.. _refs:

Publications
============

This list summarizes all scientific publications that describe FORCE, functionality, validation etc. 


* **2021**

  | Frantz, D., Stellmes, M., and Ernst, S. (2021). Water vapor database for atmospheric correction of Landsat imagery.  Zenodo. Dataset available online:
  | https://doi.org/10.5281/zenodo.4468700

  | V. Zekoll, M. Main-Knorn, J. Louis, D. Frantz, R. Richter, and B. Pflug (2021): Comparison of Masking Algorithms for Sentinel-2 Imagery. Remote Sensing 13.
  | https://doi.org/10.3390/rs13010137


* **2020**

  | P. Rufin, D. Frantz, L. Yan, and P. Hostert (2020): Operational Coregistration of the Sentinel-2A/B Image Archive Using Multitemporal Landsat Spectral Averages. IEEE Geoscience and Remote Sensing Letters (early access).
  | https://doi.org/10.1109/LGRS.2020.2982245


* **2019**

  | Frantz, D. (2019): FORCE – Landsat + Sentinel-2 Analysis Ready Data and beyond: Remote Sensing 11, 1124.
  | http://doi.org/10.3390/rs11091124
  
  | Frantz, D., Stellmes, M., and Hostert, P. (2019): A Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery. Remote Sensing 11, 257.
  | http://doi.org/10.3390/rs11030257


* **2018**

  | Frantz, D., Haß, E., Uhl, A., Stoffels, J., and Hill, J. (2018). Improvement of the Fmask algorithm for Sentinel-2 images: Separating clouds from bright surfaces based on parallax effects. Remote Sensing of Environment 215, 471-481.
  | http://doi.org/10.1016/j.rse.2018.04.046

  | Frantz, D., and Stellmes, M. (2018). Water vapor database for atmospheric correction of Landsat imagery.  PANGAEA. Dataset available online:
  | http://doi.org/10.1594/PANGAEA.893109

  | Doxani, G., Vermote, E., Roger, J.-C., Gascon, F., Adriaensen, S., Frantz, D., Hagolle, O., Hollstein, A., Kirches, G., Li, F., Louis, J., Mangin, A., Pahlevan, N., Pflug, B., and Vanhellemont, Q. (2018). Atmospheric Correction Inter-Comparison Exercise. Remote Sensing 10, 352.
  | http://doi.org/10.3390/rs10020352

  
* **2017**

  | Frantz, D., Röder, A., Stellmes, M., and Hill, J. (2017). Phenology-adaptive pixel-based compositing using optical earth observation imagery. Remote Sensing of Environment 190, 331-347. 
  | http://doi.org/10.1016/j.rse.2017.01.002
  
  | Frantz, D. (2017). Generation of Higher Level Earth Observation Satellite Products for Regional Environmental Monitoring. Ph.D. dissertation. Faculty of Regional and Environmental Sciences, Trier University, Trier, Germany, p. 194
    http://ubt.opus.hbz-nrw.de/volltexte/2017/1046/pdf/frantz_phd.pdf

  
* **2016**

  | Frantz, D., Röder, A., Stellmes, M., and Hill, J. (2016). An operational radiometric Landsat pre-processing framework for large-area time-series applications. IEEE Transactions on Geoscience and Remote Sensing 54 (7): 3928-3943.
  | http://doi.org/10.1109/TGRS.2016.2530856

  | Frantz, D., Stellmes, M., Röder, A., Udelhoven, T., Mader, S., and Hill, J. (2016). Improving the Spatial Resolution of Land Surface Phenology by Fusing Medium- and Coarse-Resolution Inputs. IEEE Transactions on Geoscience and Remote Sensing 54 (7): 4153-4164. 
  | http://doi.org/10.1109/TGRS.2016.2537929

  
* **2015**

  | Frantz, D., Röder, A., Udelhoven, T., and Schmidt, M. (2015). Enhancing the Detectability of Clouds and Their Shadows in Multitemporal Dryland Landsat Imagery: Extending Fmask. IEEE Geoscience and Remote Sensing Letters 12 (6): 1242-1246. 
  | http://doi.org/10.1109/lgrs.2015.2390673

  | Frantz, D., Röder, A., Stellmes, M., and Hill, J. (2015). On the derivation of a spatially distributed aerosol climatology for its incorporation in a radiometric Landsat pre-processing framework. Remote Sensing Letters 6 (8): 647-656. 
  | http://doi.org/10.1080/2150704x.2015.1070314