Enhanced Forest Resource Inventory

Forest Resource Inventory (FRI)

As part of the government’s response to the recommendations from the Minister's Council on Forest Sector Competitiveness, the enhancement of the Forest Resources Inventory program was announced on September 29, 2005. As part of the enhancement the Ontario Ministry of Natural Resources and Forestry (MNRF) assumed full responsibility for production of the Forest Resources Inventory.

Coming out of that decision the administration of funding for the program was assigned to the Forestry Futures Trust Committee. In addition, a Provincial Forest Inventory Advisory Committee (PFIAC) was established to advise the MNRF on how to ensure the FRI program would remain current and effective. The PFIAC was given the option of utilizing technical committees to provide input on the design of the program. The MNRF retains the overall stewardship role, policy responsibility, scheduling and priority setting, standard setting, quality control and information management requirements for the program.

FRI Funding Clarification

Funding for the FRI program does not come from the traditional FFT stumpage charge, but has its own funding stream. The FRI program has a separate $10 million/yr commitment from the government to ensure the success of this program. Funding the program does not entail an additional contribution to the FFT by the forest industry, nor does it affect the core FFT silviculture program.

Knowledge Transfer and Tool Development (KTTD)

Round 5- anticipated Requests for proposals Fall 2026

Round 4 -

Approved project summaries can be found here

Project Number	Project Name	Company	Deliverables
KTTD 1B-2024	Field Plot Measurement using Mobile LiDAR Scanning	Forest Analysis Ltd.	MLS scanned point clouds of LiDAR calibration plots in leaf-off and leaf-on conditions – March 2025
			Open-source Computree/R scripts for extracting tree attributes – December 2025
			Technical report and Technology Transfer Session – March 2026

KTTD 2B-2024	Implementing Structurally Guided Sampling (SGS) approaches to guide FRI plot placement and prioritization	University of British Columbia	Competed transfer of SGS to Ontario cloud computing platform. Documentation and example datasets also transferred and available to users - 8 months from project start.
			Report detailing assessment of existing plot network / recommendation of critical plots and duplicate plots at Sudbury / French – Severn and Draft peer reviewed publication on the use of SGS approaches in high value stands. 18 months from project start
			Report on insights shared about influence of changing disturbance regimes, compositional shifts and age on SGS strategies in different forest ecosystems. 24 months from start
			Final report –End of Project - Best Practice guides, code demos (or online tutorials), open-source code packaging. Final validation of analyses. 24 Months from start

KTTD 3B-2024	Deep Learning to Estimate Species Proportions using SPL data	University of British Columbia	Report on the compiled SPL and species occurrence data over the focus sites in GreenFirst, Ottawa Valley and Haliburton Forests. 6 months from signing.
			draft peer review publication on the trained deep learning algorithm on new datasets and assessment of the transferability of the model to different forest types. 12 months from signing
			Report on accuracy assessment / field plot compilation and plot based initial accuracy assessment across the 3 companies sites. 18 months from signing.
			Workshop (in person or online), code demos, open source code packaging and peer reviewed publication. 24 Months from signing.

KTTD 3B-2024	Deep Learning to Estimate Species Proportions using SPL data	University of British Columbia	Report on the compiled SPL and species occurrence data over the focus sites in GreenFirst, Ottawa Valley and Haliburton Forests. 6 months from signing.
			draft peer review publication on the trained deep learning algorithm on new datasets and assessment of the transferability of the model to different forest types. 12 months from signing
			Report on accuracy assessment / field plot compilation and plot based initial accuracy assessment across the 3 companies sites. 18 months from signing.
			Workshop (in person or online), code demos, open source code packaging and peer reviewed publication. 24 Months from signing.

KTTD 4B-2024	Refining Species, Disturbance and Age information within eFRI Inventories	Université Laval	Raster layers with SPL and spectral metrics required for polygon segmentation as well as disturbance layers produced over the two study sites. October 2024
			Newly segmented polygons over two focus areas using the optimized and updated algorithm. December 2024
			Updated species composition in areas where attributes are outdated. Updated age and disturbance. Initial accuracy assessment for species and age. April 2025
			Newly derived polygons with imputed species, age and disturbance. Initial accuracy assessment for global product. October 2025
			Report on performance assessment/validation for RMF and OVF. February 2026.
			Workshop, packaging of open-source tool and peer-reviewed publication. April 2026

KTTD 5B-2024	Automated Road Extraction and Integration Across Forest Management Units	Université Laval	October 2024 – D1: Compiled SPL and road datasets over study area. Metadata statements and vector road coverages of existing road networks at test sites.
			July 1st, 2025 – D2: Project meeting and road assessment workshop. First full-scale implementation of the road detection, positioning, and condition assessment algorithm for feedback from the partners.
			January 15th, 2026 – D3: Integration of road age algorithm into GEE. D4: Final full-scale road networks delivered to partners at each FMU. D5: Model of vegetation development after road abandonment distributed.
			April 15th, 2026 – D6: All code and packages publicly released for download. D7: Draft paper on vegetation development after road abandonment including proposed set of criteria to determine “when should an abandoned road no longer be considered a road”. D8: Workshops developed and run for OMNRF and Forest Company staff on the application of the algorithms and their effective use.

KTTD 6B-2024	Use of RPAS and AI technologies to classify managed forest stands by silviculture intensity	Canadian Institute of Forestry	Report #1 Report on status of Objective I (Steps 1 to 3) regarding RPAS and field data acquisitions and Objective III Step #6 review of current advances in machine learning (target November 2024)
			Report #2: Report on status of Objective II (Step #4) analyses of compositional, structural and wood quality analyses and Objective III Step #7 Process RPAS imagery and LiDAR data (target April 2025)
			Report #3: Report on status of Objective II (Step #5) preparation of compositional and structural and wood quality theses and Objective III (Steps 7 to 9) (target November 2025)
			Report #4: Final report (target March 2026)

KTTD 7B-2024	Stand density for evaluating silvicultural opportunities and future yields	Ministry of Natural Resources and Forestry	October 2024: Minimum 50 plots established in pure (>70% species composition), conifer-dominated, 20-40 year old managed stands representing a range of total tree densities above 1500 stems per hectare.
			February 2025: Project meeting and density assessment workshop (virtual). The project team will develop a presentation that can be shared with potential users within Ontario. Focus will be on explanation of the utility of the model for planning and operations, and identification of missing conditions (ecoregion, species, density, etc.) where additional sampling is needed
			March 2025: Interim report prepared for FFT documenting progress including an explanation of how the DAT could be incorporated into the PAT to provide critical data for forest management planning and operations.
			September 2025: Field data collection completed.
			December 2025: Draft Training materials on how to use the DAT prepared and circulated to ROD and Forest Industry for feedback.
			January 2026: Draft report and/or manuscript submitted for external peer review. Training materials prepared for workshops to be held in 2026.
			February 2026: Workshops in the NE and NW regions to present train users of the PAT and associated DAT. Open-source code will be made available to users in an accessible format (i.e. ArcGIS bridging and/or Shiny app.). A manuscript prepared and submitted for peer review to an open source scientific journal.
			March 2026: Final Report prepared for FFT

KTTD 8B-2024	Tree Classification and Monitoring Using UAV Technologies	University of Guelph	UAV flights (Year 1): April 2024 – October 2024
			Development of data-preprocessing workflow: April 2024 – October 2024
			Development of tree crown segmentation workflow: September 2024 – May 2025
			Development of tree species spectral library and indices: January 2025 – April 2025
			UAV flights (Year 2): April 2025 – October 2025
			Development of tree species classification models: April 2025 – December 2025
			Finalization of tree species spectral library and indices: April 2025 – December 2025
			Validation of tree species classification models: September 2025 – April 2026
			Documentation and release of spectral libraries and classification models: January 2026 – April 2026

KTTD 9B-2024	A climate-sensitive growth simulator for Ontario	Natural Resources Canada	Development of a tree recruitment model for 26 species and 4 species groups in Ontario. A scientific manuscript completed by June 2025.
			Development of a diameter increment model for 26 species and 4 species groups in Ontario. A scientific manuscript completed by Sept 2025.
			Implementation of the two models into software. This is the intermediate milestone of this project. An open-source Java library including the recruitment and the diameter increment models completed by Sept 2025.
			Integration of the three models into CAPSIS and final implementation of the simulator. This is the final milestone of this project. A CAPSIS package including the new simulator completed by Feb 2026.
			Presentation of the simulator to practitioners through a seminar or a dedicated training. A final report to the KTTD program by March 2026.

