Remote Sensing Technicians
Life, Physical, and Social Science Occupations- O*NET-SOC code
- 19-4099.03
Apply remote sensing technologies to assist scientists in areas such as natural resources, urban planning, or homeland security. May prepare flight plans or sensor configurations for flight trips.
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.096
0.000Range of values carried here0.745Group-level value
Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.26· 2 ISCO-08 groups
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
ILO value for each linked ISCO-08 group
- ISCO-08 3111Chemical and Physical Science Technicians0.26
- ISCO-08 3119Physical and Engineering Science Technicians Not Elsewhere Classified0.26
Task-level exposure
Exposed tasks only22 rated tasks · 22 tasks with β ≥ 0.5 (100.0%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- 1 rated task is not in the O*NET 31.0 task list; its score is kept as published for O*NET 27.2.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 20.1) | Claude.aiRaw / share % |
|---|---|
Prepare documentation or presentations, including charts, photos, or graphs.19-4099.03 | 0.035343.2 |
Document methods used and write technical reports containing information collected.19-4099.03 | 0.024329.7 |
Develop specialized computer software routines to customize and integrate image analysis.19-4099.03 | 0.013516.4 |
Calibrate data collection equipment.19-4099.03 | 0.008710.7 |
| Not observed on any surface — 18 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | |
Participate in the planning or development of mapping projects. | —0 |
Verify integrity and accuracy of data contained in remote sensing image analysis systems. | —0 |
Merge scanned images or build photo mosaics of large areas, using image processing software. | —0 |
Integrate remotely sensed data with other geospatial data. | —0 |
Consult with remote sensing scientists, surveyors, cartographers, or engineers to determine project needs. | —0 |
Adjust remotely sensed images for optimum presentation by using software to select image displays, define image set categories, or choose processing routines. | —0 |
Manipulate raw data to enhance interpretation, either on the ground or during remote sensing flights. | —0 |
Collect geospatial data, using technologies such as aerial photography, light and radio wave detection systems, digital satellites, or thermal energy systems. | —0 |
Maintain records of survey data. | —0 |
Collect verification data on the ground, using equipment such as global positioning receivers, digital cameras, or notebook computers. | —0 |
Operate airborne remote sensing equipment, such as survey cameras, sensors, or scanners. | —0 |
Monitor raw data quality during collection and make equipment corrections as necessary. | —0 |
Evaluate remote sensing project requirements to determine the types of equipment or computer software necessary to meet project requirements, such as specific image types or output resolutions. | —0 |
Develop or maintain geospatial information databases. | —0 |
Correct raw data for errors due to factors such as skew or atmospheric variation. | —0 |
Collaborate with agricultural workers to apply remote sensing information to efforts to reduce negative environmental impacts of farming practices. | —0 |
Collect remote sensing data for forest or carbon tracking activities involved in assessing the impact of environmental change. | —0 |
Provide remote sensing data for use in addressing environmental issues, such as surface water modeling or dust cloud detection. | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Maintain records of survey data.O*NET Task ID 16982 | 1.0 |
Document methods used and write technical reports containing information collected.O*NET Task ID 16983 | 1.0 |
Develop specialized computer software routines to customize and integrate image analysis.O*NET Task ID 16984 | 1.0 |
Participate in the planning or development of mapping projects.O*NET Task ID 16981 | 0.5 |
Collect verification data on the ground, using equipment such as global positioning receivers, digital cameras, or notebook computers.O*NET Task ID 16985 | 0.5 |
Verify integrity and accuracy of data contained in remote sensing image analysis systems.O*NET Task ID 16986 | 0.5 |
Prepare documentation or presentations, including charts, photos, or graphs.O*NET Task ID 16987 | 0.5 |
Operate airborne remote sensing equipment, such as survey cameras, sensors, or scanners.O*NET Task ID 16988 | 0.5 |
Monitor raw data quality during collection, and make equipment corrections as necessary.O*NET Task ID 16989 | 0.5 |
Merge scanned images or build photo mosaics of large areas, using image processing software.O*NET Task ID 16990 | 0.5 |
Integrate remotely sensed data with other geospatial data.O*NET Task ID 16991 | 0.5 |
Evaluate remote sensing project requirements to determine the types of equipment or computer software necessary to meet project requirements, such as specific image types or output resolutions.O*NET Task ID 16992 | 0.5 |
Develop or maintain geospatial information databases.O*NET Task ID 16993 | 0.5 |
Correct raw data for errors due to factors such as skew or atmospheric variation.O*NET Task ID 16994 | 0.5 |
Calibrate data collection equipment.O*NET Task ID 16995 | 0.5 |
Consult with remote sensing scientists, surveyors, cartographers, or engineers to determine project needs.O*NET Task ID 16996 | 0.5 |
Adjust remotely sensed images for optimum presentation by using software to select image displays, define image set categories, or choose processing routines.O*NET Task ID 16997 | 0.5 |
Manipulate raw data to enhance interpretation, either on the ground or during remote sensing flights.O*NET Task ID 16998 | 0.5 |
Collect geospatial data, using technologies such as aerial photography, light and radio wave detection systems, digital satellites, or thermal energy systems.O*NET Task ID 16999 | 0.5 |
Collaborate with agricultural workers to apply remote sensing information to efforts to reduce negative environmental impacts of farming practices.O*NET Task ID 19804 | 0.5 |
Collect remote sensing data for forest or carbon tracking activities involved in assessing the impact of environmental change.O*NET Task ID 19805 | 0.5 |
Provide remote sensing data for use in addressing environmental issues, such as surface water modeling or dust cloud detection.O*NET Task ID 19806 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
