Ce jeu de données contient les intersections des voies de circulation nommées. Il est destiné à alimenter un géocodeur pour faciliter la recherche de croisements, carrefours. Il a été extrait des données OpenStreetMap par une requête postgis disponible sur https://gist.github.com/cquest/c0a84e6757d15e66e6ae429e91a74a9e Ces données ont été ajoutées à l'instance de géocodage addok disponible sur demo.addok.xyz

This street centerline lines feature class represents current right of way in the City of Los Angeles. It shows the official street names and is related to the official street name data. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most current geographic information of the public right of way. The right of way information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works. Street Centerline layer was created in geographical information systems (GIS) software to display Dedicated street centerlines. The street centerline layer is a feature class in the LACityCenterlineData.gdb Geodatabase dataset. The layer consists of spatial data as a line feature class and attribute data for the features. City of LA District Offices use Street Centerline layer to determine dedication and street improvement requirements. Engineering street standards are followed to dedicate the street for development. The Bureau of Street Services tracks the location of existing streets, who need to maintain that road. Additional information was added to Street Centerline layer. Address range attributes were added make layer useful for geocoding. Section ID values from Bureau of Street Services were added to make layer useful for pavement management. Department of City Planning added street designation attributes taken from Community Plan maps. The street centerline relates to the Official Street Name table named EASIS, Engineering Automated Street Inventory System, which contains data describing the limits of the street segment. A street centerline segment should only be added to the Street Centerline layer if documentation exists, such as a Deed or a Plan approved by the City Council. Paper streets are street lines shown on a recorded plan but have not yet come into existence on the ground. These street centerline segments are in the Street Centerline layer because there is documentation such as a Deed or a Plan for the construction of that street. Previously, some street line features were added although documentation did not exist. Currently, a Deed, Tract, or a Plan must exist in order to add street line features. Many street line features were edited by viewing the Thomas Bros Map's Transportation layer, TRNL_037 coverage, back when the street centerline coverage was created. When TBM and BOE street centerline layers were compared visually, TBM's layer contained many valid streets that BOE layer did not contain. In addition to TBM streets, Planning Department requested adding street line segments they use for reference. Further, the street centerline layer features are split where the lines intersect. The intersection point is created and maintained in the Intersection layer. The intersection attributes are used in the Intersection search function on NavigateLA on BOE's web mapping application NavigateLA. The City of Los Angeles Municipal code states, all public right-of-ways (roads, alleys, etc) are streets, thus all of them have intersections. Note that there are named alleys in the BOE Street Centerline layer. Since the line features for named alleys are stored in the Street Centerline layer, there are no line features for named alleys in those areas that are geographically coincident in the Alley layer. For a named alley , the corresponding record contains the street designation field value of ST_DESIG = 20, and there is a name stored in the STNAME and STSFX fields.List of Fields:SHAPE: Feature geometry.OBJECTID: Internal feature number.STNAME_A: Street name Alias.ST_SUBTYPE: Street subtype.SV_STATUS: Status of street in service, whether the street is an accessible roadway. Values: • Y - Yes • N - NoTDIR: Street direction. Values: • S - South • N - North • E - East • W - WestADLF: From address range, left side.ZIP_R: Zip code right.ADRT: To address range, right side.INT_ID_TO: Street intersection identification number at the line segment's end node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.SECT_ID: Section ID used by the Bureau of Street Services. Values: • none - No Section ID value • private - Private street • closed - Street is closed from service • temp - Temporary • propose - Proposed construction of a street • walk - Street line is a walk or walkway • known as - • numeric value - A 7 digit numeric value for street resurfacing • outside - Street line segment is outside the City of Los Angeles boundary • pierce - Street segment type • alley - Named alleySTSFX_A: Street suffix Alias.SFXDIR: Street direction suffix Values: • N - North • E - East • W - West • S - SouthCRTN_DT: Creation date of the polygon feature.STNAME: Street name.ZIP_L: Zip code left.STSFX: Street suffix. Values: • BLVD - BoulevardADLT: To address range, left side.ID: Unique line segment identifierMAPSHEET: The alpha-numeric mapsheet number, which refers to a valid B-map or A-map number on the Cadastral tract index map. Values: • B, A, -5A - Any of these alpha-numeric combinations are used, whereas the underlined spaces are the numbers.STNUM: Street identification number. This field relates to the Official Street Name table named EASIS, to the corresponding STR_ID field.ASSETID: User-defined feature autonumber.TEMP: This attribute is no longer used. This attribute was used to enter 'R' for reference arc line segments that were added to the spatial data, in coverage format. Reference lines were temporary and not part of the final data layer. After editing the permanent line segments, the user would delete temporary lines given by this attribute.LST_MODF_DT: Last modification date of the polygon feature.REMARKS: This attribute is a combination of remarks about the street centerline. Values include a general remark, the Council File number, which refers the street status, or whether a private street is a private driveway. The Council File number can be researched on the City Clerk's website http://cityclerk.lacity.org/lacityclerkconnect/INT_ID_FROM: Street intersection identification number at the line segment's start node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.ADRF: From address range, right side.

