Type Digital Data
The purpose of this dataset is to provide a consistent, high-resolution, statewide geospatial representation of impervious surface and advanced transportation The purpose of this dataset is to provide a consistent, high-resolution, statewide geospatial representation of impervious surface and advanced transportation features across Connecticut. These data were created to support state, regional, and local applications including transportation planning, infrastructure management, land cover mapping, asset inventory, hydrologic and stormwater analysis, emergency management, and other GIS-based planning and decision-making workflows.
This dataset contains statewide impervious surface and advanced transportation vector features for the State of Connecticut. The dataset was developed from 2023 source imagery to provide a high-resolution, consistent geospatial representation of impervious land cover and transportation-related infrastructure across the state. The impervious surface component includes mapped features such as buildings, roads, driveways, parking areas, sidewalks, pavement, swimming pools, paved recreation surfaces, and bridges. The advanced transportation component includes transportation centerline and lane-related features such as turning lanes, through lanes, bike lanes, shoulders, sidewalks, crosswalks, and related width attribution where applicable. Feature capture and attribution were performed according to defined class-specific interpretation and minimum mapping specifications. The dataset is intended to support statewide mapping, transportation analysis, infrastructure planning, land cover assessment, hydrologic and stormwater analysis, emergency management, and other GIS-based applications. Note: The impervious surface component is represented as polygon features, while the advanced transportation component is represented as polyline features.
Dataset developed by Ecopia AI for the State of Connecticut using 2023 source imagery to support statewide geospatial mapping, transportation analysis, infrastructure planning, and land cover applications. Quality control and review completed by The Dewberry Companies Inc.
None. Users are advised to read the dataset metadata thoroughly to understand appropriate use, data limitations, and known constraints.
There is no extent for this item.
| Maximum (zoomed in) | 1:5,000 |
| Minimum (zoomed out) | 1:150,000,000 |
This dataset package contains three feature files. The Land file is a polygon dataset in which each feature contains the fields FID (unique identifier), Shape (geometry), and CateTitle (feature classification). The Lane and Road files are polyline datasets in which each feature contains the fields FID (unique identifier), Shape (geometry), CateTitle (feature classification), and WIDTH (mean feature width in meters). CateTitle values and their definitions for all three files are provided in the Entity and Attribute Information section of this metadata record.
Dataset developed by Ecopia AI for the State of Connecticut using 2023 source imagery to support statewide geospatial mapping, transportation analysis, infrastructure planning, and land cover applications. Quality control and review completed by The Dewberry Companies Inc.
ground condition
None. Users are advised to read the dataset metadata thoroughly to understand appropriate use, data limitations, and known constraints.
Although these data have been processed successfully on a computer system at the time of production, no warranty expressed or implied is made regarding the accuracy, adequacy, completeness, legality, reliability, or usefulness of the data for any particular purpose. Users assume responsibility for appropriate use and interpretation of the dataset.
None. Please see Distribution Information for details regarding access and availability.
Attribute values were derived through a combination of image-based feature extraction, rule-based classification, attribution workflows, and quality control review. Feature types and associated attributes were assigned according to class-specific capture definitions and minimum mapping specifications established for the project. Impervious surface classifications included buildings, roads, driveways, parking areas, sidewalks, pavement, swimming pools, paved recreation surfaces, and bridges. Transportation classifications included turning lanes, through lanes, bike lanes, shoulders, sidewalks, and crosswalks, with width attribution provided applicable segments. Turning lanes were interpreted to begin at the widening of the street path or the beginning of designated painted areas, and through lanes were segmented at intersections. Sidewalk features were captured as distinct from overlapping driveway or paved surface features where applicable. Quality assurance and quality control procedures were performed to identify and correct attribute inconsistencies, omissions, and classification errors prior to final delivery. Final attribute accuracy targets for feature classifications were defined as false negatives less than or equal to 5 percent, false positives less than or equal to 5 percent, valid interpretation greater than or equal to 95 percent, minimum area compliance of 100 percent, and valid geometry compliance of 100 percent.
