Landsat Surface Product Validation Instrumentation: The BigMAC Exercise
Users of remotely sensed Earth optical imagery are increasingly demanding a surface reflectance or surface temperature product instead of the top-of-atmosphere products that have been produced historically. Validating the accuracy of surface products remains a difficult task since it involves assessment across a range of atmospheric profiles, as well as many different land surface types. Thus, the standard approaches from the satellite calibration community do not apply, and new technologies need to be developed. The Big Multi-Agency Campaign (BigMAC) was developed to assess current technologies that might be used for the validation of surface products derived from satellite imagery, with emphasis on Landsat. Conducted in August 2021, in Brookings, SD, USA, a variety of measurement technologies were fielded and assessed for accuracy, precision, and deployability. Each technology exhibited its strengths and weaknesses. Handheld spectroradiometers are capable of surface reflectance measurements with accuracies within the 0.01-0.02 absolute reflectance units, but these are expensive to deploy. Unmanned Aircraft System (UAS)-based radiometers have the potential of making measurements with similar accuracy, but these are also difficult to deploy. Mirror-based empirical line methods showed improved accuracy potential, but their deployment also remains an issue. However, there are inexpensive radiometers designed for long-term autonomous use that exhibited good accuracy and precision, in addition to being easy to deploy. Thermal measurement technologies showed an accuracy potential in the 1-2 K range, and some easily deployable instruments are available. The results from the BigMAC indicate that there are technologies available today for conducting operational surface reflectance/temperature measurements, with strong potential for improvements in the future.
Authors
- Rehman S. Eon
- Brandon Russell (ORCID: https://orcid.org/0000-0002-8848-4841)
- J. Irwin (ORCID: https://orcid.org/0000-0001-5828-0787)
- Mahesh Shrestha (ORCID: https://orcid.org/0000-0002-8368-6399)
- Emily Maddox (ORCID: https://orcid.org/0000-0001-5649-1193)
- Larry Leigh (ORCID: https://orcid.org/0000-0003-0836-4768)
- Aaron Gerace (ORCID: https://orcid.org/0000-0001-7158-4830)
- Nina Raqueño
- David Conran (ORCID: https://orcid.org/0000-0001-9225-8575)
- Dennis Helder (ORCID: https://orcid.org/0000-0002-7379-4679)
- Timothy Bauch
- Christopher Durell
- Lucy Falcon
- J. P. Mann (ORCID: https://orcid.org/0000-0002-4748-0836)
Institutions
- United States Geological Survey (US)
- Rochester Institute of Technology (US)
- South Dakota State University (US)
- Earth Resources Observation and Science Center
Publication Details
- Journal
- Sensors
- Published
- 2025-04-19
- DOI
- https://doi.org/10.3390/s25082586
- Citations
- 2
- Primary Topic
- Calibration and Measurement Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Geological Survey