Mapping Technicians

Produce or update overlay maps to show information boundaries, water locations, or topographic features on various base maps or at different scales.

AI: Fully automatable - Given source data, automated GIS and cartographic tools can produce and update overlay maps across base maps and scales end-to-end.

Determine scales, line sizes, or colors to be used for hard copies of computerized maps, using plotters.

AI: Fully automatable - Cartographic styling engines and automated layout/plotting systems can determine appropriate scales, line weights, and colors for hard-copy outputs reliably.

Identify and compile database information to create maps in response to requests.

AI: Fully automatable - AI can query, join, clean, and compile spatial database information to create maps on request when the necessary data sources are accessible.

Calculate latitudes, longitudes, angles, areas, or other information for mapmaking, using survey field notes or reference tables.

AI: Fully automatable - Computing latitudes, longitudes, angles, and areas from survey notes or reference tables is a deterministic calculation that AI/software can perform fully.

Compute and measure scaled distances between reference points to establish relative positions of adjoining prints and enable the creation of photographic mosaics.

AI: Fully automatable - Computing scaled distances and relative positions between reference points is straightforward geometry that current software and AI can perform accurately and automatically.

Trace contours or topographic details to generate maps that denote specific land or property locations or geographic attributes.

AI: Fully automatable - Automated processing from DEMs, raster-to-vector extraction, and georeferencing reliably trace contours and create map layers without human intervention in typical cases.

Lay out and match aerial photographs in sequences in which they were taken and identify any areas missing from photographs.

AI: Fully automatable - Computer vision and geospatial software can now automatically sequence aerial photos using metadata and image-matching and detect coverage gaps reliably for operational use.

Trim, align, and join prints to form photographic mosaics, maintaining scaled distances between reference points.

AI: Fully automatable - Image-stitching, photogrammetric alignment, and control-point–based scaling are well automated and can trim, align, and join prints into accurate mosaics in most workflows.

Form three-dimensional images of aerial photographs taken from different locations, using mathematical techniques and plotting instruments.

AI: Fully automatable - Photogrammetry and structure-from-motion algorithms can fully generate three-dimensional models from multi-view aerial imagery using established mathematical techniques.

Check all layers of maps to ensure accuracy, identifying and marking errors and making corrections.

AI: Partial - AI can automatically detect layer inconsistencies and propose corrections but ambiguous cases and required field validation generally need human judgment.

Design or develop information databases that include geographic or topographic data.

AI: Partial - AI tools can generate geospatial database schemas, ETL pipelines, and populate spatial stores, but gathering requirements and handling complex organizational constraints typically requires human oversight.

Monitor mapping work or the updating of maps to ensure accuracy, the inclusion of new or changed information, or compliance with rules and regulations.

AI: Partial - AI can monitor updates, run validation rules, and flag likely errors or noncompliance, yet final compliance determinations and nuanced decisions often need human review.

Analyze aerial photographs to detect and interpret significant military, industrial, resource, or topographical data.

AI: Partial - Computer-vision models can detect many features in aerial imagery, but interpreting strategic significance (military, industrial, resource) requires contextual and expert analysis beyond full automation.

Enter Global Positioning System (GPS) data, legal deeds, field notes, or land survey reports into geographic information system (GIS) workstations so that information can be transformed into graphic land descriptions, such as maps or drawings.

AI: Partial - AI can parse, geocode, and import GPS points and structured survey data into GIS, but ambiguous field notes, deed language, and legal nuances require human verification.

Answer questions and provide information to the public or to staff members regarding assessment maps, surveys, boundaries, easements, property ownership, roads, zoning, or similar matters.

AI: Partial - Chatbots and retrieval systems can answer routine public and staff questions about maps and records, but advisory, contested, or legally sensitive responses require human oversight.

Research and combine existing property information to describe property boundaries in relation to adjacent properties, taking into account parcel splits, combinations, or land boundary adjustments.

AI: Partial - Automated reconciliation of parcel records can assist heavily, but resolving historical inconsistencies and legally describing boundaries relative to adjacent properties generally needs expert/legal interpretation.

Compare topographical features or contour lines with images from aerial photographs, old maps, or other reference materials to verify the accuracy of their identification.

AI: Partial - AI can align and compare contour data with aerial imagery and historical maps to flag discrepancies, but complex contextual judgment and degraded or ambiguous sources still require human validation.

Train staff members in duties such as tax mapping, the use of computerized mapping equipment, or the interpretation of source documents.

AI: Partial - AI can deliver training materials, simulations, and guided tutorials for mapping tools and document interpretation, but hands-on mentorship and handling of edge-case tacit knowledge remain human-led.

Redraw or correct maps, such as revising parcel maps, to reflect tax code area changes, using information from official records or surveys.

AI: Partial - Redrawing maps from records and surveys can be largely automated, but ensuring legal compliance, resolving ambiguous source conflicts, and certifying revisions typically require human judgment.

Research resources such as survey maps or legal descriptions to verify property lines or to obtain information needed for mapping.

AI: Partial - AI can search, extract, and cross-reference survey maps and legal descriptions to assemble candidate property lines, but nuanced legal interpretation and authoritative verification usually need human review.

Produce presentations of surface or mineral ownership layers by interpreting legal survey plans.

AI: Partial - AI can parse survey plans and generate ownership-layer visualizations, yet interpreting complex legal survey language and resolving ownership ambiguities needs expert review.

Create survey description pages or historical records related to the mapping activities or specifications of section plats.

AI: Partial - AI can draft survey description pages and synthesize historical records from existing data and templates but cannot fully guarantee legal/technical accuracy or replace expert judgment without human validation.

Identify, research, and resolve anomalies in legal land descriptions, referring issues to title or survey experts as appropriate.

AI: Partial - AI can detect and research anomalies in land descriptions and suggest likely resolutions, but final resolution and escalation to title or survey experts require human decision-making and legal authority.

Complete detailed source and method notes describing the location of routine or complex land parcels.

AI: Partial - AI can generate detailed source and method notes from datasets and standard procedures but often needs human oversight for complex parcel boundaries and legal precision.

Supervise or coordinate activities of workers engaged in plotting data, drafting maps, or producing blueprints, photostats, or photographs.

AI: Partial - Automation can assist with coordination, scheduling, and quality-monitoring, but supervisory responsibilities that require interpersonal judgment and on-site decisions remain human-led.