This intersection points feature class represents current intersections in the City of Los Angeles. Few intersection points, named pseudo nodes, are used to split the street centerline at a point that is not a true intersection at the ground level. 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.Intersection layer was created in geographical information systems (GIS) software to display intersection points. Intersection points are placed where street line features join or cross each other and where freeway off- and on-ramp line features join street line features. The intersection points layer is a feature class in the LACityCenterlineData.gdb Geodatabase dataset. The layer consists of spatial data as a point feature class and attribute data for the features. The intersection points relates to the intersection attribute table, which contains data describing the limits of the street segment, by the CL_NODE_ID field. The layer shows the location of the intersection points on map products and web mapping applications, and the Department of Transportation, LADOT, uses the intersection points in their GIS system. The intersection attributes are used in the Intersection search function on BOE's web mapping application NavigateLA. The intersection spatial data and related attribute data are maintained in the Intersection layer using Street Centerline Editing application. The City of Los Angeles Municipal code states, all public right-of-ways (roads, alleys, etc) are streets, thus all of them have intersections. List of Fields:Y: This field captures the georeferenced location along the vertical plane of the point in the data layer that is projected in Stateplane Coordinate System NAD83. For example, Y = in the record of a point, while the X = .CL_NODE_ID: This field value is entered as new point features are added to the edit layer, during Street Centerline application editing process. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline spatial data layer, then the intersections point spatial data layer, and then the intersections point attribute data during the creation of new intersection points. Each intersection identification number is a unique value. The value relates to the street centerline layer attributes, to the INT_ID_FROM and INT_ID_TO fields. One or more street centerline features intersect the intersection point feature. For example, if a street centerline segment ends at a cul-de-sac, then the point feature intersects only one street centerline segment.X: This field captures the georeferenced location along the horizontal plane of the point in the data layer that is projected in Stateplane Coordinate System NAD83. For example, X = in the record of a point, while the Y = .ASSETID: User-defined feature autonumber.USER_ID: The name of the user carrying out the edits.SHAPE: Feature geometry.LST_MODF_DT: Last modification date of the polygon feature.LAT: This field captures the Latitude in deciaml degrees units of the point in the data layer that is projected in Geographic Coordinate System GCS_North_American_1983.OBJECTID: Internal feature number.CRTN_DT: Creation date of the polygon feature.TYPE: This field captures a value for intersection point features that are psuedo nodes or outside of the City. A pseudo node, or point, does not signify a true intersection of two or more different street centerline features. The point is there to split the line feature into two segments. A pseudo node may be needed if for example, the Bureau of Street Services (BSS) has assigned different SECT_ID values for those segments. Values: • S - Feature is a pseudo node and not a true intersection. • null - Feature is an intersection point. • O - Intersection point is outside of the City of LA boundary.LON: This field captures the Longitude in deciaml degrees units of the point in the data layer that is projected in Geographic Coordinate System GCS_North_American_1983.

This dataset lists all current protected streets throughout the five boroughs. Note: NYCDOT provides this map for informational purpose only. The City makes no presentation as to the accuracy of the content and assumes no liability for omissions or errors in information contains on the website.

For the map, please follow this link.

Street intersections are challenging for people with visual impairments. While tactile maps are an important support in both mobility training and independent journeys, the caseload of manual map production has made them less accessible. This paper explores the possibility of (semi-) automatically producing tactile maps for street intersections at large scales, with an initial evaluation focused on the graphic aspect of the produced maps. The automation attempts to identify acceptable default parameters and values and proposes an exploration of possible choices for potentially open decisions. It adapts the classic map production process with parameters to present the information tactilely at the intersection scale, and produces representation meaningful for PVIs and realistic for an automatic procedure, resulting in ready-to-print maps in two scales of three sizes, with different levels of details and styles. The resulting maps are evaluated by professionals involved in tactile graphics through a questionnaire to evaluate the defaults and discuss the possibility of open choices. The professionals validated the maps, and their evaluation emphasized the need to have an acceptable default while keeping some options open to cater to the diversity in the visually impaired audience.

