Reference number : GC-2017-Q3-00875, amendment number : , agreement type : G, recipient legal name : Coops, Nicholas (The University of British Columbia), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Strategic Projects - Group, program name french : Projets stratégiques - groupe, program purpose english : Understanding sources of wood supply is critical for sustainable forest management in Canada. Critical to this_x000D_
is the selection of the optimum seed for regeneration which involves selecting the best genotypes to ensure_x000D_
maximum target growth, yield attributes and climate adaptation. British Columbia is a leader in breeding trials_x000D_
for a number of key forest timber species, such as Douglas-fir, yet assessment of the elite trees in the field,_x000D_
while an integral component of all tree improvement programs, represents a very extensive, expensive, and_x000D_
time consuming activity. Airborne Light Detection and Ranging (LiDAR) is a recent remote sensing_x000D_
technology that has proven extremely valuable in forestry applications. By utilizing super-dense airborne_x000D_
LiDAR data from both aircraft and drones, we will extract elite trees and derive extremely detailed information on tree height, crown size and shape, branching and foliage area. We will utilize these attributes to then assess how these genetic differences impact tree architecture and growth. This research will be undertaken at a number of tree breeding sites on, or near, Vancouver Island, British Columbia with collaborators from the Tree Improvement Branch of the British Columbia Ministry of Forests, Lands and Natural Resource Operations to and will examine differences in tree morphology with a range of genetic trials. Project deliverables include new methods to extract detailed individual crown attributes from super-dense LiDAR data, tree and crown size maps, and analysis of differences in crown characteristics based on LiDAR analysis across the elite trees and the subsequent implication for tree growth and yield. We will also produce a best practice guide describing the use of super-dense LIDAR data for assessment of tree breeding surveys for use by the Inventory Branch of the Ministry of Forests, Lands and Natural Resource Operations for future monitoring._x000D_
_x000D_, program purpose french : Understanding sources of wood supply is critical for sustainable forest management in Canada. Critical to this_x000D_
is the selection of the optimum seed for regeneration which involves selecting the best genotypes to ensure_x000D_
maximum target growth, yield attributes and climate adaptation. British Columbia is a leader in breeding trials_x000D_
for a number of key forest timber species, such as Douglas-fir, yet assessment of the elite trees in the field,_x000D_
while an integral component of all tree improvement programs, represents a very extensive, expensive, and_x000D_
time consuming activity. Airborne Light Detection and Ranging (LiDAR) is a recent remote sensing_x000D_
technology that has proven extremely valuable in forestry applications. By utilizing super-dense airborne_x000D_
LiDAR data from both aircraft and drones, we will extract elite trees and derive extremely detailed information on tree height, crown size and shape, branching and foliage area. We will utilize these attributes to then assess how these genetic differences impact tree architecture and growth. This research will be undertaken at a number of tree breeding sites on, or near, Vancouver Island, British Columbia with collaborators from the Tree Improvement Branch of the British Columbia Ministry of Forests, Lands and Natural Resource Operations to and will examine differences in tree morphology with a range of genetic trials. Project deliverables include new methods to extract detailed individual crown attributes from super-dense LiDAR data, tree and crown size maps, and analysis of differences in crown characteristics based on LiDAR analysis across the elite trees and the subsequent implication for tree growth and yield. We will also produce a best practice guide describing the use of super-dense LIDAR data for assessment of tree breeding surveys for use by the Inventory Branch of the Ministry of Forests, Lands and Natural Resource Operations for future monitoring._x000D_
_x000D_, agreement title english : Assessing genetic gains in coastal Douglas-fir using advanced remote sensing, agreement title french : Assessing genetic gains in coastal Douglas-fir using advanced remote sensing, agreement number : STPGP, agreement value : 318790.0, agreement start date : 2017-11-08, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2020-2021)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2020-2021)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada