Summary: Database of confusion matrices retrieved from scientific literature. Suitable for research on the creation and explotation of the confusion matrix that remain as interestint topics, such as new tools, sampling design, indices derived from the matrix, proposals in testing statistical hypotheses and so on.Format: Microsoft Access

The USDA Forest Service (USFS) builds two versions of percent tree canopy cover (TCC) data to serve needs of multiple user communities. These datasets encompass the conterminous United States (CONUS), Coastal Alaska, Hawaii, and Puerto Rico and U.S. Virgin Islands (PRUSVI). The two versions of data within the v2021-4 TCC product suite include:- The raw model outputs referred to as the annual Science data; and- A modified version built for the National Land Cover Database referred to as NLCD data. They are available at the following locations:Science:https://data.fs.usda.gov/geodata/rastergateway/treecanopycover, https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_LandscapeAndWildlife NLCD:https://www.mrlc.gov/datahttps://apps.fs.usda.gov/fsgisx01/rest/services/RDW_LandscapeAndWildlife, The Science data - the focus of this metadata - are the initial annual model outputs that consist of two images: percent tree canopy cover (TCC) and standard error. These data are best suited for users who will carry out their own detailed statistical and uncertainty analyses on the dataset, and place lower priority on the visual appearance of the dataset for cartographic purposes. Datasets for the nominal years of 2008 through 2021 are available. The Science data were produced using a random forests regression algorithm. TCC pixel values range from 0 to 100 percent. The value 254 represents the non-processing area mask where no cloud or cloud shadow-free data are available to produce an output, and 255 represents the background value. The Science data are accessible for multiple user communities, through multiple channels and platforms. For information on the NLCD TCC data and processing steps see the NLCD metadata. Information on the Science data and processing steps are included here.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

ODS (Open Document Spreadsheet) which only contains numeric data from a set of confusion matrices (one sheet per matrix).It is the same quantitative data stored in a field of a table in the database. Only is provided as a complement to the database in order to access to the quantitative data in a more convenient format.

Summary: Database of confusion matrices retrieved from scientific literature. Suitable for research on the creation and explotation of the confusion matrix that remain as interestint topics, such as new tools, sampling design, indices derived from the matrix, proposals in testing statistical hypotheses and so on.Format: SQLite

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The draft formation-level map was produced through limited field reconnaissance and visual interpretation of the pan-sharpened imagery and heads-up digitizing in ArcGIS to delineate polygons based on vegetation physiognomy. Spatial accuracy was assessed against 2006 digital orthophoto quarter quadrangle imagery, using 20 test points for each of the park’s three units. The maximum absolute error measured was less than 2 m ground distance, and maximum root mean square error was 1.03 m, well within the limits of the National Map Accuracy Standards.

GIS quality control checks are intended to identify issues in the source data that may impact a variety of9-1-1 end use systems.The primary goal of the initial CalOES NG9-1-1 implementation is to facilitate 9-1-1 call routing. Thesecondary goal is to use the data for telephone record validation through the LVF and the GIS-derivedMSAG.With these goals in mind, the GIS QC checks, and the impact of errors found by them are categorized asfollows in this document:Provisioning Failure Errors: GIS data issues resulting in ingest failures (results in no provisioning of one or more layers)Tier 1 Critical errors: Impact on initial 9-1-1 call routing and discrepancy reportingTier 2 Critical errors: Transition to GIS derived MSAGTier 3 Warning-level errors: Impact on routing of call transfersTier 4 Other errors: Impact on PSAP mapping and CAD systemsGeoComm's GIS Data Hub is configurable to stop GIS data that exceeds certain quality control check error thresholdsfrom provisioning to the SI (Spatial Interface) and ultimately to the ECRFs, LVFs and the GIS derivedMSAG.

Data sets for IJGIS submission. Include geocomplexity and model codes, raw datasets and key intermediate results.

Predicted standared error of GIS geostistical interpolation of a surface that models the depth to bedrock. Derived from known georeferenced locations where depths to bedrock have been observed. These primarily include bedrock outcrops and well or boring locations. Interpolation method was ordinary kriging, using a lag size of 448.6 ft. A maximum of 20 neighbors and a minimum of 8 neighbors were used in interpolation. The predicted standard error is the standard deviation of the predicted surface, and is a function of distance from the nearest data point.

