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

Schepaschenko, Dmitry, Chave, Jérôme, Phillips, Oliver L, Lewis, Simon L, Davies, Stuart J, Réjou-Méchain, Maxime, Sist, Plinio, Scipal, Klaus, Perger, Christoph, Herault, Bruno, Labrière, Nicolas, Hofhansl, Florian, Affum-Baffoe, Kofi, Aleinikov, Alexei, Alonso, Alfonso, Amani, Christian, Araujo-Murakami, Alejandro, Armston, John, Arroyo, Luzmila, Ascarrunz, Nataly, Azevedo, Celso, Baker, Timothy, Bałazy, Radomir, Bedeau, Caroline, Berry, Nicholas, Bilous, Andrii M, Bilous, Svitlana Yu, Bissiengou, Pulchérie, Blanc, Lilian, Bobkova, Kapitolina S, Braslavskaya, Tatyana, Brienen, Roel, Burslem, David FRP, Condit, Richard, Cuni-Sanchez, Aida, Danilina, Dilshad, Del Castillo Torres, Dennis, Derroire, Géraldine, Descroix, Laurent, Sotta, Eleneide Doff, d'Oliveira, Marcus VN, Dresel, Christopher, Erwin, Terry, Evdokimenko, Mikhail D, Falck, Jan, Feldpausch, Ted R, Foli, Ernest G, Foster, Robin, Fritz, Steffen, Garcia-Abril, Antonio Damian, Gornov, Aleksey, Gornova, Maria, Gothard-Bassébé, Ernest, Gourlet-Fleury, Sylvie, Guedes, Marcelino, Hamer, Keith C, Susanty, Farida Herry, Higuchi, Niro, Coronado, Eurídice N Honorio, Hubau, Wannes, Hubbell, Stephen, Ilstedt, Ulrik, Ivanov, Viktor V, Kanashiro, Milton, Karlsson, Anders, Karminov, Viktor N, Killeen, Timothy, Koffi, Jean-Claude Konan, Konovalova, Maria, Kraxner, Florian, Krejza, Jan, Krisnawati, Haruni, Krivobokov, Leonid V, Kuznetsov, Mikhail A, Lakyda, Ivan, Lakyda, Petro I, Licona, Juan Carlos, Lucas, Richard M, Lukina, Natalia, Lussetti, Daniel, Malhi, Yadvinder, Manzanera, José Antonio, Marimon, Beatriz, Junior, Ben Hur Marimon, Martinez, Rodolfo Vasquez, Martynenko, Olga V, Matsala, Maksym, Matyashuk, Raisa K, Mazzei, Lucas, Memiaghe, Hervé, Mendoza, Casimiro, Mendoza, Abel Monteagudo, Moroziuk, Olga V, Mukhortova, Liudmila, Musa, Samsudin, Nazimova, Dina I, Okuda, Toshinori, Oliveira, Luis Claudio, Ontikov, Petr V, Osipov, Andrey F, Pietsch, Stephan, Playfair, Maureen, Poulsen, John, Radchenko, Vladimir G, Rodney, Kenneth, Rozak, Andes H, Ruschel, Ademir, Rutishauser, Ervan, See, Linda, Shchepashchenko, Maria, Shevchenko, Nikolay, Shvidenko, Anatoly, Silveira, Marcos, Singh, James, Sonké, Bonaventure, Souza, Cintia, Stereńczak, Krzysztof, Stonozhenko, Leonid, Sullivan, Martin JP ORCID logoORCID: https://orcid.org/0000-0002-5955-0483, Szatniewska, Justyna, Taedoumg, Hermann, Ter Steege, Hans, Tikhonova, Elena, Toledo, Marisol, Trefilova, Olga V, Valbuena, Ruben, Gamarra, Luis Valenzuela, Vasiliev, Sergey, Vedrova, Estella F, Verhovets, Sergey V, Vidal, Edson, Vladimirova, Nadezhda A, Vleminckx, Jason, Vos, Vincent A, Vozmitel, Foma K, Wanek, Wolfgang, West, Thales AP, Woell, Hannsjorg, Woods, John T, Wortel, Verginia, Yamada, Toshihiro, Nur Hajar, Zamah Shari and Zo-Bi, Irié Casimir (2019) The Forest Observation System, building a global reference dataset for remote sensing of forest biomass. Scientific Data, 6. ISSN 2052-4463

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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.

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