Remote Sensing Scientists and Technologists

Life, Physical, and Social Science Occupations

O*NET-SOC 代码: 19-2099.01

Apply remote sensing principles and methods to analyze data and solve problems in areas such as natural resource management, urban planning, or homeland security. May develop new sensor systems, analytical techniques, or new applications for existing systems.

数据来源: BLS发布时间: 2026-08
高· 相对
低四级相对区间很高
职业群单位数值
尺度 · 母数 · 来源
四级相对类别（低 / 中等 / 高 / 很高）
以BLS就业预测表中831个细分职业为基数。取值按 NEM（全国就业矩阵）代码给定，因此共用同一 NEM 代码的职业得到相同分档
来源数据集（XLSX 文件下载）
数据来源: Anthropic发布时间: 2026-03
0.038
0.000此处所载数值的范围0.745
职业群单位数值
尺度 · 母数 · 来源
观测暴露度指数，按发布原值0–1
以O*NET任务映射为基准
按 SOC 2018 职业发布的数值；具有相同 SOC 2018 代码的所有 O*NET 职业均显示此值
来源数据集（CSV 文件下载）
数据来源: OpenAI发布时间: 2023
0.446
0.000此处所载数值的范围0.844
尺度 · 母数 · 来源
人工评分β，按发布原值0–1
以O*NET任务映射为基准
来源数据集（CSV 文件下载）

该来源发布的是什么性质的数值

BLS的类别是相对排位而非绝对水平，也不是一手测量：它把多项已发表研究给出的职业百分位排名归并为四个等级。它不是就业或工资预测，不是采用概率，也不区分自动化与增强。

Task-level exposure

显示隐藏的 21 项工作

已评分任务 24 项 · β ≥ 0.5 的任务 22 项（91.7%）

β = 直接暴露（E1）+ 0.5 × 借助工具时的暴露（E2），依据原始代码库的定义。

原始单位：O*NET 27.2 任务 → O*NET 31.0 职业代码
所有已评分任务均在 O*NET 31.0 任务列表中。

来源: OpenAI "GPTs are GPTs" exposure rubric
版本: gh-main-0471612
许可: MIT License, Copyright (c) 2024 OpenAI

Task (O*NET 20.1)	Claude.aiRaw / share %	APIRaw / share %
Compile and format image data to increase its usefulness. 19-2099.01	0.0270100.0	0.088992.0
Manage or analyze data obtained from remote sensing systems to obtain meaningful results.	—0	0.00424.4
Organize and maintain geospatial data and associated documentation.	—0	0.00353.6

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
Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS). O*NET Task ID 18256	0.5
Develop or build databases for remote sensing or related geospatial project information. O*NET Task ID 18257	0.5
Integrate other geospatial data sources into projects. O*NET Task ID 18258	0.5
Prepare or deliver reports or presentations of geospatial project information. O*NET Task ID 18259	0.5
Organize and maintain geospatial data and associated documentation. O*NET Task ID 18260	0.5
Process aerial or satellite imagery to create products such as land cover maps. O*NET Task ID 18261	0.5
Design or implement strategies for collection, analysis, or display of geographic data. O*NET Task ID 18262	0.5
Direct all activity associated with implementation, operation, or enhancement of remote sensing hardware or software. O*NET Task ID 18263	0.5
Collect supporting data, such as climatic or field survey data, to corroborate remote sensing data analyses. O*NET Task ID 18264	0.5
Compile and format image data to increase its usefulness. O*NET Task ID 18265	0.5
Conduct research into the application or enhancement of remote sensing technology. O*NET Task ID 18266	0.5
Develop automated routines to correct for the presence of image distorting artifacts, such as ground vegetation. O*NET Task ID 18268	0.5
Develop new analytical techniques or sensor systems. O*NET Task ID 18269	0.5
Manage or analyze data obtained from remote sensing systems to obtain meaningful results. O*NET Task ID 18270	0.5
Monitor quality of remote sensing data collection operations to determine if procedural or equipment changes are necessary. O*NET Task ID 18271	0.5
Direct installation or testing of new remote sensing hardware or software. O*NET Task ID 18272	0.5
Attend meetings or seminars or read current literature to maintain knowledge of developments in the field of remote sensing. O*NET Task ID 18273	0.5
Recommend new remote sensing hardware or software acquisitions. O*NET Task ID 18275	0.5
Set up or maintain remote sensing data collection systems. O*NET Task ID 18276	0.5
Train technicians in the use of remote sensing technology. O*NET Task ID 18277	0.5
Apply remote sensing data or techniques, such as surface water modeling or dust cloud detection, to address environmental issues. O*NET Task ID 19773	0.5
Use remote sensing data for forest or carbon tracking activities to assess the impact of environmental change. O*NET Task ID 19774	0.5
再显示 12 项工作 ▾收起 ▴

