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Abstract:Forest mapping is an important source of information for assessing woodland resources and a key issue for any National Forest Inventory (NFI). In the present study, a detailed wall-to-wall forest cover map was generated for all of Switzerland, which meets the requirement of the Swiss NFI forest definition. The workflow is highly automated and based on digital surface models from image-based point clouds of airborne digital sensor data. It fully takes into account the four key criteria of minimum tree height, crown coverage, width, and land use. The forest cover map was validated using almost 10,000 terrestrial and stereo-interpreted NFI plots, which verified 97% agreement overall. This validation implies different categories such as five production regions, altitude, tree type, and distance to the forest border. Overall accuracy was lower at forest borders but increased with increasing distance from the forest border. Commission errors remained stable at around 10%, but increased to 17.6% at the upper tree line. Omission errors were low at 1%-10%, but also increased with altitude and mainly occurred at the upper tree line (19.7%). The main reasons for this are the lower image quality and the NFI height definition for forest which apparently excludes shrub forest from the mask. The presented forest mapping approach is superior to existing products due to its national coverage, high level of detail, regular updating, and implementation of the land use criteria.

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Abstract& Key message The potential of European National Forest Inventories to harmonise stem quality estimation in European forests was identified despite considerable differences in existing national approaches. & Context Knowledge on stem quality and assortments structure in European forests is highly important for policy makers and the timber industry and also for carbon life cycle analysis due to the fact that different timber products have different end use and thus store carbon for different time periods.& Aims The study aim was to evaluate the potential of European National Forest Inventories (NFI) to objectively report on the stem quality in European forests in a harmonised manner. & Methods A comprehensive questionnaire was conducted as the first important step to evaluate the current status of stem quality assessment and assess the existing level of harmonisation. & Results Direct stem quality assessment or classification is used in 19 out of 28 European NFIs. Only eight countries provide timber assortment estimates from their NFIs. In addition, different sampling strategies for stem quality assessment are used among NFIs. Tree parameters relevant for stem quality assessment on standing trees were identified for the purpose of harmonisation. Several methods towards harmonisation between European NFIs for the purpose of reporting on stem quality of European forests were suggested. & Conclusion Current European NFIs are not capable of reporting the stem quality of European forests in a harmonised manner at this stage and considerable efforts will need to be taken before the harmonised stem quality estimation can be Handling Editor: Jean-Michel LebanContribution of the co-authors MB, JR and MK designed the study, performed the questionnaire study and wrote the manuscript; GM contributed in designing the questionnaire and revised the manuscript; GM, KK, AK, GK prepared a description of the timber quality assessment in their NFIs and revised the manuscript; RA, TG, CF and AL reviewed literature and revised the manuscript. prepared. However, the inquiry also revealed that there is a potential to develop the harmonised estimations in future. Electronic supplementary material

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The Balassa-Samuelson effect is usually seen as the prime explanation of the continuous real appreciation of central and east European (CEE) transition countries' currencies against their western counterparts. The response of a small country's real exchange rate to various shocks is derived in a simple model. It is shown that productivity shocks work not only through a Balassa-type supply channel but also through an investment demand channel.

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