KTTD 10B-2024	Towards a Living Forest Inventory with Forest Dynamics Modelling	Ministry of Natural Resources and Forestry	1. Succession Modelling: A stand-level natural succession model for boreal forest in Ontario and aggregated succession rules (Target date: December 2024)
			A stand-level post-disturbance (fire and clearcut) succession model and aggregated succession rules (Target date: June 2025)
			Peer reviewed journal publication(s) (Target date: March 2026)
			2. Mortality modelling: A stand-level boreal forest mortality model and analysis of mortality rates and variable importance by species and/or forest types (Target date: December 2024).
			Projection of boreal forest mortality 100-year in the future under different climate change scenarios (Target date: September 2025).
			Peer reviewed journal publication(s) (Target date: March 2026).
			3. Growth Modelling: A stand-level boreal forest growth model and analysis of variable importance and interactions in determining boreal forest growth (Target date: December 2024).
			Projection of boreal forest growth 100-year in the future under different climate change scenarios by species and/or forest type (Target date: July 2025).
			Peer reviewed journal publication(s) (Target date: March 2026).

KTTD 11A-2024	Automation of Polygon Delineation for Forested Landscapes	Forsite Consultants Ltd	Target Dec 20, 2024:'- Example polygons suitable for strategic inventory purposes (polygon feature class in geodatabase)
			- Documentation of recommended approach and associated eCognition ruleset
			- PowerPoint presentation of results

KTTD 12A-2024	Linking FRI data to FVS-Ontario – Phase 2	ESSA Technologies Ltd.	1. March 31 2024 - Project Progress Report and Draft Scripts
			2. Sept 1, 2024 - Draft Documentation
			3. September 30, 2024 – Final Documentation and Scripts (including GitHub publication)

KTTD 13A-2024	Lichen mapping facilitated by Single Photon LiDAR (SPL)	York University	May 2024: Compiled datasets over study area, including SPL, photos, and existing inventory data.
			August 2024: Obtained ground truthing via processing photos, initial methods/codes to extract LiDAR features.
			Jan 2025: The finalized LiDAR features and methods/models.
			March 2025: Journal manuscript, technical report, open-source code.

July 25 2023

Forestry Futures Trust Committee, in cooperation with the MNRF FRI section, hosted the KTTD R4 - Research needs to support FRI continuous inventory presentation. The following links provide access to the video, slide deck and follow-up Q&A