Street intersections are challenging for people with visual impairments. While tactile maps are an important support in both mobility training and independent journeys, the caseload of manual map production has made them less accessible. This paper explores the possibility of (semi-) automatically producing tactile maps for street intersections at large scales, with an initial evaluation focused on the graphic aspect of the produced maps. The automation attempts to identify acceptable default parameters and values and proposes an exploration of possible choices for potentially open decisions. It adapts the classic map production process with parameters to present the information tactilely at the intersection scale, and produces representation meaningful for PVIs and realistic for an automatic procedure, resulting in ready-to-print maps in two scales of three sizes, with different levels of details and styles. The resulting maps are evaluated by professionals involved in tactile graphics through a questionnaire to evaluate the defaults and discuss the possibility of open choices. The professionals validated the maps, and their evaluation emphasized the need to have an acceptable default while keeping some options open to cater to the diversity in the visually impaired audience.

Intersection Approach Segments are short segments of the route that approach an intersection, in other words, a short section of the road leading up to an intersection.Roads and Highways manages intersections, however they are not singular points; RH creates a series of points - one for each intersecting road at that intersection. For DDOT, it is more useful to have a single intersection point representing the intersection. Through a custom DDOT script,the series of intersection points is reduced into a single representative point.For more information please visit DDOT's wiki page.

Point geometry with attributes displaying street intersections of all public and private named roads in East Baton Rouge Parish, Louisiana.

Wake County Street Intersection Points, updated weekly.

This dataset contains intersections located along Utah state highways. Descriptive information includes signalization and state route intersection flags. Location information includes x,y and route & milepost. This dataset is a Pathway data layer that was collected in the Summer of 2023 via LiDAR inventory. Data is updated on a two year cycle. For questions on the data please contact Ed Graves at edgraves@utah.gov. To download this data please visit UDOT"s Open Data Site.

This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

The Los Angeles Department of Transportation identify a list of 60 prioritized intersections for the development of safety projects. Develop physical design and engineering countermeasures that would most effectively address each intersection.

Tagged image tiles as well as the Faster-RCNN framework for automatic extraction of road intersection points from USGS historical maps of the United States of America. The data and code have been prepared for the paper entitled "Automatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks" submitted to "International Journal of Geographic Information Science". The image tiles have been tagged manually. The Faster RCNN framework (see https://arxiv.org/abs/1611.10012) was captured from:https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md

Roads and Highways manages intersections, however they are not singular points; RH creates a series of points - one for each intersecting road at that intersection. For DDOT, it is more useful to have a single intersection point representing the intersection. Through a custom DDOT script,the series of intersection points is reduced into a single representative point.For more information please visit DDOT's wiki page.

The dataset contains the metadata provided on the NYC Honorary Street Names Map. The dataset will include City Council Introduction Number, the local law enactment number and date, category of change, borough, new name of the street or intersection, present name, limits, zip code, Introduced by Council Member(s), Biographical information of the individual, Notes, Longitude and Latitude coordinates.