A subset of parent FIREARM DATA.csv, this file contains only intersections of seized firearms, with limited success in geocoding from Lojic ArcGIS geocoder. This file contains X and Y coordinates in Kentucky State Plane North coordinate system, in addition to converted Latitude and Longitude coordinates.Data Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence rooms and can be used to connect the dataset to the other datasets UCR_CATEGORY - the UCR based highest offense associated with the incident. For more information on UCR standards please visit https://ucr.fbi.gov/ucrTYPE_OF_FIREARM - based on the Firearm type, eg “pistol, revolver” or “shotgun, pump action” this field is for general categorization of the Firearm.FIREARMS_MANUFACTURE - the group, or company who manufactured the FirearmFIREARMS_MODEL - secondary information used to identify the Firearm.FIREARMS_CALIBER - the caliber associated with the Firearm, we use federally supplied caliber codes.RECOVERY_DATE - the date the item was identified or taken into custody.RECOVERY_BLOCK_ADRESS - the location the items was identified or taken into custody.RECOVERY_ZIPCODE - the zip code associated to the recovery block location.PERSON_RECOVERED_FROM RACE - the race associated with person who identified the item or was taken into custody from. The person listed may be the person who found the item, not the person associated with the firearm or offense.PERSON_RECOVERED_FROM _SEX - the sex associated with person who identified the item or was taken into custody from. The person listed may be the person who found the item, not the person associated with the firearm or offense.PERSON_RECOVERED_FROM AGE - the age associated with person who identified the item or was taken into custody from. The person listed may be the person who found the item, not the person associated with the firearm or offense.YEAR - the year the incident happened, useful for times the data is masked.