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

O*NET 31.0 全部任务（24 项）

本职业在 O*NET 31.0 中的全部任务（英文原文；任务类型为核心或补充）。暴露值不列在此清单中，而在上方表格里，位于各来源所用 O*NET 版本的任务表述旁。

任务（O*NET 31.0）	类型
Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS).	核心
Develop or build databases for remote sensing or related geospatial project information.	核心
Integrate other geospatial data sources into projects.	核心
Prepare or deliver reports or presentations of geospatial project information.	核心
Organize and maintain geospatial data and associated documentation.	核心
Process aerial or satellite imagery to create products such as land cover maps.	核心
Design or implement strategies for collection, analysis, or display of geographic data.	核心
Direct all activity associated with implementation, operation, or enhancement of remote sensing hardware or software.	核心
Collect supporting data, such as climatic or field survey data, to corroborate remote sensing data analyses.	核心
Compile and format image data to increase its usefulness.	核心
Conduct research into the application or enhancement of remote sensing technology.	核心
Discuss project goals, equipment requirements, or methodologies with colleagues or team members.	核心
Develop automated routines to correct for the presence of image distorting artifacts, such as ground vegetation.	核心
Develop new analytical techniques or sensor systems.	核心
Manage or analyze data obtained from remote sensing systems to obtain meaningful results.	核心
Monitor quality of remote sensing data collection operations to determine if procedural or equipment changes are necessary.	核心
Direct installation or testing of new remote sensing hardware or software.	核心
Attend meetings or seminars or read current literature to maintain knowledge of developments in the field of remote sensing.	核心
Participate in fieldwork.	核心
Recommend new remote sensing hardware or software acquisitions.	核心
Set up or maintain remote sensing data collection systems.	核心
Train technicians in the use of remote sensing technology.	核心
Apply remote sensing data or techniques, such as surface water modeling or dust cloud detection, to address environmental issues.	核心
Use remote sensing data for forest or carbon tracking activities to assess the impact of environmental change.	核心

Anthropic「What work can robots do?」2026-09

0.07/ 3· 机器人暴露指数

0 不可3 非结构化环境

尺度 · 母数 · 来源

对每项体力任务，按已实际部署、销售或演示的机器人能够完成它的环境评定 0–3 级（0 不可 · 1 围栏式机器单元、灌装线等机器人专用设施 · 2 医院药房、集装箱港口等受管理的设施 · 3 私人住宅、建筑工地等非结构化环境），再按工作时间占比求平均

以该职业 O*NET 29.3 任务中的体力任务为准

等级与时间占比由 Anthropic 使用 Claude Opus 5（网络搜索）估算（截至 2026 年）。

来源数据集

机器人暴露指数与本站的 AI 暴露度是不同的指标，不能相加或相互比较。该指数不代表实际采用情况或成本竞争力，0 也包括没有体力任务的职业。

每项体力任务的等级

机器人环境等级（E0–E3）

E0 机器人不可详情
评定为已实际部署、销售或演示的机器人即使在机器人专用设施中也无法完成
E1 机器人专用设施详情
评定为可在围绕机器搭建的设施中完成，例如围栏式机器单元或灌装线
E2 受管理的设施详情
评定为可在由机构按工作标准维护的人类工作设施中完成，例如医院药房或集装箱港口
E3 非结构化环境详情
评定为可在没有机构按工作标准维护的环境中完成，例如私人住宅或建筑工地

