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An Improved Forest Structure Data Set for Europe.

Authors :
Pucher, Christoph
Neumann, Mathias
Hasenauer, Hubert
Source :
Remote Sensing. Jan2022, Vol. 14 Issue 2, p395-395. 1p.
Publication Year :
2022

Abstract

Today, European forests face many challenges but also offer opportunities, such as climate change mitigation, provision of renewable resources, energy and other ecosystem services. Large-scale analyses to assess these opportunities are hindered by the lack of a consistent, spatial and accessible forest structure data. This study presents a freely available pan-European forest structure data set. Building on our previous work, we used data from six additional countries and consider now ten key forest stand variables. Harmonized inventory data from 16 European countries were used in combination with remote sensing data and a gap-filling algorithm to produce this consistent and comparable forest structure data set across European forests. We showed how land cover data can be used to scale inventory data to a higher resolution which in turn ensures a consistent data structure across sub-regional, country and European forest assessments. Cross validation and comparison with published country statistics of the Food and Agriculture Organization (FAO) indicate that the chosen methodology is able to produce robust and accurate forest structure data across Europe, even for areas where no inventory data were available. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
14
Issue :
2
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
154882635
Full Text :
https://doi.org/10.3390/rs14020395