This dataset offers a detailed inventory of road intersections and their corresponding suburbs within Cape Town, meticulously curated to highlight instances of high motorcycle (Motorcycle: Above 125cc, Motorcycle: 125cc and under, Quadru-cycle, Motor Tricycle) crash counts that resulted in injuries (slight, serious, fatalities) observed in "high-high" cluster and "high-low" outlier fishnet grid cells across the years 2017, 2018 and 2019. To enhance its utility, the dataset meticulously colour-codes each month associated with elevated crash occurrences, providing a nuanced perspective. Furthermore, the dataset categorises road intersections based on their placement within "high-high" clusters (marked with pink tabs) or "high-low" outlier cells (indicated by red tabs). For ease of navigation, the intersections are further organised alphabetically by suburb name, ensuring accessibility and clarity.Data SpecificsData Type: Geospatial-temporal categorical data with numeric attributesFile Format: Word document (.docx)Size: 157 KBNumber of Files: The dataset contains a total of 158 road intersection records (11 "high-high" clusters and 147 "high-low" outliers)Date Created: 22nd May 2024MethodologyData Collection Method: The descriptive road traffic crash data per crash victim involved in the crashes was obtained from the City of Cape Town Network InformationSoftware: ArcGIS Pro, Open Refine, Python, SQLProcessing Steps: The raw road traffic crash data underwent a comprehensive refining process using Python software to ensure its accuracy and consistency. Following this, duplicates were eliminated to retain only one entry per crash incident. Subsequently, the data underwent further refinement with Open Refine software, focusing specifically on isolating unique crash descriptions for subsequent geocoding in ArcGIS Pro. Notably, during this process, only the road intersection crashes were retained, as they were the only incidents with spatial definitions.Once geocoded, road intersection crashes that involved either a motor tricycle, motorcycle above 125cc, motorcycle below 125cc and quadru-cycles and that were additionally associated with a slight, severe or fatal injury type were extracted so that subsequent spatio-temporal analyses would focus on these crashes only. The spatio-temporal analysis methods by which these motorcycle crashes were analysed included spatial autocorrelation, hotspot analysis, and cluster and outlier analysis. Leveraging these methods, road intersections with motorcycle crashes identified as either "high-high" clusters or "high-low" outliers were extracted for inclusion in the dataset.Geospatial InformationSpatial Coverage:West Bounding Coordinate: 18°20'EEast Bounding Coordinate: 19°05'ENorth Bounding Coordinate: 33°25'SSouth Bounding Coordinate: 34°25'SCoordinate System: South African Reference System (Lo19) using the Universal Transverse Mercator projectionTemporal InformationTemporal Coverage:Start Date: 01/01/2017End Date: 31/12/2019

The MAR Web Geocoder is a web browser-based tool for geocoding locations, typically addresses, in Washington, DC. It is developed by the Office of Chief Technology Officer (OCTO) and can input Excel or CSV files to output an Excel file. Geocoding is the process of assigning a _location in the form of geographic coordinates (often expressed as latitude and longitude) to spreadsheet data. This is done by comparing the descriptive geographic data to known geographic locations such as addresses, blocks, intersections, or place names.

This dataset offers a detailed inventory of road intersections and their corresponding suburbs within Cape Town, meticulously curated to highlight instances of high pedestrian crash counts observed in "high-high" cluster and "high-low" outlier fishnet grid cells across the years 2017, 2018, 2019, and 2021. To enhance its utility, the dataset meticulously colour-codes each month associated with elevated crash occurrences, providing a nuanced perspective. Furthermore, the dataset categorises road intersections based on their placement within "high-high" clusters (marked with pink tabs) or "high-low" outlier cells (indicated by red tabs). For ease of navigation, the intersections are further organised alphabetically by suburb name, ensuring accessibility and clarity.Data SpecificsData Type: Geospatial-temporal categorical data with numeric attributesFile Format: Word document (.docx)Size: 255 KBNumber of Files: The dataset contains a total of 264 road intersection records (68 "high-high" clusters and 196 "high-low" outliers)Date Created: 21st May 2024MethodologyData Collection Method: The descriptive road traffic crash data per crash victim involved in the crashes was obtained from the City of Cape Town Network InformationSoftware: ArcGIS Pro, Open Refine, Python, SQLProcessing Steps: The raw road traffic crash data underwent a comprehensive refining process using Python software to ensure its accuracy and consistency. Following this, duplicates were eliminated to retain only one entry per crash incident. Subsequently, the data underwent further refinement with Open Refine software, focusing specifically on isolating unique crash descriptions for subsequent geocoding in ArcGIS Pro. Notably, during this process, only the road intersection crashes were retained, as they were the only incidents with spatial definitions.Once geocoded, road intersection crashes that involved a pedestrian were extracted so that subsequent spatio-temporal analyses would focus on these crashes only. The spatio-temporal analysis methods by which the pedestrian crashes were analysed included spatial autocorrelation, hotspot analysis, and cluster and outlier analysis. Leveraging these methods, road intersections involving pedestrian crashes identified as either "high-high" clusters or "high-low" outliers were extracted for inclusion in the dataset.Geospatial InformationSpatial Coverage:West Bounding Coordinate: 18°20'EEast Bounding Coordinate: 19°05'ENorth Bounding Coordinate: 33°25'SSouth Bounding Coordinate: 34°25'SCoordinate System: South African Reference System (Lo19) using the Universal Transverse Mercator projectionTemporal InformationTemporal Coverage:Start Date: 01/01/2017End Date: 31/12/2021 (2020 data omitted)

