The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

Dmitry Schepaschenko* (Corresponding Author), Jérôme Chave, Oliver L Phillips, Simon L Lewis, Stuart J Davies, Maxime Réjou-Méchain, Plinio Sist, Klaus Scipal, Christoph Perger, Bruno Herault, Nicolas Labrière, Florian Hofhansl, Kofi Affum-Baffoe, Alexei Aleinikov, Alfonso Alonso, Christian Amani, Alejandro Araujo-Murakami, John Armston, Luzmila Arroyo, Nataly AscarrunzCelso Azevedo, Timothy Baker, Radomir Bałazy, Caroline Bedeau, Nicholas Berry, Andrii M Bilous, Svitlana Yu Bilous, Pulchérie Bissiengou, Lilian Blanc, Kapitolina S Bobkova, Tatyana Braslavskaya, Roel Brienen, David F R P Burslem, Richard Condit, Aida Cuni-Sanchez, Dilshad Danilina, Dennis Del Castillo Torres, Géraldine Derroire, Laurent Descroix, Eleneide Doff Sotta, Marcus V N d'Oliveira, Christopher Dresel, Terry Erwin, Mikhail D Evdokimenko, Jan Falck, Ted R Feldpausch, Ernest G Foli, Robin Foster, Steffen Fritz, Antonio Damian Garcia-Abril, Aleksey Gornov, Maria Gornova, Ernest Gothard-Bassébé, Sylvie Gourlet-Fleury, Marcelino Guedes, Keith C Hamer, Farida Herry Susanty, Niro Higuchi, Eurídice N Honorio Coronado, Wannes Hubau, Stephen Hubbell, Ulrik Ilstedt, Viktor V Ivanov, Milton Kanashiro, Anders Karlsson, Viktor N Karminov, Timothy Killeen, Jean-Claude Konan Koffi, Maria Konovalova, Florian Kraxner, Jan Krejza, Haruni Krisnawati, Leonid V Krivobokov, Mikhail A Kuznetsov, Ivan Lakyda, Petro I Lakyda, Juan Carlos Licona, Richard M Lucas, Natalia Lukina, Daniel Lussetti, Yadvinder Malhi, José Antonio Manzanera, Beatriz Marimon, Ben Hur Marimon Junior, Rodolfo Vasquez Martinez, Olga V Martynenko, Maksym Matsala, Raisa K Matyashuk, Lucas Mazzei, Hervé Memiaghe, Casimiro Mendoza, Abel Monteagudo Mendoza, Olga V Moroziuk, Liudmila Mukhortova, Samsudin Musa, Dina I Nazimova, Toshinori Okuda, Luis Claudio Oliveira, Petr V Ontikov, Andrey F Osipov, Stephan Pietsch, Maureen Playfair, John Poulsen, Vladimir G Radchenko, Kenneth Rodney, Andes H Rozak, Ademir Ruschel, Ervan Rutishauser, Linda See, Maria Shchepashchenko, Nikolay Shevchenko, Anatoly Shvidenko, Marcos Silveira, James Singh, Bonaventure Sonké, Cintia Souza, Krzysztof Stereńczak, Leonid Stonozhenko, Martin J P Sullivan, Justyna Szatniewska, Hermann Taedoumg, Hans Ter Steege, Elena Tikhonova, Marisol Toledo, Olga V Trefilova, Ruben Valbuena, Luis Valenzuela Gamarra, Sergey Vasiliev, Estella F Vedrova, Sergey V Verhovets, Edson Vidal, Nadezhda A Vladimirova, Jason Vleminckx, Vincent A Vos, Foma K Vozmitel, Wolfgang Wanek, Thales A P West, Hannsjorg Woell, John T Woods, Verginia Wortel, Toshihiro Yamada, Zamah Shari Nur Hajar, Irié Casimir Zo-Bi

*Corresponding author for this work

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Abstract

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.

Original languageEnglish
Article number198
JournalScientific Data
Volume6
DOIs
Publication statusPublished - 10 Oct 2019

Bibliographical note

This study has been partly supported by the IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) projects funded by ESA; the Austrian Federal Ministry of Science and Research (BMWF-4.409/30-II/4/2009); the Austrian Academy of Sciences (ÖAW2007-11); the Research Project AGL2009-08562, Ministry of Science’s Research and Development, Spain; the Project LIFE+ “ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques” cofounded by Life+ UE program (contract number LIFE13 ENV/PL/000048) and The National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D); the Brazilian National Council of Science and Technology (PVE project #401279/2014-6 and PELD (LTER) project #441244/2016-5); USAID (1993–2006); Brazilian National Council of Science and Technology-CNPq (Processes 481097/2008-2, 201138/2012-3); Foundation for Research Support of the State of Sao Paulo-FAPESP (Processes 2013/16262-4, 2013/50718-5). European Research Council Advanced Grant T-FORCES (291585); the Russian State Assignment of the CEPF RAS no. АААА-А18-118052400130-7. The Russian Science Foundation supported data processing of the plot data from Russia (project no. 19-77-30015). We would like to thank Shell Gabon and the Smithsonian Conservation Biology Institute for funding the collection of the RABI data (contribution No 172 of the Gabon Biodiversity Program). We would also like to thank Alexander Parada Gutierrez, Javier Eduardo Silva-Espejo, Jon Lloyd, and Olaf Banki for sharing their plot data. JC is funded by Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01; TULIP: ANR-10-LABX-0041).

Keywords

  • biogeography
  • forest ecology
  • DENSITY
  • RATES
  • NETWORK
  • DYNAMICS
  • SENSITIVITY
  • ABOVEGROUND BIOMASS
  • PATTERNS

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