This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

1. OverviewRoad intersections are crucial nodes in urban networks, where transportation lanes converge and socioeconomic activity is concentrated. While methods to identify road intersections using raster maps, satellite images, and trace data have been explored, challenges in accuracy and consistency remain.This paper proposes a method for identifying intersections based on OpenStreetMap data, which records networks at the lane level. Unlike geometric line intersections in OpenStreetMap, the identified intersections “summarize” parallel lanes and incorporate branch information, such as counts and orientations. The proposed method uses a vector-raster fusion approach to initially locate intersections, followed by hierarchical geometric configuration to improve accuracy and extract branch data.Experimental results show that the method effectively handles complex road networks in various cities, accurately identifying intersections and their branches. Experiments conducted on OpenStreetMap data from 7 cities yielded over 98% precision and 97% recall, outperforming the popular OSMnx tool. Additionally, lane synthesis at intersections achieved 99.43% precision and 98.34% recall. Urban characteristics can be quantitatively analyzed based on the identified road intersections. For instance, the proportion of four-way road intersections in New York is 52.6%, whereas in London, it is 9.6%, which may be attributed to the differing urban histories of these cities.2. Instructions for dataThis dataset contains road intersection data of seven cities (Berlin, Beijing, London, Nanjing, New York City, Rome, Shanghai) identified by our proposed method.The data of each city are stored in the folder named by its abbreviation.In each folder, there will be five *.shp files:(1) Roadnetwork (roads.shp)This layer stores the OSM road network with tag attributes.(2) Intersection points (cross-res.shp)This layer stores the location of the intersection point and the general characteristics of the road layout, including the number of intersecting roads and layout type. This provides the necessary location information for mapping and spatial analyses.(3) Related road lines (fullLine-res.shp/fail-fullLine.shp)The original road lines related to intersections extracted from the road networks were stored in this layer, preserving the inherent attributes of the original dataset. In addition, matching information, indicating whether the lines represent the same road, was stored as an attribute.(4) Synthesized road lines (simpleLine-res.shp)The geometries of this layer store synthesized road lines representing road orientations, whereas the attributes store acquired characteristics, including roadway configurations and match indices, which allow the synthesized road lines to be connected to the original roads from which they were derived. This connection is achieved through “pt_id” linked with cross-res.shp and “match_id” linked with fullLine-res.shp.3. Instructions for codesThis code repository is organized into eight folders and two files:(1) Folder: candidateIdentifyThis folder contains code related to the identification of candidate junctions or intersections from the input data. Each script plays a specific role in the overall process:bufferThin.py: Implements a thinning algorithm to generate a skeleton of buffered road geometry.candidateIdentify.py: The core script for identifying candidate points for road intersections in a spatial dataset.fastJunction.py: Provides an optimized method for detecting junctions quickly in large datasets by leveraging a fast hit-or-miss operation.junctionGeo.py: Handles the geometric processing of junction points, focusing on transforming raster cells into geographical positions.(2) Folder: compareEvaluationclipByregion.py: Clips spatial data to a specific region, which is useful for limiting analysis to a predefined geographic area. This is typically used to obtain intersections identified within the randomly selected regions.(3) Folder: geometricConfigurationTemplateMatchThis folder includes tools for matching geometric templates of road intersections:templateMatcher.py: The main module that matches geometric configurations of road intersections to the determined templates.utils_g.py: Provides utility functions that assist in geometric operations and template matching processes.(4) Folder: maxRadiusBufferThis folder focuses on the code of a greedy algorithm that produces the largest nonoverlapping buffers for a given collection of points.:maxRadBuffer.py: Core script for this algorithm.(5) Folder: intersectionDistanceAnalysisThis folder contains scripts for analyzing distances between intersection points for parameter determination:distanceAnalysis.py: Calculates the distances between identified intersections and analyze their distribution.(6) Folder: proportionDrawerThis folder contains scripts using R to produce pie charts in Figure 14.(7) Folder: refineCandidateThis folder contains a script that refines the previously identified intersection candidates.refineCandidate.py: This core script refines the set of candidate intersections by applying further geometric or statistical methods.(8) Folder: resultAnalysisThis folder is used for analyzing the identified results for insights of urban characteristics:angleAnalysis.py: Compute and analyze angles between road branches at intersections.4. Instructions on how to reproduce each reported findingsThe file 'instructions_on_how_to_reproduce_each_reported_findings.md' details the steps to reproduce the figures and the tables shown in the paper.

This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

A point feature layer with the locations and names of street intersections within Stark County, Ohio. This layer was initially developed so that police, fire, and EMS would be able to identify the closest street intersection for emergency calls. Within the attribute table, you will find the names for the intersecting streets; the primary and secondary streets are the only attributes that are populated. This data is a work in progress and will be updated periodically as new streets are added to our data. It is planned for each street intersection point to be eventually filled out for the whole county.

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.

This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections are defined as any point where 3 or more roads meet and density is calculated using kernel density, where closer intersections are weighted higher than further intersections. Intersection density is highly correlated with walking for transportation. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Intersection mapping with traffic control device.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**