcgis.com
    Updated Dec 14, 2024
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    Montgomery County, MD (2024). Ride On Routes [Dataset]. https://opendata-mcgov-gis.hub.arcgis.com/datasets/mcgov-gis::ride-on-routes
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    Dataset updated
    Dec 14, 2024
    Dataset authored and provided by
    Montgomery County, MD
    Area covered
    Description

    Ride On routes as exported from DOT's Trapeze software. Normally, updates are made three times a year, in January, May, and September. However, for the year following the kickoff of DOT's Ride On Reimagined project, there will only be two updates in 2025: in June and December.Available for download at TEBS-GIS' Open Data site here. County GIS users can find this data in TEBS-GIS database in SDE.TRANSPORTATION.

  5. a

    Address Points for NJ, Hosted, 3424

    • njogis-newjersey.opendata.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Jun 7, 2021
    + more versions
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    New Jersey Office of GIS (2021). Address Points for NJ, Hosted, 3424 [Dataset]. https://njogis-newjersey.opendata.arcgis.com/maps/5051f228c9074aa7b4116f835893c9fa
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    Dataset updated
    Jun 7, 2021
    Dataset authored and provided by
    New Jersey Office of GIS
    Area covered
    Description

    Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool. The address service contains statewide address points and related landmark name alias table and street name alias table.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

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Montgomery County, Pennsylvania (2022). Montgomery County, Pennsylvania Parcels [Dataset]. https://koordinates.com/layer/109583-montgomery-county-pennsylvania-parcels/

Montgomery County, Pennsylvania Parcels

Explore at:
pdf, shapefile, kml, geopackage / sqlite, mapinfo mif, csv, dwg, geodatabase, mapinfo tabAvailable download formats
Dataset updated
Jul 8, 2022
Dataset authored and provided by
Montgomery County, Pennsylvania
Area covered
Description

Vector polygon map data of property parcels from Montgomery County, Pennsylvania containing 307,283 features.

Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

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