Round 3 -

Approved project summaries can be found here

The table below links project deliverables

Project Number	Author	Title	KTTD Deliverables
KTTD 1A-2021	Craig Robinson	Enhancements for eFRI Next Generation Handhelds - for VSN Plots	Full code and documentation, added to the public git repository on Github at this link: (https://github.com/csrobins/eFRI_LiDAR_Handheld)
KTTD 5A-2021	Donald Robinson	Linking FRI data to FVS-Ontario	1.Summary Document 2.Results and Next Steps 3.Hands-on Training session
KTTD 6A-2021	Alain Richard	eFRI Wetland Crosswalk and Applied Products	1. Geodatabases housing EWC habitat types and inferred information; January 2022 2. DUC - eFRI Wetland Crosswalk and Applied Products - Final Report; 3. Knowledge and Technology Transfer; March 2022
KTTD 7A-2021	Adam Anderson	Development of LiDAR Based Geospatial tools to Aid in Operational Planning in Ontario	Deliverables 1.Refined of the seasonal operability tool 2.The Road Location Optimization Tool
KTTD 8A-2021	Dr. Ben DeVries (UG) and Dr. Chris MacQuarrie (NRCan)	Developing an inventory of eastern hemlock for Ontario	1. Ontario Eastern Hemlock inventory: Single-band raster dataset with an embedded colour table. Class codes are defined as follows: 0: non-hemlock forest stand 1: hemlock-dominant forest stand 2: hemlock/mixwood co-dominant forest stand 3: hemlock/evergreen co-dominant forest stand 255: non-forest and no-data Available for download at: https://github.com/bendv/FFT-KTTD-Hemlock 2. Google Earth Engine script for loading and pre-processing Sentinel-2 image stacks This script computes the Infra-Red Enhanced Chlorophyll Index (IRECI) for all available Sentinel-2 images acquired within a given tile ID. It then generates 36 10-day median IRECI composites, aggregating all images over a four-year period. Available for download at https://github.com/bendv/FFT-KTTD-Hemlock 3. 10-day IRECI composite test stack and accompanying wooded area mask IRECI test stack: https://uoguelphca-my.sharepoint.com/:i:/g/personal/bdv_uoguelph_ca/EcQfBPSHDJpDmUlrQ87bEUEBIo90hxYe8r56-Eb-edNlhQ?e=dIDOnv Wooded area mask: https://uoguelphca-my.sharepoint.com/:i:/g/personal/bdv_uoguelph_ca/EeMsxEBuPwdGuG7qKDJnwy4B0FgxdXusbFBEq6VoZaqVzQ?e=vt4tgl Pre-trained Hemlock Classifier: https://uoguelphca-my.sharepoint.com/:u:/g/personal/bdv_uoguelph_ca/EVTwQ5OGWJ9JsDi0sMp9z-8Bb2Fr-DqcZPWixkotAMb46w?e=66DxrV 4. Report
KTTD 10A-2021	John Pineau	Private Land Inventory and Economics Study	1.The Ontario Woodlander—An Ontario Woodlot Association Quarterly. Issue 103, June 2021 2.The Ontario Woodlander—An Ontario Woodlot Association Quarterly. Issue 104, September 2021 3.December 15th, 2021 capstone presentation: 2021 MFC Capstone Presentations: December 14th & 15th \| Forestry (utoronto.ca) 4. OWA Conference Presentation (Murray Woods and Ben Gwilliam) April 21st, 2021; starts at 1:30 of the video: https://us06web.zoom.us/rec/share/iTt6cm9YNrjRPvPUk9tjwcAVw9Ccy5JdOWcslxd5cHaA2n7JlFky-FsaBFmXreI4.YNe_ecQkJbHIZZLm?startTime=1619046264000 Social Media Posts : https://www.facebook.com/OntarioWoodlotAssociation/photos/a.267688763293609/4185084881553958/ https://www.facebook.com/OntarioWoodlotAssociation/photos/a.3317024455026676/4363339463728498/ https://www.facebook.com/OntarioWoodlotAssociation/photos/pcb.4365178413544603/4365169036878874/ https://www.facebook.com/OntarioWoodlotAssociation/photos/a.267688763293609/4426154520780325/
KTTD 11A-2021	Andy Welch	Assisting Ottawa Valley Forest transition to T2 FRI	Project Report

