Will AI replace Remote Sensing Scientists and Technologists?

Some of your tasks will be automated. People who use AI will have the edge.

Task exposure to today's AI

46/100

Moderate exposure

This is the occupation's typical task mix. Your own score can be up to 30 points higher or lower depending on how you work: routine share, people contact, judgment and how much you already use AI.

Get your personal score

Will AI replace Remote Sensing Scientists and Technologists?

Not entirely. Today's AI tools can take on about 46% of the typical work in this occupation, mostly: prepare or deliver reports or presentations of geospatial project information. The parts that stay human include: Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS).; Manage or analyze data obtained from remote sensing systems to obtain meaningful results.; Discuss project goals, equipment requirements, or methodologies with colleagues or team members..

People who learn to use AI for the automatable parts keep the edge. The 3-phase plan below shows where to start.

Which tasks AI can take on

The largest tasks in this occupation, their share of the working week, and how much of each today's AI tools can do.

TaskAutomatable

Prepare or deliver reports or presentations of geospatial project information. 75%

Process aerial or satellite imagery to create products such as land cover maps. 57%

Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS). 38%

Manage or analyze data obtained from remote sensing systems to obtain meaningful results. 38%

Integrate other geospatial data sources into projects. 35%

Discuss project goals, equipment requirements, or methodologies with colleagues or team members. 17%

+ 18 more tasks (48% of the week) in the full test.

Your human edge

Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS).
Manage or analyze data obtained from remote sensing systems to obtain meaningful results.
Discuss project goals, equipment requirements, or methodologies with colleagues or team members.

AI tools to try

ChatGPT / Claude for literature and writingAI research tools (e.g. Elicit, Consensus, Semantic Scholar)Copilot for data analysis code (Python, R)

Related roles

A 3-phase AI learning plan

Phase 1

Faster literature and writing

Literature search and summaries with AI, always checked against the papers.
Drafts of methods, reports and grant text.
Reference management and formatting.

Project

Use AI to summarize 20 papers on a sensor or index you work with, verify each claim against the source, and draft a 2-page methods section with formatted references in under 8 hours.

Phase 2

AI for data analysis

Analysis code in Python or R written with AI help.
Visualisation and statistics explained step by step.
Reproducibility: version code and prompts.

Project

Rebuild one past imagery analysis as an AI-assisted, version-controlled Python notebook with documented prompts, charts and accuracy statistics, and compare runtime against your original workflow.

Phase 3

AI as a research method

Classification, extraction or modelling with AI on your data.
Validate against human labels or ground truth.
Ethics, data protection and disclosure of AI use.

Project

Train an AI land cover classifier on one Sentinel-2 scene, validate it against 200 manually labelled ground-truth points, and report per-class accuracy plus an AI-use disclosure note.

Take the free 11-question test