Will AI replace Remote Sensing Technicians?
AI can do 81% of the work Remote Sensing Technicians do at least twice as fast. People already use it for 3 of their 21 tasks, while 14 more are ready but barely used so far. 4 still need a person.
AI is already doing this3 · 13% of time
People already use AI for these tasks in real work, based on Anthropic's analysis of how Claude is used.
- Prepare documentation or presentations, including charts, photos, or graphs.Mostly automated5% of time
- Document methods used and write technical reports containing information collected.Mostly automated4% of time
- Develop specialized computer software routines to customize and integrate image analysis.Mostly automated4% of time
AI could do this next14 · 68% of time
AI can speed these up by at least half, but real use has not caught up yet. These are next in line.
- Collect geospatial data, using technologies such as aerial photography, light and radio wave detection systems, digital satellites, or thermal energy systems.9% of time
- Verify integrity and accuracy of data contained in remote sensing image analysis systems.8% of time
- Integrate remotely sensed data with other geospatial data.8% of time
- Adjust remotely sensed images for optimum presentation by using software to select image displays, define image set categories, or choose processing routines.8% of time
- Consult with remote sensing scientists, surveyors, cartographers, or engineers to determine project needs.6% of time
- Develop or maintain geospatial information databases.5% of time
- Collect verification data on the ground, using equipment such as global positioning receivers, digital cameras, or notebook computers.4% of time
- Monitor raw data quality during collection, and make equipment corrections as necessary.4% of time
- Merge scanned images or build photo mosaics of large areas, using image processing software.4% of time
- Calibrate data collection equipment.4% of time
- Maintain records of survey data.3% of time
- 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.3% of time
- Collect remote sensing data for forest or carbon tracking activities involved in assessing the impact of environmental change.1% of time
- Provide remote sensing data for use in addressing environmental issues, such as surface water modeling or dust cloud detection.1% of time
Still needs a person4 · 19% of time
No real AI use, no proven AI speedup and no robot that can do it yet. This is the part of the job to build on.
- Correct raw data for errors due to factors such as skew or atmospheric variation.6% of time
- Manipulate raw data to enhance interpretation, either on the ground or during remote sensing flights.6% of time
- Participate in the planning or development of mapping projects.5% of time
- Collaborate with agricultural workers to apply remote sensing information to efforts to reduce negative environmental impacts of farming practices.1% of time
Your week is not the average
Describe what you actually do and get a personal report: your own tasks, what AI can already do, what stays yours and a 90 day plan.
What this means
AI can already do almost all of this work at least twice as fast. Real use is still behind at 12 out of 100, so the change here is only getting started. Expect the role to shift toward deciding what to do, checking AI's work and owning the result.
What to do next
- Do the 3 tasks AI is already handling with AI yourself. Your peers already are, and it is quickly becoming the baseline.
- Get ahead on the 14 tasks AI could do next. These move as tools improve, so learning them early pays off.
- Build on the 4 tasks that stay human. This is where your judgment, skill and relationships matter most.
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