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Sharing data for improved forest protection and monitoring

Date:
October 10, 2019
Source:
International Institute for Applied Systems Analysis
Summary:
Although the mapping of aboveground biomass is now possible with satellite remote sensing, these maps still have to be calibrated and validated using on-site data gathered by researchers across the world.
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FULL STORY

Although the mapping of aboveground biomass is now possible with satellite remote sensing, these maps still have to be calibrated and validated using on-site data gathered by researchers across the world. IIASA contributed to the establishment of a new global database to support Earth Observation and encourage investment in relevant field-based measurements and research.

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It also provides 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. Although satellite remote sensing technology now allows researchers to produce extensive maps of aboveground biomass, these maps still require reliable, up-to-date, on-site data for calibration and validation. Collecting data in the field by measuring trees and documenting species is, however, a very labor intensive, expensive, and time-consuming exercise and it would therefore make sense to bring together the many extant data sets to provide real added value for a number of applications. In terms of policy applications, doing so can also lead to improved biomass products and better monitoring of forest resources, which could in turn lead to more effective forest protection measures.

In a new paper published in the journal Scientific Data, 143 researchers involved in this type of data collection in the field, explored whether it was possible to build a network that openly shares their data on biomass for the benefit of different communities. They particularly wanted to see if they could bring together as much on-site data on biomass as possible to prepare for new satellite missions, such as the European Space Agency's BIOMASS mission, with a view to improving the accuracy of current remote sensing based products, and developing new synergies between remote sensing and ground-based ecosystem research communities. Their efforts have resulted in the establishment of the Forest Observation System (FOS) -- an international, collaborative initiative that aims to establish a global on-site forest aboveground biomass database to support Earth Observation and to encourage investment in relevant field-based measurements and research.

"Keeping in mind that this paper is a data descriptor and not a conventional paper with hypotheses, the whole idea behind this study is a new open database on biomass data. This is important for the following reasons: First, it represents a way to link the ecological/forestry and remote sensing communities. It also overcomes existing data sharing barriers, while promoting data sharing beyond small, siloed communities. Lastly, it provides recognition to the people working in the field, including those who collect the data, which is why there are 143 coauthors on this paper, as they are all contributors to the database," explains study lead author Dmitry Shchepashchenko, a researcher in the IIASA Ecosystems Services and Management Program.

The researchers collected data from 1,645 permanent forest sample plots from 274 locations distributed around the globe. This data has now been made available for download via the FOS website. The initiative represents the first attempt at bringing this type of data together from different networks in a single location. The researchers point out that their work in this regard is ongoing and there are plans to continue adding more data sets and networks to the FOS. In addition to promoting data sharing, the system also promotes a new leading network on biomass data (through the FOS), which IIASA is leading and will continue to grow into the future.

Apart from the obvious benefits that data sharing hold for the scientific community, the data are also essential for training various models at IIASA such as the BioGeoChemistry Management Model (BGC-MAN) and the Global Forest Model (G4M). Several on-going IIASA projects, as well as other ecological-, biophysical-, and economic models and projects outside of IIASA will also benefit, which means that providing access to the data can improve models and understanding of biomass more generally.

"A great deal of effort has gone into collecting forest data in the past, but people working in the field (ecologists and forestry scientists) hardly ever share the collected data, or if they do, they share it only within ecological networks. The data are valuable not only for ecology, but also for remote sensing calibration and validation, in other words, to train algorithms that create biomass maps, and for assessing the accuracy of the products along with inputs to a variety of models. This piece of work represents a real step forward in sharing a very valuable biomass data set," concludes IIASA researcher Linda See, who was also a study coauthor.


Story Source:

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Journal Reference:

  1. Dmitry Schepaschenko, 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 Ascarrunz, Celso 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. The Forest Observation System, building a global reference dataset for remote sensing of forest biomass. Scientific Data, 2019; 6 (1) DOI: 10.1038/s41597-019-0196-1

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International Institute for Applied Systems Analysis. "Sharing data for improved forest protection and monitoring." ScienceDaily. ScienceDaily, 10 October 2019. <www.sciencedaily.com/releases/2019/10/191010125619.htm>.
International Institute for Applied Systems Analysis. (2019, October 10). Sharing data for improved forest protection and monitoring. ScienceDaily. Retrieved March 28, 2024 from www.sciencedaily.com/releases/2019/10/191010125619.htm
International Institute for Applied Systems Analysis. "Sharing data for improved forest protection and monitoring." ScienceDaily. www.sciencedaily.com/releases/2019/10/191010125619.htm (accessed March 28, 2024).

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