Somewhat Resilient
Last Update: 7/31/2026
AI Resilience Score for Remote Sensing Scientist:
38.6%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
AI Resilience Report forRemote Sensing Scientists and Technologists
$122,570 median salary•2,000 annual openings•SOC Code: 19-2099.01
Remote Sensing Scientists and Technologists are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.
This career lands in "Somewhat Resilient" because AI is genuinely transforming a big chunk of the day-to-day work, especially the repetitive image processing and data labeling tasks that used to take teams of people many hours to complete. Tools like NASA's Prithvi model can now scan years of satellite data to map floods, monitor crops, and track environmental changes automatically, which means some entry-level tasks are being handled by machines.
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This career lands in "Somewhat Resilient" because AI is genuinely transforming a big chunk of the day-to-day work, especially the repetitive image processing and data labeling tasks that used to take teams of people many hours to complete. Tools like NASA's Prithvi model can now scan years of satellite data to map floods, monitor crops, and track environmental changes automatically, which means some entry-level tasks are being handled by machines.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreAnalysis of Current AI Resilience
Remote Sensing Scientist
Updated Quarterly
How is AI changing Remote Sensing Scientist jobs?
Remote sensing is one of the fields where AI is being used heavily right now — but mostly to help scientists, not replace them. The integration of artificial intelligence (AI) in remote sensing and satellite image processing has significantly transformed the field, offering advanced tools for data analysis, feature extraction, and environmental monitoring. A big shift is the rise of "foundation models [1]" — giant AI systems trained on huge satellite datasets.
NASA and IBM's open-source Prithvi Geospatial AI foundation model was recently demonstrated aboard two in-orbit platforms, making it the first geospatial foundation model deployed in orbit. Trained on 13 years' worth of data, Prithvi can facilitate a wide variety of Earth observation tasks, including mapping flood plains, monitoring disasters, and predicting crop yields. University researchers are doing similar things — using AI to monitor croplands, track air quality and identify invasive species more efficiently and accurately via satellite and drone imagery [2].
This automates the repetitive image-processing tasks (which is why land cover mapping and data organization show ~60%+ automation scores), while humans still handle interpretation, system design, and validation.
Sources
How fast is AI adoption growing for Remote Sensing Scientist?
Adoption is moving fast because the economic payoff is huge: satellites generate more imagery than humans could ever label manually, and AI dramatically multiplies what a small team can analyze. The ISPRS 2026 Congress program [3] highlights how machine learning and deep learning are being applied to automate plume detection, source attribution, and uncertainty reduction, signaling that the profession itself is embracing these tools. The job market reflects this: employers are seeking GIS professionals with AI literacy, including LLM workflows, machine learning for spatial analysis, and geospatial automation.
AI is projected to eliminate 92 million jobs globally by 2030, [but] it will simultaneously create 170 million new ones, according to the World Economic Forum's Future of Jobs Report [4]. Some friction remains — researchers like those at Minnesota are grappling with [AI's] broader environmental implications, and other jobs, including some in the computer, legal, business and financial, and architecture and engineering occupational groups are also potentially susceptible to AI-related impacts per the U.S. Bureau of Labor Statistics [5]. The encouraging takeaway: human judgment — recommending hardware, training others, and asking should we do this — remains the hardest part to automate, and that's exactly where your career can shine.
Sources
Will AI replace Remote Sensing Scientist?
Not entirely. We think AI will take over some tasks, but not the whole job.
Remote sensing is already one of AI's busiest workplaces. Foundation models like NASA and IBM's Prithvi, trained on 13 years of satellite data, can map flood plains, monitor disasters, and predict crop yields automatically [1]. University researchers are using similar tools to track air quality and identify invasive species via drone and satellite imagery far faster than humans could alone [2]. The repetitive work, labeling images, organizing datasets, running standard classifications, is being automated at real speed.
But a 38.6% AI Resilience Score tells you this role is under genuine pressure, not facing extinction. What stays human is the harder stuff: designing sensor systems, validating AI outputs, interpreting ambiguous results, and deciding what questions are even worth asking. The ISPRS 2026 Congress shows the profession itself is leaning into machine learning as a tool, not retreating from it [3]. The Bureau of Labor Statistics flags engineering and architecture roles as potentially susceptible to AI impact [5], and our demand data backs that up with a low long-term outlook.
The honest advice: build AI literacy now. Scientists who can work alongside these models, and catch their mistakes, will be far harder to replace than those who cannot.
Sources
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Latest AI news for Remote Sensing Scientist
These articles highlight the vital role of AI in advancing remote sensing careers. For instance, NASA's work on Dynamic Targeting showcases how AI can enhance satellite decision-making for better data collection. Similarly, initiatives like Project Cumulus illustrate AI's potential in improving weather forecasts and climate resilience, particularly in vulnerable regions. Embracing these AI advancements will equip future remote sensing scientists and technologists with the tools to tackle global challenges, making their work more impactful and relevant in a rapidly changing environment.
The emerging AI battlespace: Counter-AI threats to AI-powered satellite remote sensing analysis
thebulletin.org • 5/13/2026
Remote sensing is a data collection technique that enables the detection and monitoring of physical characteristics of target objects or...
How researchers are using AI and satellite data to address global challenges
twin-cities.umn.edu • 2/23/2026
Artificial intelligence (AI), machine learning and deep learning are rapidly reshaping how researchers understand complex systems...
AI forecasting strengthens climate resilience
www.leeds.ac.uk • 1/22/2026
Researchers are harnessing the latest advances in AI to enhance weather prediction and improve climate resilience and food security in West...
AI weather forecasting initiative to strengthen climate resilience in West Africa
www.cam.ac.uk • 1/22/2026
Project Cumulus, funded by the Gates Foundation and the Foreign, Commonwealth & Development Office, will see researchers from the Alan...
How NASA Is Testing AI to Make Earth-Observing Satellites Smarter
www.nasa.gov • 7/24/2025
A technology called Dynamic Targeting could enable spacecraft to decide, autonomously and within seconds, where to best make science...
More Career Info
Career: Remote Sensing Scientists and Technologists
They study images and data from satellites and sensors to understand and solve problems related to the Earth's environment, weather, and land use.
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Employment & Wage Data
Median Wage
$122,570
Jobs (2024)
31,900
Growth (2024-34)
+0.6%
Annual Openings
2,000
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Recommend new remote sensing hardware or software acquisitions.
2
Manage or analyze data obtained from remote sensing systems to obtain meaningful results.
3
Discuss project goals, equipment requirements, or methodologies with colleagues or team members.
4
Train technicians in the use of remote sensing technology.
5
Develop automated routines to correct for the presence of image distorting artifacts, such as ground vegetation.
6
Attend meetings or seminars or read current literature to maintain knowledge of developments in the field of remote sensing.
7
Collect supporting data, such as climatic or field survey data, to corroborate remote sensing data analyses.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
