Smart Harvest Operations and Timber Processing for Improved Forest Management
| Autor: | Roberto Tognetti, S. Grigolato, Pietro Panzacchi, J. Sandak, Gianni Picchi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Traceability
business.industry Computer science Process (engineering) media_common.quotation_subject forest operations Forest management Environmental resource management harvesting equipment Information technology digital information technology sensors timber processing Work (electrical) forest machines Quality (business) business Resilience (network) Silviculture media_common |
| Zdroj: | Climate-Smart Forestry in Mountain Regions ISBN: 9783030807665 Climate-Smart Forestry in Mountain Regions, edited by Tognetti R., Smith M., Panzacchi P., pp. 317–359. Cham, Heidelberg, New York, Dordrecht, London: Springer, 2022 info:cnr-pdr/source/autori:Picchi G., Sandak J., Grigolato S., Panzacchi P., Tognetti R./titolo:Smart Harvest Operations and Timber Processing for Improved Forest Management/titolo_volume:Climate-Smart Forestry in Mountain Regions/curatori_volume:Tognetti R., Smith M., Panzacchi P./editore: /anno:2022 |
| Popis: | Climate-smart forestry can be regarded as the evolution of traditional silviculture. As such, it must rely on smart harvesting equipment and techniques for a reliable and effective application. The introduction of sensors and digital information technologies in forest inventories, operation planning, and work execution enables the achievement of the desired results and provides a range of additional opportunities and data. The latter may help to better understand the results of management options on forest health, timber quality, and many other applications. The introduction of intelligent forest machines may multiply the beneficial effect of digital data gathered for forest monitoring and management, resulting in forest harvesting operations being more sustainable in terms of costs and environment. The interaction can be pushed even further by including the timber processing industry, which assesses physical and chemical characteristics of wood with sensors to optimize the transformation process. With the support of an item-level traceability system, the same data could provide a formidable contribution to CSF. The “memory” of wood could support scientists to understand the response of trees to climate-induced stresses and to design accordingly an adaptive silviculture, contributing to forest resilience in the face of future changes due to human-induced climate alteration. |
| Databáze: | OpenAIRE |
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