The BC Address Geocoder is a REST API that can used to resolve the physical locations of addresses and place names in British Columbia (i.e., their latitude and longitude). It also provides additional capability, such as correcting and standardizing civic and non-civic addresses, reverse geocoding addresses within areas of interest, locating intersections and identifying parcels associated with specific addresses. For more information please see the glossary and the developer guide. The API is governed by these terms of use, with the exception of the parcels API resource (see note below). Note: the parcels API resource is restricted to B.C. government ministries use only. Ministries should contact DataBC to request an API key.

This dataset offers a detailed inventory of road intersections and their corresponding suburbs within Cape Town, meticulously curated to highlight instances of high public transport (Bus, Bus-train, Combi/minibus, Midibus) crash counts observed in "high-high" cluster and "high-low" outlier fishnet grid cells across the years 2017, 2018, 2019, and 2021. To enhance its utility, the dataset meticulously colour-codes each month associated with elevated crash occurrences, providing a nuanced perspective. Furthermore, the dataset categorises road intersections based on their placement within "high-high" clusters (marked with pink tabs) or "high-low" outlier cells (indicated by red tabs). For ease of navigation, the intersections are further organised alphabetically by suburb name, ensuring accessibility and clarity.Data SpecificsData Type: Geospatial-temporal categorical data with numeric attributesFile Format: Word document (.docx)Size: 49,0 KBNumber of Files: The dataset contains a total of 40 road intersection records (28 "high-high" clusters and 12 "high-low" outliers)Date Created: 21st May 2024MethodologyData Collection Method: The descriptive road traffic crash data per crash victim involved in the crashes was obtained from the City of Cape Town Network InformationSoftware: ArcGIS Pro, Open Refine, Python, SQLProcessing Steps: The raw road traffic crash data underwent a comprehensive refining process using Python software to ensure its accuracy and consistency. Following this, duplicates were eliminated to retain only one entry per crash incident. Subsequently, the data underwent further refinement with Open Refine software, focusing specifically on isolating unique crash descriptions for subsequent geocoding in ArcGIS Pro. Notably, during this process, only the road intersection crashes were retained, as they were the only incidents with spatial definitions.Once geocoded, road intersection crashes that involved either a bus, a bus/train, combi/minibus and midibuses were extracted so that subsequent spatio-temporal analyses would focus on these crashes only. The spatio-temporal analysis methods by which the public transport crashes were analysed included spatial autocorrelation, hotspot analysis, and cluster and outlier analysis. Leveraging these methods, road intersections with public transport crashes identified as either "high-high" clusters or "high-low" outliers were extracted for inclusion in the dataset.Geospatial InformationSpatial Coverage:West Bounding Coordinate: 18°20'EEast Bounding Coordinate: 19°05'ENorth Bounding Coordinate: 33°25'SSouth Bounding Coordinate: 34°25'SCoordinate System: South African Reference System (Lo19) using the Universal Transverse Mercator projectionTemporal InformationTemporal Coverage:Start Date: 01/01/2017End Date: 31/12/2021 (2020 data omitted)

Roadway SubBlocks - Right of Way Information. A single line, segmented at all intersections (alley and others), representing each street in the District. They follow the general trend of the street and do not deviate due to parking lanes, turning lanes, etc. and contain address ranges for geocoding. The street GIS database includes five different street road types: street centerline, alley, drive, ramp and service road. All DC GIS data is stored and exported in Maryland State Plane coordinates NAD 83 meters. This layer contains complete theoretical address ranges.

