Knowledge of current and future status of forest resources are critical for forest planning and sustainable forest management. Most forest growth and yield models currently in operational use cannot readily integrate 3D data inputs, specifically wall-to-wall 3D measures of forest structure from Airborne Laser Scanning (ALS) and Digital Aerial Photogrammetry (DAP), as well as derived forest inventory attribute layers (i.e. Enhanced Forest Inventory, EFI).
This project requires a one year post doctoral fellow, with a possible second year extension, who will explore the development of EFI-driven growth simulators as well as derivation of spatially-explicit height growth increments from a time series of 3D data inputs. Outcomes of this research will be shared via peer-reviewed publications and an open-access R software package. The project is supported by a collaboration with the Pacific Forestry Centre, Canadian Forest Service and the Canadian Wood Fiber Centre.
Successful applicants should:
- Hold a PhD in Forestry, Forest Ecology, or related field;
- Have a strong statistical background;
- Have experience in developing predictive models, including linear, non-linear, and mixed-effects approaches and a demonstrated interest in applying 3D remote sensing datasets
- Have experience working with stand-level forest growth and yield models;
- Have strong programming skills (preferably in R). Experience in R package development is also a strong asset;
- Have excellent oral and written communication skills with a strong publication record.
- Prior experience in developing growth models will be a strong asset.
- Experience in working with ALS and DAP data is desirable, but not a requirement.
The candidate will be based at the University of British Columbia (UBC) in Vancouver, Canada under the supervision of Professor Nicholas Coops. Applicants should send a letter explaining their motivation and relevant skill set, a CV and the names of three references to firstname.lastname@example.org
The deadline for sending in applications is May 15th 2021, but we will consider applications until the position is filled. The expected start date would be in July 1st 2021. The position is for a fixed length of 12 months with a possibility of a second year extension.