• Network: ICOS
• Principal investigator: Kamel Soudani
• PI-affiliated institution: University of Paris Sud / CNRS
• Primary IGBP ecosystem type: Deciduous Broadleaf Forests
• Dominant plant functional type: Deciduous Broadleaf trees
• Recent and historic disturbance and management events that may affect this site:
  • Forestry: Forest management such as logging of any kind, plantation planting, or herbicide application.
• Flux data collection:
  • Start date: March 2005
  • End date: Ongoing
• Flux methods:
  • Chambers
  • Eddy covariance
• Optical data collection:
  • Start date: March 2005
  • End date: Ongoing
• Data collection period: Various: Continuous operation: Variable collected continuously with the reported method; Intermittent: Variable collected intermittently with the reported method; Periodic operation: Variable collected part of the year with the reported method
• Data scale: Leaf, Canopy, Stand
• Collection methods: Tower, Manual
• Types of data collected: Albedo (Y Kipp & Zonen net radiometer) fAPAR (from Kipp and Zonen PQS1 PPFDin, PPFDout and PPFD below canopy), fIPAR (from Kipp and Zonen PQS1 PPFDin and PPFD below canopy), NDVI (Laboratory made (640-660;780-920)), PAR (Kipp & Zonen PQS1), PRI (Skye and Decagon sensors [531, 570 (10 nm)]), PYR (Kipp & Zonen CNR4 (LWin and LWout)), Relative Humidity (Vaisala HMP155 in Young 61302V ventilated shield), Spectral reflectance (Aseq spectrometers), Webcam (Axis P1348 (5Mpx)), Leaf pigment (Campbell IR120 sensors), Canopy temperature (Inventory).
• Publications
  • Soudani K, Hmimina G, Dufrêne E, Berveiller D, Delpierre N, Ourcival JM, Rambal S, Joffre R. Relationships between photochemical reflectance index and light-use efficiency in deciduous and evergreen broadleaf forests. Remote Sensing of Environment. 2014 Mar 25;144:73-84.
  • Soudani K, Hmimina G, Delpierre N, Pontailler JY, Aubinet M, Bonal D, Caquet B, De Grandcourt A, Burban B, Flechard C, Guyon D. Ground-based Network of NDVI measurements for tracking temporal dynamics of canopy structure and vegetation phenology in different biomes. Remote sensing of environment. 2012 Aug 1;123:234-45.
  • Hmimina G, Dufrêne E, Pontailler JY, Delpierre N, Aubinet M, Caquet B, De Grandcourt A, Burban B, Flechard C, Granier A, Gross P. Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements. Remote Sensing of Environment. 2013 May 15;132:145-58.

Flux data repository: http://gaia.agraria.unitus.it/home/site-details?id=17
External home page: http://www.barbeau.u-psud.fr/