The Street Centerlines layer is a series of lines (or polylines) digitized along the center of streets. These lines connected at intersections creating a street network. Each line carries attributes for the street name, address range, road class, jurisdiction and other data items.

Street centerlines are one of the most fundamental and useful G.I.S. layers. There are many applications that require accurate and comprehensive street centerlines datasets. Main applications: Networking (routing, navigating etc.) Geocoding - assigning a geographic location to an address based on the address ranges stored in the street data.

Road segments representing centerlines of all roadways or carriageways in a local government. Typically, this information is compiled from orthoimagery or other aerial photography sources. This representation of the road centerlines support address geocoding and mapping. It also serves as a source for public works and other agencies that are responsible for the active management of the road network. (From ESRI Local Government Model "RoadCenterline" Feature)**This dataset was significantly revised in August of 2014 to correct for street segments that were not properly split at intersections. There may be issues with using data based off of the original centerline file. ** The column Speed Limit was updated in November 2014 by the Transportation Intern and is believed to be accurate** The column One Way was updated in November of 2014 by core GIS and is believed to be accurate.[MAXIMOID] A unique id field used in a work order management software called Maximo by IBM. Maximo uses GIS CL data to assign locations to work orders using this field. This field is maintained by the Transportation GIS specialists and is auto incremented when new streets are digitized. For example, if the latest digitized street segment MAXIMOID = 999, the next digitized line will receive MAXIMOID = 1000, and so on. STREET NAMING IS BROKEN INTO THREE FIELDS FOR GEOCODING:PREFIX This field is attributed if a street name has a prefix such as W, N, E, or S.NAME Domain with all street names. The name of the street without prefix or suffix.ROAD_TYPE (Text,4) Describes the type of road aka suffix, if applicable. CAPCOG Addressing Guidelines Sec 504 U. states, “Every road shall have corresponding standard street suffix…” standard street suffix abbreviations comply with USPS Pub 28 Appendix C Street Abbreviations. Examples include, but are not limited to, Rd, Dr, St, Trl, Ln, Gln, Lp, CT. LEFT_LOW The minimum numeric address on the left side of the CL segment. Left side of CL is defined as the left side of the line segment in the From-To direction. For example, if a line has addresses starting at 101 and ending at 201 on its left side, this column will be attributed 101.LEFT_HIGH The largest numeric address on the left side of the CL segment. Left side of CL is defined as the left side of the line segment in the From-To direction. For example, if a line has addresses starting at 101 and ending at 201 on its left side, this column will be attributed 201.LOW The minimum numeric address on the RIGHT side of the CL segment. Right side of CL is defined as the right side of the line segment in the From-To direction. For example, if a line has addresses starting at 100 and ending at 200 on its right side, this column will be attributed 100.HIGHThe maximum numeric address on the RIGHT side of the CL segment. Right side of CL is defined as the right side of the line segment in the From-To direction. For example, if a line has addresses starting at 100 and ending at 200 on its right side, this column will be attributed 200.ALIAS Alternative names for roads if known. This field is useful for geocode re-matching. CLASSThe functional classification of the centerline. For example, Minor (Minor Arterial), Major (Major Arterial). THIS FIELD IS NOT CONSISTENTLY FILLED OUT, NEEDS AN AUDIT. FULLSTREET The full name of the street concatenating the [PREFIX], [NAME], and [SUFFIX] fields. For example, "W San Antonio St."ROWWIDTH Width of right-of-way along the CL segment. Data entry from Plat by Planning GIS Or from Engineering PICPs/ CIPs.NUMLANES Number of striped vehicular driving lanes, including turn lanes if present along majority of segment. Does not inlcude bicycle lanes. LANEMILES Describes the total length of lanes for that segment in miles. It is manually field calculated as follows (( [ShapeLength] / 5280) * [NUMLANES]) and maintained by Transportation GIS.SPEEDLIMIT Speed limit of CL segment if known. If not, assume 30 mph for local and minor arterial streets. If speed limit changes are enacted by city council they will be recorded in the Traffic Register dataset, and this field will be updating accordingly. Initial data entry made by CIP/Planning GIS and maintained by Transportation GIS.