仅列出被归类为体力任务的任务；其他任务在来源中没有等级。

任务（O*NET 29.3）	机器人环境等级
Participate in fieldwork.	E3 非结构化环境
Set up or maintain remote sensing data collection systems.	E0 机器人不可

就业展望（BLS）

这些数值属于整个 SOC 19-2099 组（Physical scientists, all other），并非仅属于该 O*NET 职业。

就业人数，2025: 27K
预计就业人数，2035: 27K
变化 (2025–35): +2.1%
年薪中位数，2025: $122,570
入职通常所需学历: Bachelor's degree

最低 $30,890BLS EP 2025–35 中 825 个细分职业的工资中位数范围最高 $559,030

来源: U.S. Bureau of Labor Statistics, Employment Projections 2025–35 — Employment by detailed occupation, 2025 and projected 2035

韩国职业分类关联（KSCO）

来自 AI Changing Work 制作的 Korea Occupation Direct Crosswalk v1.1 当前版本的关联。关系值从 O*NET-SOC 职业一侧解读。

KSCO 代码	KSCO 名称	关系	状态
23162	사진측량 및 원격탐사 분석가	范围相同	已确认

关系与状态的定义(kr-direct v1.1)

ESCO 职业词汇

以下每一项都是在已公开的ESCO-O*NET Crosswalk（第 1 版，2022 年）中与本职业逐项对应的。对应类型出自该对照表；表述出自 AI Changing Work。

geographerESCO 2632.5有重叠，但不相同
Geographers are scholars who study human and physical geography. Depending on their specialisation, they study political, economical and cultural aspects of humanity contained within human geography. Moreover, they study land formations, soils, natural frontiers, and water flows contained in physical geography.
remote sensing technicianESCO 3111.13有重叠，但不相同
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.
seismologistESCO 2114.1.10有重叠，但不相同
Seismologists study the movement of tectonic plaques in the Earth which causes the propagation of seismic waves and earthquakes. They study and observe the various sources causing earthquakes such as volcanic activity, atmospheric phenomena, or the behaviour of oceans. They provide their scientific observations to prevent dangers in construction and infrastructure.

来源: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)

许可: CC BY 4.0 (EU Reuse Notice)

查看原文

ESCO reuse terms and the modification notice are in Credits.

法国职业分类关联（ROME）

本职业与 ROME 4.0 职业条目（fiche）之间的关联，由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。标为「暂定」的关联仅凭同一模型系列（Claude）两位判定者的判定采纳，或对其判定适用运营方规则后采纳，因此其依据弱于已确认的关联。

ROME 代码	ROME 名称（法语）	关系
M1808	Cartographe	相关，但不对应
M1895	Géomaticien / Géomaticienne	相关，但不对应

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)

西班牙职业分类关联（CNO-11）

本职业与 CNO-11 职业之间的关联，由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。

CNO-11 代码	CNO-11 名称（西班牙语）	关系
2414	Geólogos y geofísicos	相关，但不对应
2454	Ingenieros geógrafos y cartógrafos	相关，但不对应
2821	Sociólogos, geógrafos, antropólogos, arqueólogos y afines	相关，但不对应

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)

德国职业分类关联（KldB）

本职业与 KldB 职业之间的关联，由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。

KldB 代码	KldB 名称（德语）	关系
43144	Berufe in der Geoinformatik - hoch komplexe Tätigkeiten	有重叠，但不相同
42134	Berufe in der Geografie - hoch komplexe Tätigkeiten	相关，但不对应

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)

日本职业分类关联（JSCO）

本职业与 JSCO 职业之间的关联，由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。

JSCO 代码	JSCO 名称（日语）	关系
051	自然科学系研究者	相关，但不对应
093	測量技術者	相关，但不对应

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)

本页数据的来源与许可，以及 AI Changing Work 的修改与翻译说明：致谢与来源