Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests

Show simple item record Neumann, Mathias Moreno, Adam Thurnher, Christopher Mues, Volker Härkönen, Sanna Mura, Matteo Bouriaud, Olivier Lang, Mait Cardellini, Giuseppe Thivolle-Cazat, Alain Bronisz, Karol Merganic, Jan Alberdi, Iciar Astrup, Rasmus Mohren, Frits Zhao, Maosheng Hasenauer, Hubert 2017-02-15T09:19:01Z 2017-02-15T09:19:01Z 2016-07
dc.identifier.citation Neumann , M , Moreno , A , Thurnher , C , Mues , V , Härkönen , S , Mura , M , Bouriaud , O , Lang , M , Cardellini , G , Thivolle-Cazat , A , Bronisz , K , Merganic , J , Alberdi , I , Astrup , R , Mohren , F , Zhao , M & Hasenauer , H 2016 , ' Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests ' , Remote Sensing , vol. 8 , no. 7 , 554 .
dc.identifier.other PURE: 69780436
dc.identifier.other PURE UUID: c6815421-7604-4f0e-a483-fc15c8867f4b
dc.identifier.other WOS: 000382224800024
dc.identifier.other Scopus: 85019707645
dc.description.abstract Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at en
dc.format.extent 18
dc.language.iso eng
dc.relation.ispartof Remote Sensing
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject NPP
dc.subject bioeconomy
dc.subject forest inventory
dc.subject NFI
dc.subject climate
dc.subject carbon
dc.subject biomass
dc.subject downscaling
dc.subject increment
dc.subject MOD17
dc.subject LEAF-AREA INDEX
dc.subject UNITED-STATES
dc.subject ECOSYSTEMS
dc.subject RESOLUTION
dc.subject STAND
dc.subject 4112 Forestry
dc.title Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests en
dc.type Article
dc.contributor.organization Department of Forest Sciences
dc.description.reviewstatus Peer reviewed
dc.relation.issn 2072-4292
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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