[YRBUILT] replaced by [DateBuilt] See below. Will be deleted. 4/21/2017LASTYRRECON (Text,10) Is the last four-digit year a major reconstruction occurred. Most streets have not been reconstructed since orignal construction, and will have values. The Transportation GIS Specialist will update this field. OWNER Describes the governing body or private entity that owns/maintains the CL. It is possible that some streets are owned by other entities but maintained by CoSM. Possible attributes include, CoSM, Hays Owned/City Maintained, TxDOT Owned/City Maintained, TxDOT, one of four counties (Hays, Caldwell, Guadalupe, and Comal), TxState, and Private.ST_FROM Centerline segments are split at their intersections with other CL segments. This field names the nearest cross-street in the From- direction. Should be edited when new CL segments that cause splits are added. ST_TO Centerline segments are split at their intersections with other CL segments. This field names the nearest cross-street in the To- direction. Should be edited when new CL segments that cause splits are added. PAV_WID Pavement width of street in feet from back-of-curb to back-of-curb. This data is entered from as-built by CIP GIS. In January 2017 Transportation Dept. field staff surveyed all streets and measured width from face-of-curb to face-of-curb where curb was present, and edge of pavement to edge of pavement where it was not. This data was used to field calculate pavement width where we had values. A value of 1 foot was added to the field calculation if curb and gutter or stand up curb were present (the face-of-curb to back-of-curb is 6 in, multiple that by 2 to find 1 foot). If no curb was present, the value enter in by the field staff was directly copied over. If values were already present, and entered from asbuilt, they were left alone. ONEWAY Field describes direction of travel along CL in relation to digitized direction. If a street allows bi-directional travel it is attributed "B", a street that is one-way in the From_To direction is attributed "F", a street that is one-way in the To_From direction is attributed "T", and a street that does not allow travel in any direction is attibuted "N". ROADLEVEL Field will be aliased to [MINUTES] and be used to calculate travel time along CL segments in minutes using shape length and [SPEEDLIMIT]. Field calculate using the following expression: [MINUTES] = ( ([SHAPE_LENGTH] / 5280) / ( [SPEEDLIMIT] / 60 ))ROWSTATUS Values include "Open" or "Closed". Describes whether a right-of-way is open or closed. If a street is constructed within ROW it is "Open". If a street has not yet been constructed, and there is ROW, it is "Cosed". UPDATE: This feature class only has CL geometries for "Open" rights-of-way. This field should be deleted or re-purposed. ASBUILT field used to hyper link as-built documents detailing construction of the CL. Field was added in Dec. 2016. DateBuilt Date field used to record month and year a road was constructed from Asbuilt. Data was collected previously without month information. Data without a known month is entered as "1/1/YYYY". When month and year are known enter as "M/1/YYYY". Month and Year from asbuilt. Added by Engineering/CIP. ACCEPTED Date field used to record the month, day, and year that a roadway was officially accepted by the City of San Marcos. Engineering signs off on acceptance letters and stores these documents. This field was added in May of 2018. Due to a lack of data, the date built field was copied into this field for older roadways. Going forward, all new roadways will have this date. . This field will typically be populated well after a road has been drawn into GIS. Entered by Engineering/CIP. ****In an effort to make summarizing the data more efficient in Operations Dashboard, a generic date of "1/1/1900" was assigned to all COSM owned or maintained roads that had NULL values. These were roads that either have not been accepted yet, or roads that were expcepted a long time ago and their accepted date is not known. WARRANTY_EXP Date field used to record the expiration date of a newly accepted roadway. Typically this is one year from acceptance date, but can be greater. This field was added in May of 2018, so only roadways that have been excepted since and older roadways with valid warranty dates within this time frame have been populated.

