Sensor Data Quality Control

Sensor Data Quality Control is a methodological framework within agricultural data systems that ensures the accuracy, consistency, and reliability of sensor-derived measurements through systematic validation, calibration, and error detection processes specific to in-field harvest data collection environments.

40

Publications

1.7K

Citations

200

Authors

82

Institutions

Publications per year

2017–2026

22

Authors

200

  1. GT
    Greg Timms

    Commonwealth Scientific and Industrial Research Organisation, Australia

    2 publications · 48 citations

    2

    h-index

  2. LR
    Leon Reznik

    Rochester Institute of Technology, United States

    2 publications · 36 citations

    2

    h-index

  3. CA
    Christopher A. Fiebrich

    Oklahoma Biological Survey, United States

    2 publications · 372 citations

    2

    h-index

  4. DS
    Daniel Smith

    Commonwealth Scientific and Industrial Research Organisation, Australia

    2 publications · 48 citations

    2

    h-index

  5. JR
    Jeffrey R. Taylor

    National Ecological Observatory Network, United States

    2 publications · 178 citations

    2

    h-index

1–5 of 200

Venues

  1. Sensors

    6 publications · 264 citations

    6

    h-index

  2. The Science of The Total Environment

    2 publications · 138 citations

    2

    h-index

  3. BioScience

    1 publications · 123 citations

    1

    h-index

  4. Earth system science data

    1 publications · 11 citations

    1

    h-index

  5. Control Engineering Practice

    1 publications · 28 citations

    1

    h-index

1–5