KTTD 1B-2021	Alexander Bilyk	Assessing Site Productivity from Remote Sensing and historic information	Assessing Site Productivity from Remote Sensing and historic information Assessing Site Productivity via Remote Sensing—Age-Independent Site Index Estimation in Even-Aged Forests Final Report Webinar of results
KTTD 2B-2021	Dr. Nicholas Coops	Automated Road and Attribute Extraction from SPL Data	Code released for download Deliverable Workshops developed and run for Ministry and Forest Company staff on the toolkit
KTTD 3B-2021	Dr. Nicholas Coops	Integration of Photo Interpreted and LIDAR Attributes Into a Polygonal Forest Inventory Framework Attributes	Open source code release Deliverable Workshop for industry and Government participants. Peer reviewed papers on approach.
KTTD 10B-2021	Dr. Margaret Penner	Automated characterization of forest vertical structure using single photon LIDAR	Species Prediction Using Single Photon LiDAR Results from the Algonquin Park Forest Automated characterization of forest canopy vertical layering for predicting forest inventory attributes by layer using airborne LiDAR data
KTTD 14B-2021	Dr. Mahadev Sharma	Developing G&Y models for white pine and white spruce plantations	Taper equations for Sw and Pw plantations Volume equations for Sw and Pw plantations Journal paper on diameter growth of white spruce and white pine plantations Implementation and transfer of final model products in MIST
KTTD 16B-2021	Craig Robinson	FIM Compliant LiDAR Inventory of Selected Areas in the Romeo Malette Forest	Webinar July 13, 2023 entitled LiDAR Derived Individual Tree, Hexagon, and Polygonal Forest Inventories - Romeo Malette Forest Link and login information to where the individual tree (ITI), hexagon (EFI), and polygon (FRI) inventories and the LiDAR ArcGIS Add-In ftp.forsite.ca user: FFT-LiDAR pass: GKTB2valuers= KTTD 16B-2021 Final Report
KTTD 19B-2021	Dr. Kara Webster	Advancing Digital Soil Mapping tools in support of forest resource inventory, planning and decision making	Yanni, S., Webster, K.L. 2024. Forest Soil Datasets in Ontario – Fact Sheets. CFS Information Report. 75pp Paré, D., Bognounou, F., Emilson, E.J., Laganière, J., Leach, J., Mansuy, N., Martineau, C., Norris, C., Venier, L. and Webster, K., 2024. Connecting forest soil properties with ecosystem services: Toward a better use of digital soil maps—A review. Soil Science Society of America Journal. https://acsess.onlinelibrary.wiley.com/doi/full/10.1002/saj2.20705 Fleming, R.L., Uhlig, P.W., Morris, D.M., Kwiaton, M., Baldwin, K.A., Hazlett, P.W., Webster, K.L. and Chapman, K.A., 2023. A quantitative approach to defining soil nutrient regimes within ecosystem classifications for Northwestern Ontario. Canadian Journal of Forest Research, 53, 620-641.https://doi.org/10.1139/cjfr-2022-0296. CFS Group of Analytical Labs (edited by Paré, D., Webster, K., and Norris, C. 2023. Collecting, analysing and storing forest soil data and samples in the age of big data. A guide for researchers and field practitioners. Laurentian Forestry Centre publication. ISBN: Fo4-211/2023E-PDF 978-0-660-47983-5. https://scf.rncan.gc.ca/publications?id=40929. Blackford, C., Heung, B. and Webster, K.L., 2022. Incorporating spatial uncertainty maps into soil sampling improves digital soil mapping classification accuracy in Ontario, Canada. Geoderma Regional, p.e00495. https://doi.org/10.1016/j.geodrs.2022.e00495 Digital soil mapping Newsletter Blackford, C., Heung, B., Baldwin, K., Fleming, R., Hazlett, P., Morris, D.M., Uhlig, P., Webster, K.L. 2021. Digital Soil Mapping workflow for forest resource applications: A case study in the Hearst Forest, Ontario. Canadian Journal of Forest Research 51: 59–77. https://doi.org/10.1139/cjfr-2020-0066 Fact Sheet- Forest Ecosystem Classification/Ecosystem Land Classification Fact Sheet – Forest Soil Datasets Summary KTTD 19B-2021 Final Report
KTTD 20B-2021	Murray Woods	Accelerating the implementation of enhanced forest inventories in Ontario	Acceleration _Algonquin Park Report_July16_22 Algonquin Park LiDAR Model Calibration Results_July19_2022 DogR Matawin LiDAR Model Calibration Results_Feb6_22 Romeo Malette Project Results Nov5_2021 Acceleration _DogRiverMatawin Report_Mar8_22 Acceleration _RomeoMalette Report_March 15 FrenchSevern T2 Final Report_Dec1 -> Plot compilation code and documentation posted to GITHUB development and calibration plot

Round 2

Approved project summaries can be found here and deliverabled linked in the table below, when available.

Project name

Applicant

Deliverables

Using the eFRI to predict hardwood selection stands in the Bancroft Minden Forest

Bancroft-Minden Forest Company

Project cancelled by applicant

Seasonal Operability Predictor Tool for Forest Operations

Resource Innovations Inc.

Seasonal Operability Predictor Toolbox (.tbx ArcGIS file) Contact office for file

Seasonal Operability Predictor Tool for Forest Operations - Technical Operations Guide (.pdf)

Overlay Raster (.lyr ArcGIS file) Contact office for file

WebEx Presentation:

Forestry Futures Trust Committee KTTD Round 2 Technology Transfer Presentations-20210211 1731-3

Password: bVMP2Q8P Presentation

Modeling post-fire residual shoreline forest pattern

MNRF

Final Report: Newax, Md.S., Mackereth, R.W., Mallik, A.U., McCormick, D., 2020. How much

boreal lake shoreline is burned by wildfire? Implications for emulating natural disturbance in

riparian forest management. For. Ecol. Manag. 473, 1-9.

