{"schemaVersion":"1.0","exportedAt":"2026-05-15T12:38:26.784Z","occupation":{"soc":"19-2099.01","title":"Remote Sensing Scientists and Technologists","group":"Life, Physical & Social Science","sector":"54","jobZone":4,"jobZoneInferred":false},"framework":{"version":"v.26.05","description":"","contextCovered":"This framework covers the full spectrum of remote sensing science and technology practice — from supervised data processing and GIS analysis in laboratory and field settings to strategic leadership of enterprise geospatial programs across environmental, governmental, and commercial contexts.","levels":{"emerging":{"label":"Emerging","statements":["Remote sensing datasets — retrieve and organize under direct supervision using established file management protocols in a geospatial lab environment.","Image analysis software — apply basic functions to load and display aerial or satellite imagery under the guidance of a senior scientist.","Geospatial data documentation — compile and maintain metadata records following standardized templates on assigned project files.","Statistical analysis tools — execute pre-configured scripts to summarize remote sensing data outputs under direct oversight.","Raw imagery files — format and convert to required project specifications using graphic or photo imaging software with supervisor direction.","GIS platform basics — import vector and raster datasets and verify coordinate reference systems under structured guidance.","Project status updates — draft written summaries of data collection progress using established report templates for team review.","Equipment requirements — participate in team discussions about sensor platforms and data collection needs under the direction of a project lead.","Land cover classification workflows — follow documented procedures to assign spectral classes to satellite imagery with close supervision.","External geospatial data sources — locate and download publicly available datasets to support integration tasks as directed by senior staff."]},"developing":{"label":"Developing","statements":["Remote sensing data pipelines — manage end-to-end processing of aerial and satellite imagery with reduced oversight on routine project deliverables.","GIS and image analysis software — perform multi-layer spatial analyses and produce derivative data products for standard land cover mapping projects.","Ancillary geospatial datasets — integrate elevation, census, and environmental data into remote sensing projects to enrich analytical outputs.","Geospatial data repositories — maintain organized, version-controlled archives and associated documentation across multiple concurrent projects.","Image compilation workflows — apply radiometric and geometric correction procedures to improve imagery quality and analytical utility.","Project reports and presentations — prepare clear written reports and slide decks summarizing geospatial findings for internal stakeholders.","Statistical analysis software — apply classification algorithms and accuracy assessment methods to evaluate remote sensing map outputs.","Team communications — contribute technical input during project planning discussions, clearly conveying equipment and methodology requirements.","Database management systems — design and query geospatial databases to store, retrieve, and manage large volumes of sensor-derived data.","Cloud-based processing platforms — configure and run batch processing jobs on cloud infrastructure to handle moderate-scale imagery datasets."]},"proficient":{"label":"Proficient","statements":["Complex remote sensing datasets — design and execute advanced analytical workflows autonomously, deriving actionable insights across multispectral, hyperspectral, and LiDAR data types.","Critical project decisions — apply expert judgment to select appropriate sensors, platforms, and analytical methodologies for non-routine environmental monitoring challenges.","Multi-source geospatial integration — fuse satellite, airborne, and ground-based datasets seamlessly into unified spatial models for high-stakes deliverables.","Advanced classification systems — develop and validate supervised and unsupervised machine learning models for land cover and change detection mapping.","Geospatial data quality assurance — establish and enforce rigorous accuracy assessment protocols to ensure analytical integrity across the full project lifecycle.","Technical reports and presentations — author peer-quality written analyses and deliver compelling presentations of geospatial results to diverse technical audiences.","Systems analysis — evaluate the performance of remote sensing data collection systems against project objectives and recommend operational improvements.","Expert system and analytical software — configure and customize scientific toolsets to solve complex geospatial problems without external assistance.","Cross-disciplinary data synthesis — incorporate biology, physics, and engineering knowledge domains to interpret remote sensing signals in applied environmental contexts.","Project methodology design — lead technical scoping discussions with colleagues to define data acquisition strategies, processing chains, and success criteria."]},"advanced":{"label":"Advanced","statements":["Organizational remote sensing strategy — set the technical direction and standards for large-scale geospatial programs across multiple projects and client portfolios.","Innovation in analytical methods — pioneer the adoption of emerging sensor technologies and machine learning frameworks to advance the organization's remote sensing capabilities.","Workforce development — mentor and evaluate junior scientists and technologists, designing learning strategies that build technical depth across the team.","Enterprise geospatial infrastructure — lead the design and governance of cloud-based data management and processing architectures supporting organization-wide operations.","Executive-level reporting — communicate complex remote sensing findings and strategic recommendations to senior leadership, government agencies, and external partners.","Cross-sector partnerships — negotiate and manage collaborative agreements with satellite data providers, research institutions, and industry clients to expand mission scope.","Systems evaluation at scale — assess the effectiveness of entire remote sensing programs against scientific and operational benchmarks, driving evidence-based program evolution.","Research agenda leadership — define and champion applied research priorities that align remote sensing science with emerging societal and environmental challenges.","Ethical and policy frameworks — establish organizational standards for data integrity, geospatial data sharing, and responsible use of sensitive imagery products.","Operations analysis and resource planning — oversee budgeting, technology procurement, and staffing allocations to ensure sustained capability and mission readiness across the remote sensing enterprise."]}}},"sources":{"onet":"v30.2 (CC BY 4.0)","crosswalk":"https://skillscrosswalk.com","generator":"LER.me"},"attribution":"© EBSCOed"}