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

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

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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.

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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.

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.

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.

Parcels and Land Ownership dataset current as of 2010. GIS version of municipal tax maps.

Water bodies are defined as being any area of water, including streams, greater than 500 square feet in size; includes ponds, rivers and lakes. For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

The MCAD Tax Parcel Point View was updated in early 2024 to streamline the data schema and improve data accuracy. Instead of including a centroid for every parcel in the county (~300,000 parcels), the updated point layer now only includes parcels with anomalies that may impact mapping or other GIS products. The following types of anomalies qualify a parcel to be included in this view:Multiple Owners: Parcels with more than three listed owners.Example: Parcel at 2827 Waterbend Cove, Spring, TX, with 6 listed owners.Disconnected or Multi-part Parcels: Parcels that are split into multiple parts (more than one polygon).Example: Parcel 51296, which is split into 3 separate parts.Because the point layer is focused on these special cases, the record count for the Tax Parcel Point View has decreased significantly after the May 2024 update. For a complete view of all parcels, users are encouraged to refer to the MCAD Tax Parcel View dataset, which includes all parcels in Montgomery County.Data Includes:Flagged Parcels: Geographic points representing parcels with anomalies (multiple owners, disconnected parcels, multi-part parcels).Anomaly Types: Data on parcels with specific anomalies such as multiple owners or multiple parts.Data Source:The data is maintained and provided by the Montgomery Central Appraisal District (MCAD).Access:The view is available through Montgomery County’s Open Data Portal and can be accessed for public use.Update Frequency:The data is updated monthly, especially after changes to MCAD’s appraisal processes or data schema.

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.

Prior to the year 2000, DVRPC’s aerial imagery consisted of mylar aerial photo enlargements or “atlas sheets”. These atlas sheets were produced from 9x9" aerial photos. The imagery dates from the years 1959, 1965, 1970, 1975, 1980, 1985, 1990, & 1995. The 1959s and 1965s primarily cover the urbanized portion of the DVRPC region (the DVRPC region is made up of nine counties: Bucks, Chester, Delaware, Montgomery, and Philadelphia in Pennsylvania; Burlington, Camden, Gloucester, and Mercer in New Jersey). Subsequent years provide full coverage of the region, minus the occasional missing scan. In order to increase the efficiency of using the historical aerial imagery, the sheets were scanned into TIFF (Tagged Image File Format) files. Each TIFF file ranges between 35- 40MB in size. Unlike DVRPC’s more recent aerial imagery (2000 and later), the historical aerials are not “orthorectified” or “orthocorrected”. In other words, they are simply aerial images with no spatial reference or uniform scale. Through the process of georeferencing, Montgomery County GIS assigned a spatial reference which will enabled them to be used more readily in a GIS environment. That said, georeferencing is not orthorectifying or orthocorrecting. What it does allow is for the scan to be displayed relative to other spatially referenced GIS layers. A georeferenced scan does not have the properties of an actual orthoimage. Whereas an orthoimage can be used for making accurate measurements, a georeferenced image cannot, as it does not have the spatial accuracy and uniform scale of an orthoimage.