Point Cloud V2 Issue 4 (Jan 2017)

New Year’s Edition of the Point Cloud

The Point Cloud, AWARE’s Electronic Newsletter
Vol. 2, Issue 4. Date: 1/09/2017
aware.forestry.ubc.ca
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Welcome to the New Year’s edition of the Point Cloud. In this edition:

 

Introduction
Happy New Year!

There are a few things to mention since the last newsletter. First of all, I’d like to welcome Naime Safia to AWARE. He started in November and will be working on TLS metrics with Richard Fournier at the University of Sherbrooke.

Second, we expect to have complete datasets from the two LiDAR surveys we finished this summer. For those interested in getting a sample dataset from the multi-spectral survey of Petawawa, we expect to have this ready in late spring.

Finally, Jean-Romain Roussel, who is working on acquisition effects on point clouds (q8), has released two packages, lidR and rlas. These are now available on the CRAN: https://cran.r-project.org/

Feature Researcher

Aurélie Schmidt

Aurélie Schmidt is an MSc student at the Université de Sherbrooke, studying under the supervision of Richard Fournier and Joan Luther. She is working on Question 17a of Theme 2. Her research precludes the PhD research slated for Question 17 (now referred to as 17b) within the AWARE research project.
Aurelie’s first experience in Canada was in 2009 during an one year student exchange at the Université de Sherbrooke. At Sherbrooke, she got her first exposure to GIS and remote-sensing. She fell in love with Canada and remote-sensing. After completing her undergraduate degree in Environmental Sciences at the Université de Paris Diderot, France in 2011, she decided to continue in remote-sensing/GIS to gain more experience in tools to guide environmental sustainable management and natural disaster mapping.
She completed a professional MSc degree in geomatics/remote-sensing at the Université de Strasbourg, France in 2014. As part of this program, she completed three internships. The first one was at the Environment and Remote-sensing Laboratory, Strasbourg, France, where she performed tests for extracting and mapping landslides by object-oriented classification from very high resolution aerial and satellite images in Barcelonnette area, France. For her second internship, she worked for the French Ministry of Ecology to make an inventory and maps of protected species of “Natura 2000” sites in Haut-Rhin, France. Her last internship was at the Office National des Forêts in France where she was involved in the development of methods for characterizing forest stands (variety and structure) using ground, airborne and satellite remotely-sensed data to optimize forest management on the Mont Ventoux, France. She moved to Sherbrooke in 2015 to start her MSc research with R. Fournier.
When not working, Aurélie enjoys outdoors activities and cooking. She is also involved with the emergency mapping team of a Humanitarian organization, CartONG, that provide context maps to partners NGOs that get deployed on the field after a natural or human disaster.

Research Snapshot

 

Question 15 Theme 2: How can airborne LiDAR and high spatial resolution optical imagery be used to augment conventional forest health surveys?

 

Shawn Donovan, a Master’s student studying at the University of New Brunswick, is currently working on Question 15 of Theme 2 for the AWARE project. Shawn’s research is supervised by Dr. MacLean, and advised by Dr. Kershaw and Dr. Zhang from the University of New Brunswick, and by Dr. Lavigne from the Canadian Forest Service. Shawn’s research question focuses on how satellite and high spatial resolution optical imagery can be used to augment spruce budworm forest health surveys. Specifically, Shawn’s research is focusing on quantifying spruce budworm (SBW) defoliation using hemispherical optical imagery and EO-1 Hyperion hyperspectral satellite data.

 

The impacts that SBW outbreaks have on forest ecosystems and timber availability for forest industries are well documented. Managing for SBW outbreak impacts requires accurate quantification of the extent and severity, allowing for intervention management strategies and future outbreak predictions. In conjunction with SBW population data collections, defoliation (foliage loss) estimations provide forest managers with information for managing the forest sustainably and economically during an outbreak. However, SBW defoliation surveys have yet to adapt advances in remote sensing technology and mainly rely on human interpretation of defoliation for aerial (coarse landscape scale) and plot level (fine scale within stands) surveys.

 

Shawn’s research has two separate approaches designed to investigate alternative methods for both coarse and fine scale defoliation survey assessments. Approach 1 aims to use pre and post SBW defoliation satellite images acquired in 2016 from the EO-1 Hyperion hyperspectral satellite to calculate changes in various vegetation indices related to foliage health and abundance. The increased spectral resolution of the EO-1 Hyperion sensor (220 bands) over multispectral sensors (up to 10 bands) provides much finer spectral information, enabling greater sensitivity in vegetation indices changes. The spatial resolution of the EO-1 sensor (30m X 30m pixels) compared to aerial survey methods offers increased resolution, improving management capability across large forested areas on a pixel by pixel basis. Vegetation indices changes will be compared to a range of plot level branch defoliation estimates from 75 research plots established in the Gaspe Bay area of Quebec, and used to model the defoliation for the entire satellite image scene.

