LabCompass

Melba M. Crawford

Engineering · Purdue University West Lafayette

Established · publishing since 1970

Publications

246

Citations

7,733

Est. group size

~3

Recurring co-author estimate

Active years

57

Publishing since 1970

Research summary
AI-generated

Melba M. Crawford's research focuses on analyzing remote sensing data—images and sensor measurements collected from satellites, aircraft, and drones—using machine learning and deep learning methods. A major application area is agriculture, where her work predicts crop traits like yield, biomass, and nitrogen use from drone-based imagery, LiDAR (laser-based 3D scanning), and hyperspectral cameras (which capture many more color bands than standard cameras). She also develops general-purpose AI models (foundation models and transformers) for classifying and interpreting multispectral and hyperspectral imagery across different sensor types.

Remote sensing image classificationHyperspectral and multispectral image analysisDeep learning and transformer models for geospatial dataUAV/drone-based crop phenotyping and yield predictionDomain generalization and transfer learning for sensor data

Publication output has fluctuated over the past decade, with a peak around 2021 and generally lower yearly counts since 2022, suggesting a slowing pace in recent years.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 4.6/year recently
2017: 7 publications172018: 8 publications182019: 8 publications192020: 6 publications202021: 15 publications15212022: 5 publications222023: 10 publications232024: 4 publications242025: 3 publications252026: 1 publication26
Recent publications
Publishes in
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing×8
  • Remote Sensing×7
  • arXiv (Cornell University)×6
  • IEEE Transactions on Geoscience and Remote Sensing×5
  • Frontiers in Plant Science×4
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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