The dataset was reviewed for logical consistency with defined feature capture specifications and internal production standards. Quality control procedures were applied to identify and resolve issues related to feature duplication, geometry validity, classification consistency, attribution completeness, and topological integrity where applicable. Polygon-based impervious features were evaluated to confirm compliance with minimum mapping requirements, valid geometry standards, and class-specific interpretation rules. Transportation centerline and lane features were reviewed to ensure consistency in lane categorization, segment structure, width attribution, and class assignment. Through lanes were segmented at intersections, turning lanes were interpreted based on roadway widening or marked painted areas, and bike lanes were distinguished from shared lane markings where visually identifiable. Sidewalks, driveways, roads, and bridges were also reviewed to ensure consistency with feature hierarchy and interpretation rules. Features were evaluated for consistency in structure, spatial representation, and thematic classification prior to final delivery.
The dataset is intended to represent impervious surface and advanced transportation features visible and identifiable from 2023 source imagery in accordance with class-specific capture definitions and minimum mapping thresholds established for the project. Impervious surface feature inclusion was limited to the mapped classes of building, road, driveway, parking, sidewalk, pavement, in-ground swimming pool, paved sports field or recreation area, and bridge. Building footprints represent the interpreted ground footprint of structures based on roofline and wall façade interpretation. Roads represent paved roadway surfaces including curbs. Driveways represent paved surfaces extending from the edge of curb to a structure. Parking areas represent paved surfaces with visible parking lanes. Sidewalks include both public and private sidewalks and take classification priority over overlapping driveway or other paved surfaces where applicable. Pavement represents paved surfaces not otherwise captured by a more specific impervious class. In-ground swimming pools represent clearly identifiable subsurface open water features on residential or commercial properties. Paved sports fields and recreation areas include features such as tennis courts and running tracks. Bridges represent elevated driving surfaces and do not include walking paths. Transportation features include turning lanes, through lanes, bike lanes, shoulders, sidewalks, and crosswalks visible and distinguishable in the source imagery. Bike lanes were captured only where specifically designated for bicycles and visually identifiable. Width measurements were provided for applicable segments. Features obscured by shadow, vegetation, image limitations, overlap conditions, or otherwise not visible or distinguishable in source imagery may be absent or partially represented.
Feature geometry was derived from high-resolution source imagery and aligned to the positional accuracy of the source data used for production. Spatial placement of mapped features was reviewed through internal quality assurance and quality control procedures to ensure reasonable alignment with visible source imagery and project capture specifications. Positional accuracy may vary locally based on source imagery characteristics, feature visibility, and interpretation conditions.
Vertical accuracy is not applicable to this vector feature dataset.
Source imagery and supporting project materials were prepared and reviewed for use in statewide feature extraction and compilation. Source inputs representing 2023 ground conditions were evaluated to support the identification and mapping of impervious surface and advanced transportation features across the State of Connecticut. Production specifications, feature definitions, and capture thresholds were established prior to data extraction.
Impervious surface and advanced transportation features were extracted and compiled from the source imagery using image interpretation, feature extraction, and production workflows designed to capture project-defined feature classes. Impervious surface features were mapped according to project thresholds for buildings, roads, driveways, parking areas, sidewalks, pavement, swimming pools, paved recreation surfaces, and bridges. Advanced transportation features were mapped to represent lane and roadway elements including turning lanes, through lanes, shoulders, bike lanes, road features, sidewalks, and crosswalks where visible and meeting project capture criteria.
Extracted features were reviewed and refined to improve consistency with project specifications. Attribution was applied and validated for mapped features, including classification and width attribution where applicable. Geometry was adjusted as needed to improve feature representation, continuity, and consistency across the statewide dataset.
Quality assurance and quality control procedures were performed on the statewide dataset prior to final delivery. Review activities included checks for classification consistency, attribution completeness, geometry validity, logical consistency, and adherence to project capture specifications. Identified issues were corrected during production review and final dataset compilation.
