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Forests produce a wide range of ecosystem services, including the traditional wood production. Sustainable forest management approaches are used to locally calibrate wood harvesting on the basis of local conditions and should not adversely affect other ecosystem services. To assess forest harvesting sustainability and impacts it is essential to know their spatial distribution. At the present date accurate statistics on wood harvesting are not available in Italy. In this context, remote sensing and automatic mapping algorithms constitute an important tool for providing spatially explicit information to quantify wood harvesting and thus supporting more sustainable forest management approaches. In this work we tested an automatic mapping algorithm (3I3D) using multitemporal Sentinel-2 imagery to produce a map of forest disturbance produced by different types of wood harvesting in the province of Arezzo for the year 2018. Thanks to a photo-interpretation work of high resolution PlanetScope imagery and field data collected by the Carabinieri Forestali, we were able to calculate commission (2%) and omission (18%) errors of the automatic 3I3D map. The results of this work motivate the introduction of remote sensing tools as a support for monitoring and quantification of forest wood harvesting.

Forest planning, forest management, and forest policy require updated, reliable, and harmonized spatial datasets. In Italy a national geographic Forest Information System (FIS) designed to store and facilitate the access and analysis of spatial datasets is still missing. Among the different information layers which are useful to start populating a FIS, two are essential for their multiple use in the assessment of forest resources: (i) forest mapping, and (ii) data from Airborne Laser Scanning (ALS). Both layers are not available wall-to-wall for Italy, though different local sources of information potentially useful for their implementation already exist. The objectives of this work were to: (i) review forest maps and ALS data availability in Italy; (ii) develop for the first time a high resolution forest mask of Italy which was validated against the official statistics of the Italian National Forest Inventory; (iii) develop the first mosaic of all the main ALS data available in Italy producing a consistent Canopy Height Model (CHM). An on-line geographic FIS with free access to both layers from (ii) and (iii) was developed for demonstration purposes. The total area of forest and other wooded lands computed from the forest mask was 102.608.82 km2 (34% of the Italian territory), i.e., 1.9% less than the NFI benchmark estimate. This map is currently the best wall-to-wall forest mask available for Italy. We showed that only the 63% of the Italian territory (the 60% of the forest area) is covered by ALS data. These results highlight the urgent need for a national strategy to complete the availability of forest data in Italy.

On October 29, 2018, the Vaia storm hits the North-Eastern regions of Italy by wind gusts exceeding 200 km h-1. The forests in these regions have been seriously damaged. This contribution illustrates the methodology adopted in the emergency phase to estimate forest damages caused by Vaia storm, both in terms of damaged forest areas and growing stock volume of fallen trees. 494 Municipalities registered forest damages caused by Vaia, destroyed or intensely damaged forest stands amounted to about 42.500 ha, spread in Trentino Alto Adige, Veneto, Friuli Venezia Giulia, Lombardy and, only marginally, Piedmont and Valle d’Aosta. The growing stock volume of fallen trees was about 8.5 millions m3.