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Remote Sensing Scientists and Technologists

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.

Median Annual Pay
$112,280
Range: $59,590 - $183,500
Training Time
4-5 years
AI Resilience
🟡AI-Augmented
Education
Bachelor's degree

🎬Career Video

📋Key Responsibilities

  • Manage or analyze data obtained from remote sensing systems to obtain meaningful results.
  • Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS).
  • Integrate other geospatial data sources into projects.
  • Organize and maintain geospatial data and associated documentation.
  • Compile and format image data to increase its usefulness.
  • Prepare or deliver reports or presentations of geospatial project information.
  • Discuss project goals, equipment requirements, or methodologies with colleagues or team members.
  • Process aerial or satellite imagery to create products such as land cover maps.

💡Inside This Career

The remote sensing scientist analyzes data captured from above—processing satellite imagery, aerial photographs, and sensor data to understand Earth's surface, monitor environmental changes, and extract information for applications ranging from agriculture to urban planning to disaster response. A typical week blends data processing with analysis and communication. Perhaps 40% of time goes to image processing: calibrating data, applying algorithms, creating derived products. Another 30% involves analysis and interpretation—identifying patterns, validating results, integrating with other geospatial data. The remaining time splits between report writing, client communication, data management, and staying current with evolving sensing technologies and analysis methods.

People who thrive as remote sensing scientists combine technical facility with spatial thinking and genuine interest in understanding what imagery reveals about the world. Successful scientists develop expertise in specific domains—land cover, atmospheric conditions, agricultural monitoring, urban analysis—while building the programming and statistical skills that modern remote sensing demands. They must translate complex data into actionable information for non-specialists. Those who struggle often cannot bridge the gap between technical processing and meaningful interpretation or find the data management aspects tedious. Others fail because they become disconnected from the real-world applications their analysis supports.

Remote sensing science enables observation at scales impossible from the ground, with scientists supporting applications in agriculture, forestry, urban planning, environmental monitoring, defense, and disaster management. The field has grown with satellite availability, sensor capabilities, and the computational power that makes processing vast imagery archives feasible. Remote sensing scientists appear in discussions of Earth observation, environmental monitoring, geospatial analysis, and the view from above that reveals patterns invisible from the surface.

Practitioners cite the unique perspective remote sensing provides and the broad applications of imagery analysis as primary rewards. Seeing the world from above offers fascinating viewpoints. The applications span environmental to commercial to defense sectors. The field continues advancing with new sensors and methods. The work combines technical skills with visual interpretation. The expertise enables understanding at otherwise impossible scales. Common frustrations include the weather dependence that limits optical imagery collection and the data volumes that require constant storage and processing infrastructure management. Many find that clients don't understand the limitations of what remote sensing can reveal. The field requires ongoing technical learning as methods evolve. Ground truth validation can be difficult to obtain.

This career requires geoscience or engineering education emphasizing remote sensing and GIS, combined with image processing and programming experience. Strong analytical, technical, and communication skills are essential. The role suits those fascinated by Earth observation who enjoy data-intensive analysis. It is poorly suited to those preferring fieldwork over computer analysis, uncomfortable with technical image processing, or needing direct physical engagement with their subject matter. Compensation is solid with opportunities in government agencies, environmental consulting, defense contractors, and emerging commercial Earth observation companies.

📈Career Progression

1
Entry (10th %ile)
0-2 years experience
$59,590
$53,631 - $65,549
2
Early Career (25th %ile)
2-6 years experience
$81,210
$73,089 - $89,331
3
Mid-Career (Median)
5-15 years experience
$112,280
$101,052 - $123,508
4
Experienced (75th %ile)
10-20 years experience
$148,430
$133,587 - $163,273
5
Expert (90th %ile)
15-30 years experience
$183,500
$165,150 - $201,850

📚Education & Training

Requirements

  • Entry Education: Bachelor's degree
  • Experience: Several years
  • On-the-job Training: Several years
  • !License or certification required

Time & Cost

Education Duration
4-5 years (typically 4)
Estimated Education Cost
$46,440 - $173,400
Public (in-state):$46,440
Public (out-of-state):$96,120
Private nonprofit:$173,400
Source: college board (2024)

🤖AI Resilience Assessment

AI Resilience Assessment

Moderate human advantage with manageable automation risk

🟡AI-Augmented
Task Exposure
Medium

How much of this job involves tasks AI can currently perform

Automation Risk
Medium

Likelihood that AI replaces workers vs. assists them

Job Growth
Stable
0% over 10 years

(BLS 2024-2034)

Human Advantage
Moderate

How much this role relies on distinctly human capabilities

Sources: AIOE Dataset (Felten et al. 2021), BLS Projections 2024-2034, EPOCH FrameworkUpdated: 2026-01-02

💻Technology Skills

Remote sensing software (ENVI, ERDAS)GIS software (ArcGIS)Programming (Python)Image processing toolsMATLABMicrosoft Office

Key Abilities

Deductive Reasoning
Inductive Reasoning
Oral Comprehension
Written Comprehension
Oral Expression
Written Expression
Problem Sensitivity
Near Vision
Information Ordering
Mathematical Reasoning

🏷️Also Known As

All Source Intelligence AnalystCommercial Drone OperatorCommercial Drone PilotDrone OperatorDrone PilotGeospatial Image AnalystGeospatial Intelligence AnalystImage ScientistImagery Remote Sensing ScientistLIDAR Analyst (Light Detection and Ranging Analyst)+5 more

🔗Related Careers

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🔗Data Sources

Last updated: 2025-12-27O*NET Code: 19-2099.01

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