An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications

@article{Frantz2016AnOR,
  title={An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications},
  author={David Frantz and Achim Roder and Marion Stellmes and Joachim Hill},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2016},
  volume={54},
  pages={3928-3943}
}
We developed a large-area preprocessing framework for multisensor Landsat data, capable of processing large data volumes. Cloud and cloud shadow detection is performed by a modified Fmask code. Surface reflectance is inferred from Tanré's formulation of the radiative transfer, including adjacency effect correction. A precompiled MODIS water vapor database provides daily or climatological fallback estimates. Aerosol optical depth (AOD) is estimated over dark objects (DOs) that are identified in… CONTINUE READING

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