All O*NET 31.0 task statements (21)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Participate in the planning or development of mapping projects. | Core |
| Verify integrity and accuracy of data contained in remote sensing image analysis systems. | Core |
| Prepare documentation or presentations, including charts, photos, or graphs. | Core |
| Merge scanned images or build photo mosaics of large areas, using image processing software. | Core |
| Integrate remotely sensed data with other geospatial data. | Core |
| Consult with remote sensing scientists, surveyors, cartographers, or engineers to determine project needs. | Core |
| Adjust remotely sensed images for optimum presentation by using software to select image displays, define image set categories, or choose processing routines. | Core |
| Manipulate raw data to enhance interpretation, either on the ground or during remote sensing flights. | Core |
| Collect geospatial data, using technologies such as aerial photography, light and radio wave detection systems, digital satellites, or thermal energy systems. | Core |
| Maintain records of survey data. | Supplemental |
| Document methods used and write technical reports containing information collected. | Supplemental |
| Develop specialized computer software routines to customize and integrate image analysis. | Supplemental |
| Collect verification data on the ground, using equipment such as global positioning receivers, digital cameras, or notebook computers. | Supplemental |
| Monitor raw data quality during collection, and make equipment corrections as necessary. | Supplemental |
| Evaluate remote sensing project requirements to determine the types of equipment or computer software necessary to meet project requirements, such as specific image types or output resolutions. | Supplemental |
| Develop or maintain geospatial information databases. | Supplemental |
| Correct raw data for errors due to factors such as skew or atmospheric variation. | Supplemental |
| Calibrate data collection equipment. | Supplemental |
| Collaborate with agricultural workers to apply remote sensing information to efforts to reduce negative environmental impacts of farming practices. | — |
| Collect remote sensing data for forest or carbon tracking activities involved in assessing the impact of environmental change. | — |
| Provide remote sensing data for use in addressing environmental issues, such as surface water modeling or dust cloud detection. | — |
0.48/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
Robot environment tiers (E0–E3)
E0 noneDetails
Rated not doable by robots that have been deployed, sold or demonstrated, even in a purpose-built setting
E1 purpose-built robot settingsDetails
Rated doable in a setting built around the machine, such as a fenced machine cell or a bottling line
E2 structured facilitiesDetails
Rated doable in a human work facility that an institution keeps to a working standard, such as a hospital pharmacy or a container port
E3 unstructured settingsDetails
Rated doable in a setting that no institution keeps to a working standard, such as a private home or a construction site
Only tasks classified as physical are listed; other tasks have no tier in the source.
| Task (O*NET 29.3) | Robot environment tier |
|---|---|
| Collect geospatial data, using technologies such as aerial photography, light and radio wave detection systems, digital satellites, or thermal energy systems. | E2 structured facilities |
| Collect verification data on the ground, using equipment such as global positioning receivers, digital cameras, or notebook computers. | E3 unstructured settings |
| Monitor raw data quality during collection, and make equipment corrections as necessary. | E3 unstructured settings |
| Calibrate data collection equipment. | E1 purpose-built robot settings |
| Collect remote sensing data for forest or carbon tracking activities involved in assessing the impact of environmental change. | E2 structured facilities |
Occupation information
Employment outlook (BLS)
Values for the whole SOC 19-4099 group (Life, physical, and social science technicians, all other), not for this O*NET occupation alone.
- Employment, 2025
- 90K
- Projected employment, 2035
- 93K
- Change (2025–35)
- +4.4%
- Median annual wage, 2025
- $62,280
- Typical education needed for entry
- Associate's degree
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 23162 | 사진측량 및 원격탐사 분석가 | Same scope | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 3111Chemical and Physical Science Technicians
- ISCO-08 3119Physical and Engineering Science Technicians Not Elsewhere Classified
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- remote sensing technicianESCO 3111.13Same scope
Remote sensing technicians collect airborne data. They utilise equipment aimed for the collection of data and determination of geographical points in order to help in a variety of operations such as land conservation, urban planning, and military operations.
- hydrographic surveying technicianESCO 3111.5Overlapping, not the same
Hydrographic surveying technicians perform oceanographic and surveying operations in marine environments. They assist hydrographic surveyors, using specialised equipment to map and study underwater topography and morphology of bodies of water. They assist in the installation and deployment of hydrographic and surveying equipment and report about their work.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| M1808 | Cartographe | Related, not a match |
| M1895 | Géomaticien / Géomaticienne | Related, not a match |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 3121 | Técnicos en ciencias físicas y químicas | Related, not a match |
| 3129 | Otros técnicos de las ciencias físicas, químicas, medioambientales y de las ingenierías | Related, not a match |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 31223 | Berufe in der Kartografie - komplexe Spezialistentätigkeiten | Overlapping, not the sameprovisional |
| 31222 | Berufe in der Kartografie - fachlich ausgerichtete Tätigkeiten | Related, not a match |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 119 | その他の技術者 | Related, not a match |
| 093 | 測量技術者 | Related, not a matchprovisional |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources