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Get Free AccessGlobal measurements of forest height, biomass are urgently needed as essential climate and ecosystem variables, but can benefit from greater co-operation between remote sensing (RS) and forest ecological communities. The Forest Observation System - FOS (https://forest-observation-system.net/ [https://forest-observation- system.net/]) is an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. FOS aims to link the RS community with ecologists who measure forest biomass and estimating biodiversity in the field. The FOS aims to overcome data sharing issues and introduce a standard biomass data flow from tree-level measurement to the plot-level aggregation served in the most suitable form for the RS. Ecologists benefit from the FOS with improved access to global biomass information, data standards, gap identification and potentially improved funding opportunities to address the known gaps and deficiencies in the data. FOS closely collaborate with the CTFS-ForestGEO, the ForestPlots.net (incl. RAfNFOR, AfriTRON and T-FORCES), AusCover, TmFO and the llASA network. FOS is an open initiative with other networks and teams most welcome to join. The online database provides open access for forest plot location, canopy height and above-ground biomass. Plot size is 0.25ha or larger. Comparison of plot biomass data with available global and regional maps (incl. Kindermann et al., 2013; Thurner et al., 2013; Saatchi et al., 2011; Baccini et al., 2012; Avitabile et al., 2016; Hu et al., 2016; Santoro et al., 2018) shows wide range of uncertainties associated with biomass estimation.
Dmitry Schepaschenko, Jérôme Chave, Oliver L. Phillips, Stuart J. Davies, Simon L. Lewis, Plínio Sist, Maxime Réjou‐Méchain, Christoph Perger (2019). First mission - towards a global harmonised in-situ data repository for forest biomass datasets validation. Pesquisa Florestal Brasileira
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Type
Article
Year
2019
Authors
8
Datasets
0
Total Files
0
Language
English
Journal
Pesquisa Florestal Brasileira
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