David Frantz

Universität Trier, Humboldt-Universität zu Berlin

Papers

2

Total Citations

162

H-Index

2

About

David Frantz is a leading figure in the field of large-area remote sensing, with his research fundamentally advancing the operational use of Landsat and Sentinel-2 satellite data. His primary contributions lie in developing robust preprocessing frameworks and rigorously assessing atmospheric correction methods, which are critical for accurate, multi-temporal environmental monitoring. Frantz’s most influential work, “An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications” (2016, 99 citations), introduced a pioneering system that efficiently processes vast volumes of multisensor Landsat data. This framework, which integrates a modified Fmask algorithm for cloud detection and Tanré’s radiative transfer model for surface reflectance retrieval, has become a cornerstone for large-scale land surface studies. He further cemented his impact by co-authoring the landmark ACIX-II Land study (2022, 63 citations), a comprehensive benchmark that assessed the performance of state-of-the-art atmospheric correction processors for Landsat 8 and Sentinel-2. By providing the remote sensing community with validated, operational tools and critical inter-comparison data, Frantz has enabled more reliable time-series analyses, directly supporting advancements in agriculture, forestry, and climate change research.

Research Focus

Key Achievements

2
H-Index
2
Papers
162
Total Citations
81
Avg Citations/Paper
🏆 Most Cited Paper
An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications
99 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: Universität Trier, Humboldt-Universität zu Berlin

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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