The FluxnetEO dataset (Landsat) for European stations located in Germany

@misc{https://hdl.handle.net/11676/I-aTvaq0A-IElgJ9kzUH7Bl_,
  author={Besnard, Simon and Walther, Sophia and Weber, Ulrich},
  title={The FluxnetEO dataset (Landsat) for European stations located in Germany},
  year={2023},
  note={Quality checked and gap-filled monthly Landsat observations of surface reflectance at global eddy co-variance sites for the time period 1984-2022.
	Two product versions: one features all Landsat pixels within 2km radius around a given site, and a second version consists of an average time series that represents the area within 1km2 around a site. All data layers have a complementary layer with gap-fill information. Landsat data comprise all sites in the Fluxnet La Thuile, Berkeley and ICOS Drought 2018 data releases.
	Reflectance products: enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), generalized NDVI (kNDVI), near infra-red reflectance of vegetation (NIRv), normalized difference water index (NDWI) with both shortwave infra-red bands as reference, the scaled wide dynamic range vegetation index (sWDRVI), surface reflectance in individual Landsat bands. Based on the Landsat 4,5,7,8 collection 1 products with a pixel size of 30m.
	Supplementary data to Walther, S., Besnard, S., Nelson, J.A., El-Madany, T. S., Migliavacca, M., Weber, U., Ermida, S. L., Brümmer, C., Schrader, F., Prokushkin, A., Panov, A., Jung, M. , 2021. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset, in preparation for Biogeosciences Discussions.
	ZIP archive of netcdf files for stations in Europe: DE-Akm, DE-Bay, DE-Fen, DE-Geb, DE-Gri, DE-GsB, DE-Gwg, DE-Hai, DE-Har, DE-HoH, DE-Hte, DE-Hzd, DE-Kli, DE-Lkb, DE-Lnf, DE-Meh, DE-Obe, DE-RuR, DE-RuS, DE-RuW, DE-Seh, DE-SfN, DE-Spw, DE-Tha, DE-Wet, DE-Zrk},
  keywords={quality control, gap-filled, surface reflectance, eddy-covariance stations, Landsat},
  url={https://hdl.handle.net/11676/I-aTvaq0A-IElgJ9kzUH7Bl_},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/I-aTvaq0A-IElgJ9kzUH7Bl_}
}

TY - DATA
T1 - The FluxnetEO dataset (Landsat) for European stations located in Germany
ID - 11676/I-aTvaq0A-IElgJ9kzUH7Bl_
PY - 2023
AB - Quality checked and gap-filled monthly Landsat observations of surface reflectance at global eddy co-variance sites for the time period 1984-2022.
	Two product versions: one features all Landsat pixels within 2km radius around a given site, and a second version consists of an average time series that represents the area within 1km2 around a site. All data layers have a complementary layer with gap-fill information. Landsat data comprise all sites in the Fluxnet La Thuile, Berkeley and ICOS Drought 2018 data releases.
	Reflectance products: enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), generalized NDVI (kNDVI), near infra-red reflectance of vegetation (NIRv), normalized difference water index (NDWI) with both shortwave infra-red bands as reference, the scaled wide dynamic range vegetation index (sWDRVI), surface reflectance in individual Landsat bands. Based on the Landsat 4,5,7,8 collection 1 products with a pixel size of 30m.
	Supplementary data to Walther, S., Besnard, S., Nelson, J.A., El-Madany, T. S., Migliavacca, M., Weber, U., Ermida, S. L., Brümmer, C., Schrader, F., Prokushkin, A., Panov, A., Jung, M. , 2021. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset, in preparation for Biogeosciences Discussions.
	ZIP archive of netcdf files for stations in Europe: DE-Akm, DE-Bay, DE-Fen, DE-Geb, DE-Gri, DE-GsB, DE-Gwg, DE-Hai, DE-Har, DE-HoH, DE-Hte, DE-Hzd, DE-Kli, DE-Lkb, DE-Lnf, DE-Meh, DE-Obe, DE-RuR, DE-RuS, DE-RuW, DE-Seh, DE-SfN, DE-Spw, DE-Tha, DE-Wet, DE-Zrk
UR - https://hdl.handle.net/11676/I-aTvaq0A-IElgJ9kzUH7Bl_
PB - Carbon Portal
AU - Besnard, Simon
AU - Walther, Sophia
AU - Weber, Ulrich
KW - quality control
KW - gap-filled
KW - surface reflectance
KW - eddy-covariance stations
KW - Landsat
ER -