 

Approach 2 aims to use hemispherical images (fine scale within stands/plots) acquired in 2015 and 2016 pre and post defoliation from the 75 research plots to quantify changes in gap fraction, leaf area index (LAI), and canopy openness. The calculated image and canopy attributes will be compared with the coinciding plot branch level defoliation results, and correlation relationships will be examined. Hemispherical image acquisition is relatively quick to acquire compared to branch defoliation surveys, and also has an added benefit in that it quantifies the foliage remaining in the canopy and not the foliage that is removed. This possibly will provide new insight on tree/stand responses to SBW defoliation, improving forest management decisions.

Research progress completed to date includes: the collection of all field data (SBW defoliation, hemispherical images, and EO-1 Hyperion images); summarization of plot level SBW defoliation for 2014, 2015, and 2016; and pre-processing of all hemispherical images. Currently, ongoing objectives are focused on completing pre-processing of all satellite images, and analysis of hemispherical images from the 2015 dataset.

Figure 1.

AWARE Research Opportunities

 

 

Graduate Students


TERRAIN BASED INDICATORS IN PREDICTIVE SPATIAL REPRESENTATIONS OF FOREST GROWTH AND WOOD FIBRE ATTRIBUTES

Download Full Description PDF

A MESc. Student at Nipissing University will investigate the potential to derive a suite of terrain based indicators from newly acquired LiDAR data and other geospatial information at the Newfoundland core site and integrate these with existing soil and forest structure information available from the provincial growth plot network. The student will then assess the capacity of these indicators to be used as inputs into land classification schemes which can be used to produce predictive spatial representations of forest growth and wood fibre attributes.

The ideal candidate will have some background in quantitative analysis at the undergraduate level, a Bachelor’s degree in forestry, biology or geography and some experience in growth and yield modelling or forest inventory.

Interested candidates are encouraged to submit a cover letter and curriculum vitae by Jan. 1, 2017 to:

Dr. Jeff Dech
Associate Professor
Department of Biology and Chemistry
Nipissing University
100 College Drive
North Bay, ON, Canada P1B 8L7
Tel: (705) 474-3450 x.4701
Fax: (705) 474-1947
jeffrey@nipissingu.ca

 


Post-Doctoral Positions

 

DEVELOPMENT OF GENERALIZED AIRBORNE LIDAR METHODS FOR TREE SPECIES IDENTIFICATION TRANSFERABLE ACROSS CANADIAN FOREST SITES

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AWARE (Assessment of Wood Attributes from Remote Sensing) is an NSERC Collaborative Research and Development (CRD) project spanning eight universities, federal and provincial governments and seven industrial partners that seeks to use remote sensing to enhance Canada’s forest inventory and to improve the modelling of forested ecosystems (see aware.forestry.ubc.ca).

Within this framework, we are seeking applicants for a postdoctoral fellowship to join AWARE researchers, other postdoctoral fellows and graduate students who are actively conducting research on a variety of themes related to the project’s overall objectives. The selected postdoctoral fellow will be mentored by Prof. Benoît St-Onge, Ph.D. (Department of Geography, University of Quebec at Montreal) and will work collaboratively with other project members locally, and across Canada.

Application

Persons interested in this position should send a statement of interest outlining relevant research qualifications (maximum of two pages), a CV (showing the actual or planned Ph.D. defence date), and up to three relevant publications and contact information for three references. At the end of the selection process, a copy of the PhD diploma will be required.

Deadline for applications: 16 January 2017

Please submit your application, or any request for further information, to:

Prof. Benoît St-Onge
Phone: +1 (514) 987-3000 ext. 0280
email: st-onge.benoit@uqam.ca


METHODS DEVELOPMENT FOR TERRESTRIAL LIDAR APPLIED TO FOREST INVENTORY WITH EMPHASIS ON INTEGRATING A TREE ARCHITECTURAL MODEL

 

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Location: Applied Geomatics Department, Université de Sherbrooke, Sherbrooke, Quebec, Canada

Timeframe: Up to two years starting between April 2016 and September 2016

The Terrestrial LiDAR research group at the Applied Geomatics Department of the Université de Sherbrooke is seeking to hire a post-doctoral candidate. The research will be focussed on the development of methods to estimate tree and stand structural attributes from point cloud data acquired with terrestrial scanners in forested environments. These new methods will take advantage of architectural models to describe detailed branching structure and foliage distribution in trees.

Review of applications will begin on April. 1, 2016 and continue until the position is filled. Interested parties should send their CV and two letters of reference to:

Dr. Richard Fournier
Department of Applied Geomatics (FLSH)
Université de Sherbrooke
2500 boul de l’Université, Sherbrooke (Quebec) Canada J1K 2R1
E-mail: Richard.Fournier@USherbrooke.ca
Tel.: 1-819-821-8000 ext 63209

Upcoming Events

 

Next summer, IUFRO will hold a conference in Vancouver from June 12-16th (www.IUFROdiv5-2017.ca). The week after, from June 20-22nd, Earth Observation Summit will be happening at UQAM. AWARE is planning to present at both these events next summer.

Last of all, we will be holding our AGM in New Brunswick in the early summer. The date and location in New Brunswick will be determined in the coming months. More details will be provided in the New Year.


 

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