Articles | Volume 18, issue 2
https://doi.org/10.5194/bg-18-621-2021
https://doi.org/10.5194/bg-18-621-2021
Research article
 | 
27 Jan 2021
Research article |  | 27 Jan 2021

Retrieval and validation of forest background reflectivity from daily Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) data across European forests

Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke

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Cited articles

Bacour, C. and Bréon, F. M.: Variability of biome reflectance directional signatures as seen by POLDER, Remote Sens. Environ., 98, 80–95, 2005. 
Baret, F., Morisette, J. T., Fernandes, R. A., Champeaux, J. L., Myneni, R. B., Chen, J., Plummer, S., Weiss, M., Bacour, C., Garrigues, S., and Nickeson, J. E.: Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products: Proposition of the CEOSBELMANIP, IEEE T. Geosci. Remote Sens., 44, 1794–1803, 2006. 
Campagnolo, M. L., Sun, Q., Liu, Y., Schaaf, C., Wang, Z., and Román, M. O.: Estimating the effective spatial resolution of the operational BRDF, albedo, andnadir reflectance products from MODIS and VIIRS, Remote Sens. Environ., 175, 52–64, https://doi.org/10.1016/j.rse.2015.12.033, 2016. 
Canisius, F. and Chen, J. M.: Retrieving forest background reflectance in a boreal region from Multi-angle Imaging SpectroRadiometer (MISR) data, Remote Sens. Environ., 107, 312–321, 2007. 
Chen, J. M., Li, X., Nilson, T., and Strahler, A.: Recent advances in geometrical optical modeling and its applications, Remote Sens. Rev., 18, 227–262, 2000. 
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Short summary
Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
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