{ "culture": "en-US", "name": "", "guid": "", "catalogPath": "", "snippet": "This dataset represents the results of the October 2024 pavement condition survey performed for the city of Gaithersburg, MD. The data includes pavement surface condition indices derived from high-resolution Laser Crack Measurement System (LCMS-2) technology. The results provide quantitative assessments intended for use in pavement management, maintenance prioritization, and network-level reporting.", "description": "

Attribute Definitions<\/SPAN><\/P>

GISID<\/SPAN><\/SPAN><\/P>

Unique identifier for the roadway segment from the client GIS network.<\/SPAN><\/SPAN><\/P>

FunCL<\/SPAN><\/SPAN><\/P>

Functional classification of the roadway segment (e.g., Arterial, Collector, Local).<\/SPAN><\/SPAN><\/P>

PaveType<\/SPAN><\/SPAN><\/P>

Pavement surface type (e.g., Asphalt, PCC, Composite).<\/SPAN><\/SPAN><\/P>

Pavement_Cndtn_Index<\/SPAN><\/SPAN><\/P>

Final delivered PCI score for the roadway segment (0\u2013100 scale).<\/SPAN><\/SPAN><\/P>

CPCI<\/SPAN><\/P>

PCI aged to Easy Street Analysis start date of 7/1/2026 using deterioration models.<\/SPAN><\/P>

ProjectID<\/SPAN><\/SPAN><\/P>

Unique identifier for the improvement project or group of segments bundled for planning.<\/SPAN><\/SPAN><\/P>

Project_Current_PCI<\/SPAN><\/P>

Area-weighted PCI for the full grouped project, used to determine treatment and prioritization.<\/SPAN><\/SPAN><\/P>

Rehab_Activity<\/SPAN><\/SPAN><\/P>

Recommended treatment or rehabilitation strategy (e.g., Mill & Overlay, Microsurface, Crack Seal, Reconstruct).<\/SPAN><\/SPAN><\/P>

Whole_Project_Cost<\/SPAN><\/SPAN><\/P>

Total estimated costs for all segments included within the project group.<\/SPAN><\/SPAN><\/P>

Collected_PCI<\/SPAN><\/SPAN><\/P>

Raw or directly computed PCI derived from LCMS data prior to grouping or adjustments.<\/SPAN><\/SPAN><\/P>

Notes<\/SPAN><\/SPAN><\/P>

  • PCI values follow <\/SPAN><\/SPAN>ASTM D6433<\/SPAN><\/SPAN> methodology.<\/SPAN><\/SPAN><\/P><\/LI><\/UL>

    Use Limitations<\/SPAN><\/SPAN><\/P>

    Recommended rehabilitation activities and project groupings are <\/SPAN><\/SPAN>planning-level outputs<\/SPAN><\/SPAN> and should be validated through field review before final design or budgeting.<\/SPAN><\/SPAN><\/P>

    Pavement Condition Index (PCI) values represent surface condition at the <\/SPAN><\/SPAN>time of survey<\/SPAN><\/SPAN> and may not reflect subsequent maintenance or deterioration.<\/SPAN><\/SPAN><\/P>

    <\/P><\/DIV><\/DIV><\/DIV>", "summary": "This dataset represents the results of the October 2024 pavement condition survey performed for the city of Gaithersburg, MD. The data includes pavement surface condition indices derived from high-resolution Laser Crack Measurement System (LCMS-2) technology. The results provide quantitative assessments intended for use in pavement management, maintenance prioritization, and network-level reporting.", "title": "Pavement Condition and Management Plan Dataset - Gaithersburg, MD - 2025", "tags": [ "Pavement Condition Data" ], "type": "", "typeKeywords": [], "thumbnail": "", "url": "", "minScale": 150000000, "maxScale": 5000, "spatialReference": "", "accessInformation": "Data collection and processing were performed by ICC-IMS using LCMS-2 (Laser Crack Measurement System v2) technology.", "licenseInfo": "

    Recommended rehabilitation activities and project groupings are <\/SPAN>planning-level outputs<\/SPAN><\/SPAN> and should be validated through field review before final design or budgeting.<\/SPAN><\/SPAN><\/P>

    Pavement Condition Index (PCI) values represent surface condition at the <\/SPAN><\/SPAN>time of survey<\/SPAN><\/SPAN> and may not reflect subsequent maintenance or deterioration.<\/SPAN><\/SPAN><\/P><\/DIV><\/DIV><\/DIV>" }