Polyline feature file representing road centerlines, sidewalk centerlines, and crosswalk centerlines across the State of Connecticut, extracted from 2023 source imagery. WIDTH measurements are in meters on a mean basis per segment. Fields: FID (internal feature identifier assigned by GIS software); Shape (polyline geometry); CateTitle (feature classification - see values below); WIDTH (mean width of the feature segment in meters). CateTitle values - road: paved roadway centerline captured from edge of curb, minimum 8 ft wide; sidewalk: paved pedestrian path centerline parallel to a street, includes public and private sidewalks, minimum 3 ft wide; continential_crosswalk: crosswalk marked with thick horizontal stripes extending across the road; standard_crosswalk: crosswalk marked by two parallel lines; ladder_crosswalk: crosswalk combining parallel lines with horizontal stripes between them; mid_block_crosswalk: crosswalk at a mid-block location rather than at an intersection; other_crosswalk: crosswalk markings not fitting the continental, standard, or ladder categories. Crosswalks as visible from source imagery.
Producer defined
Polyline feature file representing individual lane-level centerlines for advanced transportation features across the State of Connecticut, extracted from 2023 source imagery. WIDTH measurements are in meters on a mean basis per segment. Fields: FID (internal feature identifier assigned by GIS software); Shape (polyline geometry); CateTitle (feature classification - see values below); WIDTH (mean width of the feature segment in meters). CateTitle values - through_lane: lane running uninterrupted along the roadway without diversion into turning or exit lanes, segmented at intersections, greater than 8 ft wide; left_through_lane: through lane on the left side of the roadway, segmented at intersections, greater than 8 ft wide; right_through_lane: through lane on the right side of the roadway, segmented at intersections, greater than 8ft wide; left_turn_lane: lane designated for left turns on the far left or center of the road, interpreted to begin at widening of street path or start of designated painted area, greater than 8 ft wide; right_turn_lane: lane designated for right turns on the far right of the roadway, interpreted to begin at widening of street path or start of designated painted area, greater than 8 ft wide; left_right_lane: lane designated for both left and right turns, greater than 8 ft wide; middle_turn_lane: lane positioned in the center of the roadway designated for turning movements, greater than 8 ft wide; slip_turn_lane: dedicated turning lane allowing vehicles to merge into cross-street traffic without stopping, greater than 8ft wide; shoulder: emergency stopping lane on the far edge of the road outside through lanes, not connected to intersections or exits, greater than 8 ft wide; bike_lane_centerline: lane designated exclusively for bicycle traffic based on visual interpretation of imagery, sharrows are classified as through lanes not bike lanes, greater than 8ft wide.
Producer defined
Polygon feature file representing impervious surface land cover across the State of Connecticut, extracted from 2023 source imagery. Fields: FID (internal feature identifier assigned by GIS software); Shape (polygon geometry); CateTitle (feature classification - see values below). CateTitle values - bridge: elevated driving surface separated from terrain level, does not include walking paths, greater thab 8ft wide and 50ft long; building: polygonal ground footprint of a structure derived from roofline and wall facade, minimum 100 sq ft; driveway: paved surface from edge of curb to a structure,, sidewalk takes priority where overlap occurs, greater than 8ft wided and 50ft long; parking: paved surface with visible parking lanes, minimum 500 sq ft; paved_sport_ground: paved recreational area such as a tennis court or running track, as visible from source imagery; pavement: paved surface not captured by a more specific impervious class, minimum 100 sq ft; railway: railway infrastructure visible from source imagery; road: paved roadway surface from edge of curb to edge of curb, minimum 50 ft long and 8 ft wide; sidewalk: paved pedestrian path parallel to a street, includes public and private sidewalks, takes priority over driveway and other paved surfaces, greater than 500 sq ft; swimming_pool: in-ground open water on residential or commercial property, minimum 100 sq ft; unpaved_sportsground: unpaved recreational area such as a baseball diamond or soccer field, as visible from source imagery.
Producer defined
This dataset package contains three separate feature files: a Land file of polygon features representing impervious surface land cover classes, a Lane file of polyline features representing individual lane-level centerlines, and a Road file of polyline features representing road centerlines, sidewalk centerlines, and crosswalk centerlines The Road and Lane layers additionally include a WIDTH field with measurements in meters provided on a mean basis per segment. Feature capture and attribution were performed according to class-specific interpretation rules and minimum mapping specifications defined in the project Scope of Work.