{"schemaVersion":"1.0","exportedAt":"2026-05-15T12:38:26.615Z","occupation":{"soc":"19-4099.03","title":"Remote Sensing Technicians","group":"Life, Physical & Social Science","sector":"54","jobZone":4,"jobZoneInferred":false},"framework":{"version":"v.26.05","description":"","contextCovered":"This framework covers remote sensing technician practice in aerial, satellite, and ground-based geospatial data collection, processing, integration, and mapping project delivery environments across government, engineering, and environmental consulting sectors.","levels":{"emerging":{"label":"Emerging","statements":["Geospatial data collection technologies — identify and distinguish under direct supervision across aerial photography, LiDAR, and satellite sensor platforms in a laboratory or field training environment.","Remote sensing image files — retrieve and organize following established naming conventions and directory structures within a project data management system.","Image processing software interfaces — navigate and execute basic display adjustments under guidance to optimize visual presentation of raw remotely sensed imagery.","Data integrity checklists — apply to verify completeness and formatting accuracy of incoming remote sensing datasets before submission to senior technicians.","Scanned image tiles — import and align using image processing software under supervision to support photo mosaic assembly tasks on assigned mapping projects.","Technical project documentation — read and comprehend to extract sensor specifications, coordinate systems, and flight parameters relevant to assigned data collection tasks.","Raw digital imagery — manipulate brightness, contrast, and band combinations using standard software routines under direction to prepare data for preliminary interpretation.","Geospatial data integration workflows — follow step-by-step protocols to combine remotely sensed layers with GIS datasets in established project environments.","Project meeting notes and stakeholder requirements — listen actively and summarize key technical needs under supervision when supporting interdisciplinary project planning sessions.","Basic cartographic output — produce using map creation software following templates and specifications provided by senior remote sensing technicians or scientists."]},"developing":{"label":"Developing","statements":["Aerial and satellite imagery acquisition — coordinate and execute using LiDAR, multispectral, and thermal sensor platforms with reduced oversight on routine mapping assignments.","Remote sensing image analysis system outputs — verify integrity and accuracy independently by applying quality assurance procedures and resolving common data anomalies.","Remotely sensed data layers — integrate with GIS datasets routinely by selecting appropriate coordinate reference systems and resampling methods in analytical software environments.","Image enhancement routines — select and apply within graphics and analytical software to optimize classification accuracy and visual interpretation for standard project deliverables.","Photo mosaics of moderate geographic extents — build by merging scanned image datasets using image processing software with attention to seamline quality and radiometric consistency.","Raw flight and sensor data — manipulate in-field or post-mission to correct for atmospheric effects and geometric distortions in support of client deliverable timelines.","Mapping project requirements — contribute to planning discussions by presenting technical assessments of sensor suitability and data coverage to project teams and scientists.","Interdisciplinary project stakeholders — consult with surveyors, cartographers, and engineers routinely to clarify data needs and resolve minor technical discrepancies on active projects.","Analytical and scientific software tools — apply to perform quantitative analysis of remotely sensed indices such as NDVI or land surface temperature in environmental study contexts.","Technical reports summarizing data acquisition and processing results — write clearly and accurately for review by senior scientists and project managers on multimonth deliverable cycles."]},"proficient":{"label":"Proficient","statements":["Complex geospatial data collection campaigns — plan and execute autonomously across multiple sensor modalities including SAR, hyperspectral, and thermal systems in diverse field and aerial environments.","End-to-end data integrity validation pipelines — design and conduct across full remote sensing image analysis workflows, resolving non-routine errors in large-scale or time-sensitive projects.","Multi-source geospatial data fusion — perform independently by integrating satellite, airborne, and ground-truth datasets using advanced analytical software to produce authoritative spatial products.","Non-standard image processing challenges — diagnose and resolve by selecting and customizing processing routines within expert system and analytical software environments on high-complexity deliverables.","Large-area photo mosaics spanning regional extents — construct and quality-control by managing radiometric normalization, feathering, and seamline optimization across high-volume image datasets.","In-flight and ground-level raw data manipulation — execute with full autonomy to correct sensor artifacts and environmental interference, maintaining data fidelity under variable field conditions.","Mapping project architectures — develop from scope through delivery by defining sensor selection, flight planning parameters, processing workflows, and output specifications for interdisciplinary teams.","Remote sensing scientists, engineers, and external clients — consult with and advise proactively to align technical capabilities with project objectives, resolving scope and data quality conflicts.","Systems analysis of geospatial technology stacks — perform to evaluate performance gaps, recommend software or hardware upgrades, and optimize data pipelines across organizational projects.","Critical technical findings and methodology recommendations — communicate through written reports and oral presentations to scientific and non-technical audiences in regulatory or commercial project contexts."]},"advanced":{"label":"Advanced","statements":["Organizational remote sensing data acquisition strategy — set and govern by evaluating emerging satellite, UAV, and airborne sensor technologies against long-term programmatic and client portfolio needs.","Enterprise-level geospatial data integrity and governance frameworks — establish and maintain to ensure consistent accuracy standards across all remotely sensed products delivered by the organization.","Cross-disciplinary geospatial data integration standards — define and enforce to guide technicians and scientists in fusing remote sensing outputs with GIS, survey, and engineering datasets at scale.","Senior scientists, agency partners, and executive clients — advise at the strategic level by translating complex remote sensing capabilities into actionable intelligence for high-stakes decision making.","Organization-wide image processing and product delivery pipelines — architect by deploying scalable analytical software solutions and workflow automation that elevate team throughput and product quality.","Advanced mapping project portfolios — lead from inception through delivery by directing resource allocation, managing cross-functional teams, and ensuring on-time, on-budget execution of multi-project programs.","Emerging remote sensing methodologies — champion by conducting applied research, evaluating new tools, and institutionalizing best practices that advance organizational technical capabilities.","Talent development programs for remote sensing technicians — design and mentor through structured competency pathways, peer review systems, and coaching that build junior-to-senior capability pipelines.","Interagency and industry partnerships — cultivate and lead by representing the organization in technical working groups, standards bodies, and collaborative research initiatives at the national or international level.","Complex problem solving frameworks for non-routine geospatial challenges — formulate and apply at the organizational level, directing teams in resolving systemic data quality, policy, or technology adoption barriers."]}}},"sources":{"onet":"v30.2 (CC BY 4.0)","crosswalk":"https://skillscrosswalk.com","generator":"LER.me"},"attribution":"© EBSCOed"}