Esri ArcGIS Online (AGOL) Imagery Layer which includes the MDOT SHA 2050 Mean Sea Level 10% Annual Chance (10.Year Storm) - Flood Depth Grid geospatial data product.MDOT SHA 2050 Mean Sea Level 10% Annual Chance (10.Year Storm) - Flood Depth Grid consists of a depth grid image service depicting conditions of sea level change based on the 10% annual chance event (10-Year Storm) scenario for coastal areas throughout the State of Maryland in year 2050. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2050 Mean Sea Level 10% Annual Chance (10.Year Storm) - Flood Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2050.MDOT SHA 2050 Mean Sea Level 10% Annual Chance (10.Year Storm) - Flood Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/07/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/MDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Maryland Roadway Centerline data consists of linear geometric features which represent the street centerline for all public roadways in the State of Maryland. The centerline represents the geographic location on the roadway between both shoulders (physical center), which often but not always coincides with the center painted line dividing bi-directional travel lanes. Roadway Centerlines data plays an important role in transportation management and planning, while also being the basis for all other roadway related data products. Maryland Roadway Centerline data is the end product of a statewide data sharing process between the Federal Highway Administration (FHWA), Maryland Department of Transportation (MDOT), Maryland Department of Transportation State Highway Administration (MDOT SHA), county governments and local municipal governments. Using a common centerline allows for better exchange of information related to the roadway system and provides opportunities for more efficient collection of information about roadway assets. Some centerlines were created in-house using imagery, GPS data, and MDOT SHA's Highway Performance Monitoring System (HPMS) database and others were received from county governments and updated in house using imagery, GPS data and MDOT SHA's HPMS database. The Centerline data includes annual HPMS updates / improvements submitted to the Federal Highway Administration (FHWA). Maryland Roadway Centerline data is needed for emergency response and management, routing buses and other vehicles, planning for land use and transportation needs, continuity of roadway data and display at county boundaries leading to the same "look and feel" across jurisdictions, tracking assets on and along the roadway network, producing maps at various scales, and numerous other applications. There are opportunities to make these processes more efficient, and this program addresses a shared foundation to solve some of these issues. This data is also used by various business units throughout MDOT, as well as many other Federal, State and local government agencies. Maryland Roadway Centerline data is updated and published on an annual basis for the prior year. This data is for the year 2017. For additional information, contact MDOT SHA Geospatial Technologies Email: GIS@mdot.state.md.us For additional information related to the Maryland Department of Transportation (MDOT) Website: https://www.mdot.maryland.gov/ For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA): Website: https://roads.maryland.gov/Home.aspx MDOT SHA Geospatial Data Legal Disclaimer: The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

