Grant: Engage Plus Grants Program
Université du Québec à Montréal
$12,500.00
Enhancement of species class and forest timber volume mapping methods based on aerial and space imagery
FY 2014-15
Summary
Currently FRMG (First Resource Management Group Inc.) allocates harvest blocks in Crown forests tocompanies that harvest or consume timber. Each consuming mill has specific requirements as to the type oftimber they require. The most important requirement is for hardwood versus softwood. Mills also expect toreceive certain amount of timber volume to process. The existing Ontario Ministry of Natural Resources(OMNR) Forest Resource Inventory (FRI) is very inaccurate with an estimated error of 64% in the speciescomposition on harvest blocks, which also translate in uncertainty of harvested volumes. This inaccuracy isextremely costly. It can result in harvesters or consuming mills having to purchase timber from unallocatedharvest blocks that may be a great distance away. The level of accuracy could be increased by new remotesensing approaches. Orthoimages and digital surface models (DSM) derived from aerial photo are now widelyavailable but have not yet been exploited to their full potential as more advanced methods are needed to extracttheir full information contents. Significant progress has been made in the first phase of this project in usingthese DSMs. A new method for creating canopy height models (detailed maps of forest height) from theseDSMs have been developed and applied to not only characterize heights but also timber volumes. Mapping theproportions of hardwood and softwood trees from aerial images has however proven more difficult thananticipated. Accuracy is variable depending on the acquisition conditions of these images. For this reason, inthis second phase, we will be using a different type of multispectral imagery for achieving our goals. Moreover,obtaining reliable validation data for the timber volumes predicted by remote sensing is quite challengingbecause the volume of a tree is difficult to measure. Without trustable validation data, it is difficult to ascertainthat the remote sensing estimates of volume are accurate. For this reason, an intensive field campaign will becarried out. FRMG inc. will benefit from the advances brought about by this project by reducing harvest costsfor their clients and profiting from a new competitive advantage.
Program
Engage Plus Grants Program
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
468535-2014
Name nom
StOnge, Benoît
Department département
Géographie
Organization id
57
Institution établissement
Université du Québec à Montréal
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2014
Competition year année de concours
2014
Award amount
12500
Program id
EGP2
Program name en
Engage Plus Grants Program
Program name fr
Programme de subvention d'engagement partenarial Plus
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1552
Committee name en
Quebec Internal Decision Committee
Committee name fr
Comité de décision interne pour le Québec
Area of application code
201
Area of application group en
Natural resources (economic aspects)
Area of application group fr
Ressources naturelles (aspects économiques)
Area of application en
Forestry (silviculture, forest management)
Area of application fr
Foresterie (sylviculture, aménagement forestier)
Research subject code
4102
Research subject group en
Geographical information
Research subject group fr
Information géographique
Research subject en
Remote sensing
Research subject fr
Télédétection
Partie
1
Nb partie
1
Application title
Enhancement of species class and forest timber volume mapping methods based on aerial and
space imagery
Keyword
NSERC
Application summary
Currently FRMG (First Resource Management Group Inc.) allocates harvest blocks in Crown forests tocompanies that harvest or consume timber. Each consuming mill has specific requirements as to the type oftimber they require. The most important requirement is for hardwood versus softwood. Mills also expect toreceive certain amount of timber volume to process. The existing Ontario Ministry of Natural Resources(OMNR) Forest Resource Inventory (FRI) is very inaccurate with an estimated error of 64% in the speciescomposition on harvest blocks, which also translate in uncertainty of harvested volumes. This inaccuracy isextremely costly. It can result in harvesters or consuming mills having to purchase timber from unallocatedharvest blocks that may be a great distance away. The level of accuracy could be increased by new remotesensing approaches. Orthoimages and digital surface models (DSM) derived from aerial photo are now widelyavailable but have not yet been exploited to their full potential as more advanced methods are needed to extracttheir full information contents. Significant progress has been made in the first phase of this project in usingthese DSMs. A new method for creating canopy height models (detailed maps of forest height) from theseDSMs have been developed and applied to not only characterize heights but also timber volumes. Mapping theproportions of hardwood and softwood trees from aerial images has however proven more difficult thananticipated. Accuracy is variable depending on the acquisition conditions of these images. For this reason, inthis second phase, we will be using a different type of multispectral imagery for achieving our goals. Moreover,obtaining reliable validation data for the timber volumes predicted by remote sensing is quite challengingbecause the volume of a tree is difficult to measure. Without trustable validation data, it is difficult to ascertainthat the remote sensing estimates of volume are accurate. For this reason, an intensive field campaign will becarried out. FRMG inc. will benefit from the advances brought about by this project by reducing harvest costsfor their clients and profiting from a new competitive advantage.