WebEx Presentation

Forestry Futures Trust Committee KTTD Round 2 Technology Transfer Presentations-20210311 1725-3

Password tEpARPg8 Presentation

FRIHub: A Discovery Portal for FRI Data and Products

Lim Geomatics Inc

WebEx Presentation for both projects

Forestry Futures Trust Committee KTTD Round 2 Technology Transfer Presentations-20210325 1601-2

Password wYwqBWX7

ITESTA - Individual Tree Extraction and Species Typing Analysis

Lim Geomatics Inc

one link for 2 projects

Next Generation eFRI Ground Data Collection App

ArborData Consulting Ltd

Final Report - Next Generation eFRI Mobile Application (.pdf)

[report contains links to the eLiDAR App (located on Github) and a downloadable Android version of eLiDAR]

WebEx Presentation:

Forestry Futures Trust Committee KTTD Round 2 Technology Transfer Presentations-20210211 1701-2

password :6Xa94cPt Presentation

Development of an enhanced operational forest inventory based on multispectral imagery and 3D point data.

KBM Resources Group

Withdrawn

eFRI Accuracy Assessment and Change Update Approaches

University of British Columbia

Final Report - Development of a Forest Inventory using 2018 Single Photon LiDAR and Assessing Decadal Forest Change (.pdf)

WebEx Presentation:

Forestry Futures Trust Committee KTTD Round 2 Technology Transfer Presentations-20210318 1600-2

Password xFdqdWi4 Presentation

Scoping an enhanced G&Y program to complement the eFRI

Forest Analysis Ltd.

Final Report - The Ontario Growth and Yield Program Status and Needs - Report to the Forestry Futures Trust Committee (.pdf)

Ontario Growth & Yield Status and Needs Final Report (.pptx)

An analysis of machine learning methodologies for determining stand level attributes.

KBM Resources Group

Report pending

Enhancing Forest Inventory with Terrestrial LiDAR

Overstory Consultants

Final Report - Enhancing Forest Inventory with TLiDAR (.pdf)

Science Insights Seminar Feb. 6, 2019 - Enhancing Growth and Yield Data Collection and Forest Resource Inventory with Terrestrial LiDAR https://mnrfscience.adobeconnect.com/psmsc7kvqsx0/

WebEx Presentation:

Forestry Futures Trust Committee KTTD Round 2 Technology Transfer Presentations-20210311 1701-2

Password mDnsShb2 Presentation

Exploring the innovation potential of single photon LiDAR for Ontario’s eFRI

Canadian Institute of Forestry

Final Report - Exploring the Innovation Potential of Single Phton LiDAR for Ontario's eFRI (.pdf)

Appendix C Part 1 2018 AFRIT SPL Inventory Field Protocols (.pdf)

Appendix C Part 2 Small Tree Sampling Protocol (.pdf)

Appendix C Part 3 Validation Data Collection Protocols for Petawawa Research Forest (.pdf)

Appendix D Penner Petawawa Research Forest SPL Final Report (.pdf)

PRF_CNL_SPL_EFI_layers

PRFCNL_dtm_2018.tar.gz

CIF/IFC Electronic Lecture Feb. 6, 2019 - Remote Sensing Tools and Approaches to eFRI - an Ontario &

National Snapshot pdf and http://cif-ifc.adobeconnect.com/ptu6q4capftm/

Article in Canadian Institute of Forestry membership magazine: CIF. Strong research collaborations are key in exploring the innovation potential of new technologies

for the forest sector: New data for mapping the terrain surface. The Leader, Spring 2020, pp. 20-23.

English copy: http://www.cif-ifc.org/wp-content/uploads/2020/05/20200315-CIF-The-Leader-8.5x11-EN-spreads-DIGITAL.pdf

French Copy: http://www.cif-ifc.org/wp-content/uploads/2020/05/20200315-CIF-The-Leader-8.5x11-FR-spreads-DIGITAL.pdf

Evaluating the capacity of single photon lidar for terrain characterization
under a range of forest conditions.pdf

The Forestry Chronicle • 23 February 2021 • Assessing single photon LiDAR for operational implementation of an enhanced forest inventory in diverse mixedwood forests- https://pubs.cif-ifc.org/doi/10.5558/tfc2021-009

WebEx presentation:

Forestry Futures Trust Committee KTTD Round 2 Technology Transfer Presentations-20210218 1700-2

password Jxz7gTbF Presentation