ArcGIS Online (AGOL) Feature Layer which includes the MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid geospatial data product.MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid consists of a depth grid image service depicting conditions of sea level change based on the 1% annual chance event (100-Year Storm) scenario for coastal areas throughout the State of Maryland in year 2100. This data product supports Maryland Department of Transportation State Highway Administration (MDOT SHA) leadership and planners as they endeavor to mitigate or prevent the impacts of sea level change resulting from land surface subsidence and rising sea levels.MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid data was produced as a result of efforts by the Maryland Department of Transportation State Highway Administration (MDOT SHA), Eastern Shore Regional GIS Cooperative (ESRGC), Salisbury University (SU), United States Corps of Engineers (USACE), National Oceanic & Atmospheric Administration (NOAA), and the United States Geological Survey (USGS). The US Army Corps of Engineers provide the sea level change estimate. Sea level change is localized using water elevations collected from a qualifying National Oceanic and Atmospheric Administration (NOAA) tidal reference station - NOAA observations are transformed from tidal datum to North American Vertical Datum of 1988. A final correction for glacial isostatic adjustment and land creates an sea level change value for the official project year, 2100.MDOT SHA 2100 Mean Sea Level 1% Annual Chance (100YR Storm) - Depth Grid data was task-based, and will only be updated on an As-Needed basis where necessary.Last Updated: 10/09/2019For additional information, contact the MDOT SHA Geospatial Technologies:Email: GIS@mdot.maryland.govFor information related to the data, visit the Eastern Shore Regional GIS Cooperative (ESRGC) websiteWebsite: https:www.esrgc.org/mapServices/For additional data, visit the MDOT GIS Open Data Portal:Website: https://data.imap.maryland.gov/pages/mdot/For additional information related to the Maryland Department of Transportation (MDOT):Website: https://www.mdot.maryland.gov/For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA):Website: https://www.roads.maryland.gov/Home.aspxMDOT SHA Geospatial Data Legal Disclaimer:The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Maryland Roadway Centerline data consists of linear geometric features which represent the street centerline for all public roadways in the State of Maryland. The centerline represents the geographic location on the roadway between both shoulders (physical center), which often but not always coincides with the center painted line dividing bi-directional travel lanes. Roadway Centerlines data plays an important role in transportation management and planning, while also being the basis for all other roadway related data products.Maryland Roadway Centerline data is the end product of a statewide data sharing process between the Federal Highway Administration (FHWA), Maryland Department of Transportation (MDOT), Maryland Department of Transportation State Highway Administration (MDOT SHA), county governments and local municipal governments. Using a common centerline allows for better exchange of information related to the roadway system and provides opportunities for more efficient collection of information about roadway assets. Some centerlines were created in-house using imagery, GPS data, and MDOT SHA's Highway Performance Monitoring System (HPMS) database and others were received from county governments and updated in house using imagery, GPS data and MDOT SHA's HPMS database. The Centerline data includes annual HPMS updates / improvements submitted to the Federal Highway Administration (FHWA). Maryland Roadway Centerline data is needed for emergency response and management, routing buses and other vehicles, planning for land use and transportation needs, continuity of roadway data and display at county boundaries leading to the same "look and feel" across jurisdictions, tracking assets on and along the roadway network, producing maps at various scales, and numerous other applications. There are opportunities to make these processes more efficient, and this program addresses a shared foundation to solve some of these issues. This data is also used by various business units throughout MDOT, as well as many other Federal, State and local government agencies. Maryland Roadway Centerline data is updated and published on an annual basis for the prior year. This data is for the year 2017. Last Updated: November 2018 (11/28/2018) For additional information, contact MDOT SHA Geospatial Technologies Email: GIS@mdot.state.md.us For additional information related to the Maryland Department of Transportation (MDOT) Website: https://www.mdot.maryland.gov/ For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA): Website: https://roads.maryland.gov/Home.aspx MDOT SHA Geospatial Data Legal Disclaimer: The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Maryland Roadway Centerline data consists of linear geometric features which represent the street centerline for all public roadways in the State of Maryland. The centerline represents the geographic location on the roadway between both shoulders (physical center), which often but not always coincides with the center painted line dividing bi-directional travel lanes. Roadway Centerlines data plays an important role in transportation management and planning, while also being the basis for all other roadway related data products. Maryland Roadway Centerline data is the end product of a statewide data sharing process between the Federal Highway Administration (FHWA), Maryland Department of Transportation (MDOT), Maryland Department of Transportation State Highway Administration (MDOT SHA), county governments and local municipal governments. Using a common centerline allows for better exchange of information related to the roadway system and provides opportunities for more efficient collection of information about roadway assets. Some centerlines were created in-house using imagery, GPS data, and MDOT SHA's Highway Performance Monitoring System (HPMS) database and others were received from county governments and updated in house using imagery, GPS data and MDOT SHA's HPMS database. The Centerline data includes annual HPMS updates / improvements submitted to the Federal Highway Administration (FHWA). Maryland Roadway Centerline data is needed for emergency response and management, routing buses and other vehicles, planning for land use and transportation needs, continuity of roadway data and display at county boundaries leading to the same "look and feel" across jurisdictions, tracking assets on and along the roadway network, producing maps at various scales, and numerous other applications. There are opportunities to make these processes more efficient, and this program addresses a shared foundation to solve some of these issues. This data is also used by various business units throughout MDOT, as well as many other Federal, State and local government agencies. Maryland Roadway Centerline data is updated and published on an annual basis for the prior year. This data is for the year 2017. For additional information, contact MDOT SHA Geospatial Technologies Email: GIS@mdot.state.md.us For additional information related to the Maryland Department of Transportation (MDOT) Website: https://www.mdot.maryland.gov/ For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA): Website: https://roads.maryland.gov/Home.aspx MDOT SHA Geospatial Data Legal Disclaimer: The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Roadway Interchange Exits data consists of point feature geometry which represent the geographic location of interchange exits along public roadways in the State of Maryland. Roadway Interchange Exits data is developed as part of the Highway Performance Monitoring System (HPMS) which maintains and reports transportation related information to the Federal Highway Administration (FHWA) on an annual basis. HPMS is maintained by the Maryland Department of Transportation State Highway Administration (MDOT SHA), under the Office of Planning and Preliminary Engineering (OPPE) Data Services Division (DSD). This data is used by various business units throughout MDOT, as well as many other Federal, State and local government agencies. Roadway Interchange Exits data is key to understanding the location of interchange exits along roadways throughout the State of Maryland. Roadway Interchange Exits data is updated and published on an annual basis for the prior year. This data is for the year 2017. Last Updated: September 2018 (09/2018) For additional information, contact the MDOT SHA Geospatial Technologies Email: GIS@mdot.state.md.us For additional information related to the Maryland Department of Transportation (MDOT) Website: https://www.mdot.maryland.gov/ For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA): Website: https://roads.maryland.gov/Home.aspx MDOT SHA Geospatial Data Legal Disclaimer: The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

The cone represents the probable track of the center of a tropical cyclone, and is formed by enclosing the area swept out by a set of circles along the forecast track (at 12, 24, 36 hours, etc). The size of each circle is set so that two-thirds of historical official forecast errors over a 5-year sample fall within the circle.

