Subventions et des contributions :

Titre :
Developing a LiDAR-based timber cruising model for the Canadian forest sector
Numéro de l’entente :
CARD1
Valeur d'entente :
25 000,00 $
Date d'entente :
14 juin 2017 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Colombie-Britannique, Autre, CA
Numéro de référence :
GC-2017-Q1-00067
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019)

Nom légal du bénéficiaire :
Griesbauer, Hardy (College of New Caledonia)
Programme :
Subventions d'engagement partenarial pour les collèges
But du programme :

The College of New Caledonia and Silvatech Consulting Ltd. are collaborating on an applied research project to research and develop a forest stand inventory process that uses light detection and ranging (LiDAR) data and digital imagery to produce accurate and precise estimates of stand-level timber volumes. Silvatech has conducted research and development in this area for 14 years, with the objective of developing an innovative service that uses accurate remote sensing technologies to predict forest stand species composition, density and volumes. The project will occur on the CNC Research Forest, a 12,500-hectare forest research and teaching facility located near Prince George, British Columbia. Students in the College's Natural Resources and Environmental Technology program will assist with establishing research sample plots to verify LiDAR-based models. x000D
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This project will introduce an important innovation to the remote sensing and forest management sectors in Canada. Forest companies will benefit from this technology by having precise models of forest stand volumes; these models will reduce planning costs and improve business decisions around timber harvesting. Widespread adoption of this new service could add substantial value to the sustainable and innovative management of Canada's forests. x000D