The compiling of Sustainable Forest Management (SFM) indicators is usually accomplished by ground surveys. This approach, based on forest inventory techniques, ensures accurate statistical assessments of forest attributes and how they change over time. However, surveying is generally expensive and time-consuming for medium to large forest management units. In addition, forest data are usually not updated within short time intervals. In order to develop more cost-effective data collection methods for large forest areas, the use of forest ecosystem inventory and mapping data obtained from remote sensors (i.e. drones) is highly recommended.

The FRESh LIFE project aimed to demonstrate:

• That the use of remote sensing (i.e. drones fitted with multispectral sensors) for forest mapping has the potential to make the compiling of indicators less expensive and time consuming than current data collection systems based on forest inventories;
• That the information generated through these new techniques will help improve forest management decisions;
• That the information obtained from these new techniques is extremely useful to help achieve sustainable forest management targets and forest certifications; and
• The applicability of the methodologies at a wider scale at the European Forest Data Centre and, subsequently, in the European Commission's Forest Information System for Europe.

Results



The FRESh LIFE project showed that remote sensing drones can be used to develop a forest information system that aggregates multiple indicator maps in order to create methodologies and products consistent with the activities of the European Forest Data Centre (EFDAC) and with the Forest Information System for Europe (FISE). Drone acquisition and forest information system was used to support forest managers in three pilot areas in Italy: Rincine, Comune di Londa (Florence), 276 ha; Caprarola: Comune di Caprarola (Viterbo), 240 ha; and Bosco Pennataro, Comune di Vastogirardi, (IS), 277 ha.

In these three areas, the beneficiaries began acquiring existing in homogeneous data and then proceeded with the harmonisation of data according to COST Action E43 “Harmonisation of National Forest Inventories in Europe: Technique for Common Reporting”. They then proceeded to the use of drones, both multispectral (visible and infra-red) and LIDAR (Laser Imaging Detection and Ranging). From the drone acquisitions, six forest indicators were extracted and the data reliability guaranteed by ground samples used as reference. The data was integrated into a GIS software, the Forest Information System, and then used by the forest managers of the pilot sites. One policy barrier identify by the project is the limit to fly drones only in the line-of- sight (LOS). In this regard, the project team advices policy makers to consider the possibility of classifying all forests in rural areas as “low-risk”, in order to allow drones to fly beyond the line-of-sight (BLOS) and to increase distances, without requiring a special permit. The Forest Information System proved to be a very flexible tool for use of different tasks and purposes by the managers of the three forests, allowing them to explore potential climate changes in the future and to anticipate the impacts on forests and forestry. It was used in day-to-day work and optimisation of the resources of the forest, such as wood cutting; through the defoliation indicators it was possible to monitor the health of the tress; from other indicators, it was possible to identify ancient trees or old charcoal kiln and use the system for the definition of new tracks and public itinerary that are particular relevant for the Natural Reserve. The project results were replicated in Rincine by extending the acquisition to the whole forest and in the Natural Reserve of Vallombrosa (Florence); and the resulting information system has been used to generate the management plans for both forests.

The extension of the project methodology at regional, national and international level is possible, but while the costs of the drone acquisitions are sustainable at a local scale, they are excessive on a larger scale. The project therefore suggested that the forest indicators should be extracted from available satellite imagery. Even if the measurement error is greater, the resolution is sufficient for good decision-making aimed at identifying areas that are relevant for drone acquisition.

The project team engaged several forest managers during the project’s duration, establishing good cooperation with another project (GOSURF) that aims to create an operational group inside the European Innovation Partnership (EIP-AGRI).

Further information on the project can be found in the project's layman report and After-LIFE Communication Plan (see "Read more" section).


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