A set of MATLAB functions (HSI_PSFS, SC_RS_Analysis_NAD.m, SC_RS_Analysis_sim.m) were developed to assess the spatial coverage of pushbroom hyperspectral imaging (HSI) data. HSI_PSFs derives the net point spread function of HSI data based on nominal data acquisition and sensor parameters (sensor speed, sensor heading, sensor altitude, number of cross track pixels, sensor field of view, integration time, frame time and pixel summing level). SC_RS_Analysis_sim calculates a theoretical spatial coverage map for HSI data based on nominal data acquisition and sensor parameters. The spatial coverage map is the sum of the point spread functions of all the pixels collected within an HSI dataset. Practically, the spatial coverage map quantifies how HSI data spatially samples spectral information across an imaged scene. A secondary theoretical spatial coverage map is also calculated for spatially resampled (nearest neighbour approach) HSI data. The function also calculates theoretical resampling errors such as pixel duplication (%), pixel loss (%) and pixel shifting (m). SC_RS_Analysis_NAD calculates an empirical spatial coverage map for collected HSI data (before and after spatial resampling) based on its nominal data acquisition and sensor parameters. The function also calculates empirical resampling errors. The current implementation of SC_RS_Analysis_NAD only works for ITRES (Calgary, Alberta, Canada) data products as it uses auxiliary information generated during the ITRES data processing workflow. This auxiliary information includes a ground look-up table that specifies the location (easting and northing) of each pixel of the HSI data in its raw sensor geometry. This auxiliary information also includes the pixel-to-pixel mapping between the HSI data in its raw sensor geometry and the spatially resampled HSI data. SC_RS_Analysis_NAD can readily be modified to work with HSI data collected by sensors from other manufacturers so long as the required auxiliary information can be extracted during data processing.

Graffiti presents serious urban concerns, often signaling urban decay. This study uses open spatial data to analyze and model graffiti occurrences in terms of street network centrality measures. In particular, betweenness centrality, closeness centrality, and degree centrality are evaluated using San Francisco, California, as the case study area, with data from OpenStreetMap and reported graffiti from 2008 to 2023 from the San Francisco nonemergency municipal service (denoted as 311) as the data sets. The spatial error model was found to outperform both ordinary least squares tests and the spatial lag model. The model could further explain graffiti spatiality. Graffiti writers were observed to favor street segments that are close to the downtown and well-connected to other streets, often having high accessibility, visibility, and accommodating street furniture. The results indicate that bridges and highway segments that are difficult to stop and tag were typically avoided. In addition, for a given street, the model error in adjacent streets significantly (p 