Roadway SubBlocks - Right of Way Information. A single line, segmented at all intersections (alley and others), representing each street in the District. They follow the general trend of the street and do not deviate due to parking lanes, turning lanes, etc. and contain address ranges for geocoding. The street GIS database includes five different street road types: street centerline, alley, drive, ramp and service road. All DC GIS data is stored and exported in Maryland State Plane coordinates NAD 83 meters. This layer contains complete theoretical address ranges.

This is publishing-level featureclass contains features which are used for geocoding addresses and intersections.

© This data set was created by Hennepin County Taxpayer Services Survey Division.

Street Centerlines 2013. A single line, segmented at all intersections (alley and others), representing each street in the District. They follow the general trend of the street and do not deviate due to parking lanes, turning lanes, etc. and contain address ranges for geocoding. The street GIS database includes five different street road types: street centerline, alley, drive, ramp and service road. This layer contains complete theoretical address ranges.

The Road Inventory is a GIS-based asset management system for the state's highway transportation system. As such, its strengths are in describing the configuration and condition of public roads and rights-of-way. It is not designed to support route-finding (e.g., shortest path applications), nor is it designed to support geocoding (although in theory intersection-based geocoding could be set up on it). It is part of the official documentation of the state road system and is used to prepare the yearly Highway Performance Monitoring System (HPMS) report to the Federal Highway Administration (FHWA). It is a record of centerline and lane miles, which are the basis of state reimbursements to localities for road maintenance expenses (Chapter 90 funds).The Massachusetts Department of Transportation Highway Division Road Inventory contains the spatial linework for all the public and a good portion of the private roadways in Massachusetts, along with roadway attributes covering the roadway classification, ownership, physical conditions, traffic volumes, pavement conditions, highway performance monitoring information, and more. This version has been processed to eliminate overlaps among features in the original distributed by MassDOT and to add pavement data, which is no longer attached by MassDOT.

Roadway Street Block by Functional Class. A single line, segmented at all intersections (alley, service road, drive, street, and driveway centerline types), representing each street in the District. They follow the general trend of the street and do not deviate due to parking lanes, turning lanes, etc. and contain address ranges for geocoding. The street GIS database includes five different street road types: Collector, Interstate, Local, Minor Arterial, Other Freeway and Expressway, Principal Arterial

Street Centerlines 2005. A single line, segmented at all intersections (alley and others), representing each street in the District. They follow the general trend of the street and do not deviate due to parking lanes, turning lanes, etc. and contain address ranges for geocoding. The street GIS database includes five different street road types: street centerline, alley, drive, ramp and service road. This layer contains complete theoretical address ranges.

Street Centerlines 2005. A single line, segmented at all intersections (alley and others), representing each street in the District. They follow the general trend of the street and do not deviate due to parking lanes, turning lanes, etc. and contain address ranges for geocoding. The street GIS database includes five different street road types: street centerline, alley, drive, ramp and service road. This layer contains complete theoretical address ranges.

Roadway Street Block by Functional Class. A single line, segmented at all intersections (alley, service road, drive, street, and driveway centerline types), representing each street in the District. They follow the general trend of the street and do not deviate due to parking lanes, turning lanes, etc. and contain address ranges for geocoding. The street GIS database includes five different street road types: Collector, Interstate, Local, Minor Arterial, Other Freeway and Expressway, Principal ArterialFor more information please visit DDOT's wiki page.

The VMTRoadInventory 2016 Is a version of the Road Inventory 2016 that contains Vehicle Miles Traveled (VMT) for the Road Inventory, in Massachusetts for the year 2016. The Road Inventory is a GIS-based asset management system for the state's highway transportation system. As such, its strengths are in describing the configuration and condition of public roads and rights-of-way. It is not designed to support route-finding (e.g., shortest path applications), nor is it designed to support geocoding (although in theory intersection-based geocoding could be set up on it). It is part of the official documentation of the state road system and is used to prepare the yearly Highway Performance Monitoring System (HPMS) report to the Federal Highway Administration (FHWA). It is a record of centerline and lane miles, which are the basis of state reimbursements to localities for road maintenance expenses (Chapter 90 funds).