The USDA Forest Service (USFS) builds multiple versions of percent tree canopy cover data, in order to serve needs of multiple user communities. These datasets encompass CONUS, Coastal Alaska, Hawaii, U.S. Virgin Islands and Puerto Rico. There are three versions of data within the 2016 TCC Product Suite, which include: The initial model outputs referred to as the Analytical data; A masked version of the initial output referred to as Cartographic data; And a modified version built for the National Land Cover Database and referred to as NLCD data, which includes a canopy cover change dataset derived from subtraction of datasets for the nominal years of 2011 and 2016.The Analytical data are the initial model outputs generated in the production workflow. These data are best suited for users who will carry out their own detailed statistical and uncertainty analyses on the dataset and place lower priority on the visual appearance of the dataset for cartographic purposes. Datasets for the nominal years of 2011 and 2016 are available. The Cartographic products mask the initial model outputs to improve the visual appearance of the datasets. These data are best suited for users who prioritize visual appearance of the data for cartographic and illustrative purposes. Datasets for the nominal years of 2011 and 2016 are available. The NLCD data are the result of further processing of the masked data. The goal was to generate three coordinated components. The components are (1) a dataset for the nominal year of 2011, (2) a dataset for the nominal year of 2016, and (3) a dataset that captures the change in canopy cover between the two nominal years of 2011 and 2016. For the NLCD data, the three components meet the criterion of 2011 TCC + change in TCC = 2016 TCC. These NLCD data are best suited for users who require a coordinated three-component data stack where each pixel's values meet the criterion of 2011 TCC + change in TCC = 2016 TCC. Datasets for the nominal years of 2011 and 2016 are available, as well as a dataset that captures the change (loss or gain) in canopy cover between those two nominal years of 2011 and 2016, in areas where change was identified. These tree canopy cover data are accessible for multiple user communities, through multiple channels and platforms, as listed below: Analytical USFS Tree Canopy Cover Datasets USFS Enterprise Data Warehouse Cartographic USFS Tree Canopy Cover Datasets NLCD Multi-Resolution Land Characteristics (MRLC) Consortium USFS Enterprise Data WarehouseThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Maryland Roadway Centerline data consists of linear geometric features which represent the street centerline for all public roadways in the State of Maryland. The centerline represents the geographic location on the roadway between both shoulders (physical center), which often but not always coincides with the center painted line dividing bi-directional travel lanes. Roadway Centerlines data plays an important role in transportation management and planning, while also being the basis for all other roadway related data products. Maryland Roadway Centerline data is the end product of a statewide data sharing process between the Federal Highway Administration (FHWA), Maryland Department of Transportation (MDOT), Maryland Department of Transportation State Highway Administration (MDOT SHA), county governments and local municipal governments. Using a common centerline allows for better exchange of information related to the roadway system and provides opportunities for more efficient collection of information about roadway assets. Some centerlines were created in-house using imagery, GPS data, and MDOT SHA's Highway Performance Monitoring System (HPMS) database and others were received from county governments and updated in house using imagery, GPS data and MDOT SHA's HPMS database. The Centerline data includes annual HPMS updates / improvements submitted to the Federal Highway Administration (FHWA). Maryland Roadway Centerline data is needed for emergency response and management, routing buses and other vehicles, planning for land use and transportation needs, continuity of roadway data and display at county boundaries leading to the same "look and feel" across jurisdictions, tracking assets on and along the roadway network, producing maps at various scales, and numerous other applications. There are opportunities to make these processes more efficient, and this program addresses a shared foundation to solve some of these issues. This data is also used by various business units throughout MDOT, as well as many other Federal, State and local government agencies. Maryland Roadway Centerline data is updated and published on an annual basis for the prior year. This data is for the year 2017. For additional information, contact MDOT SHA Geospatial Technologies Email: GIS@mdot.state.md.us For additional information related to the Maryland Department of Transportation (MDOT) Website: https://www.mdot.maryland.gov/ For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA): Website: https://roads.maryland.gov/Home.aspx MDOT SHA Geospatial Data Legal Disclaimer: The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.

Maryland Roadway Centerline data consists of linear geometric features which represent the street centerline for all public roadways in the State of Maryland. The centerline represents the geographic location on the roadway between both shoulders (physical center), which often but not always coincides with the center painted line dividing bi-directional travel lanes. Roadway Centerlines data plays an important role in transportation management and planning, while also being the basis for all other roadway related data products. Maryland Roadway Centerline data is the end product of a statewide data sharing process between the Federal Highway Administration (FHWA), Maryland Department of Transportation (MDOT), Maryland Department of Transportation State Highway Administration (MDOT SHA), county governments and local municipal governments. Using a common centerline allows for better exchange of information related to the roadway system and provides opportunities for more efficient collection of information about roadway assets. Some centerlines were created in-house using imagery, GPS data, and MDOT SHA's Highway Performance Monitoring System (HPMS) database and others were received from county governments and updated in house using imagery, GPS data and MDOT SHA's HPMS database. The Centerline data includes annual HPMS updates / improvements submitted to the Federal Highway Administration (FHWA). Maryland Roadway Centerline data is needed for emergency response and management, routing buses and other vehicles, planning for land use and transportation needs, continuity of roadway data and display at county boundaries leading to the same "look and feel" across jurisdictions, tracking assets on and along the roadway network, producing maps at various scales, and numerous other applications. There are opportunities to make these processes more efficient, and this program addresses a shared foundation to solve some of these issues. This data is also used by various business units throughout MDOT, as well as many other Federal, State and local government agencies. Maryland Roadway Centerline data is updated and published on an annual basis for the prior year. This data is for the year 2017. For additional information, contact MDOT SHA Geospatial Technologies Email: GIS@mdot.state.md.us For additional information related to the Maryland Department of Transportation (MDOT) Website: https://www.mdot.maryland.gov/ For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA): Website: https://roads.maryland.gov/Home.aspx MDOT SHA Geospatial Data Legal Disclaimer: The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.