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Remote Sensing (RS) Science and Applications in the CFS

Remote Sensing (RS) Science and Applications in the CFS. Presenters: Jeff Dechka, Ron Hall, Mike Wulder. Cornerbrook. CFS RS Investments (2014-15). 1 RES, 1 Other Salary $188K O&M $11 K Leveraging $50K. 1 RES, 2 Other Salary $ 270 K O&M $11K Leveraging $50 K. 1 RES, 2 Other

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Remote Sensing (RS) Science and Applications in the CFS

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  1. Remote Sensing (RS) Science and Applications in the CFS Presenters: Jeff Dechka, Ron Hall, Mike Wulder

  2. Cornerbrook CFS RS Investments (2014-15) 1 RES, 1 Other Salary $188K O&M $11 K Leveraging $50K 1 RES, 2 Other Salary $270K O&M $11K Leveraging $50 K 1 RES, 2 Other Salary $279K O&M $11K Leveraging $70K 4 RES, 4 Other Salary $868K O&M $37K Leveraging $625 K 0 RES, 1 Other Salary $98K O&M $0 Leveraging $115K

  3. CFS’ RS Landscape • Staff • 7 RES • 10 Professional • Salaries • RES Salary - $778K • Professional Salary - $926K • A-Base O&M - $70K (in NFIA) • OGD Leverage - $910K (Funding)

  4. Main Federal Collaborators • Canadian Space Agency (CSA) • Financial support for applications development • Environment Canada (EC) • UNFCCC and NIR (GHG) reporting • Support EC on forestry related to the Group on Earth Observations (GEO) • collaboration with EC MSC on sharing fire information and land cover data • Agriculture and Agri-foods Canada (AAFC) • NFI, NIR, UNFCCC through deforestation/land use/cover • NRCan-ESS • Data preparation and automation • Scientific collaboration (e.g. Fire)

  5. Why CFS Relies on RS Solutions • Canada’s vast and diverse forests present challenges for measuring and monitoring. • 1000M ha of land • 600M ha forest ecosystem • 400M ha forested lands • Opportunity for Innovative Solutions • Cost effective, repeatable analyses of forest status and trends • RS is an enabling tool for a variety of CFS work • NFI, Carbon, Climate Change, Forest Change, CBFA, Enhanced Inventory, Markets, SoF, Fire, etc. • Supports and connects industry, academia, federal, provincial and territorial partners

  6. National Forest Inventory • RS provides timely and up-to-date information to help meet Canada's national and international reporting commitments (SoF, FRA, UNFCCC, CBD) • CFS RS research focuses on new RS methodologies to enhance the NFI Selected RS Solutions - 1 Map in SoF 2015 Generated using RS and NFI

  7. Selected RS Solutions - 2 • Multisource Vegetation Inventory in NWT • Integrates field, aerial, LiDAR, and satellite data for forest inventory • Central for carbon accounting, NFI update, NWT inventory needs & SFM indicators • CFS research with NoFC, LFC & PFC on national maps

  8. Selected RS Applications - 3 • FireMARS: National Burned Area Composite • Annual mapping of burned areas since 2004 • Input to Carbon Accounting to compute C emissions • Integrating with NFI • Future new forest change indicator on area burned • Input to EC Nat’l disturbance • Result of NRCan CFS-ESS collaboration.

  9. Cumulative Forest Changes 2000-2011

  10. Selected RS Applications - 4 Canopy Model Elevation Model • Enhanced Forest Inventory (EFI) • Improved industry decision-making • Tree heights • Volume • Biomass • Merchantable timber • Road development • CWFC, AFC (Corner Brook) and PFC

  11. Selected RS Applications - 5 • Deforestation Mapping and Reporting • Changes in land use • Various RS data sets • Supports NFI and carbon • UNFCCC, EC NIR • SoF, provincial/territorial summaries. • Supported BC’s zero deforestation policy.

  12. Benefits to CFS • Supports a variety of activities in CFS – Climate change, markets, ecosystems, disturbances (fire, insects, anthropogenic) etc. • Forest cover change • Deforestation can be mapped at a regional or national scale. • Fire can be mapped annually (National Burn Area Composite). • Disturbances from 1980’s to present. • Collaboration with the provinces on NFI permits leveraging $2M of RS data (aerial photography, satellite imagery) • Enhanced Forest Inventory • CWFC case study - LiDAR saved $800K for Romeo Malette Forest (Timmins, Ont.) • Other companies moving towards LiDAR. 12

  13. Summary • RS is indispensable and evolutionary • Important to CFS • Needed for EIO, DIO, Innovation, Markets IO’s (fire, pest, anthropogenic change), and for Public Safety (fire) • Supports domestic and international reporting • Future opportunities and challenges • CFS will more heavily rely on this tool in the future • Diversity and volume of data is rapidly increasing • Open data allows opportunities not previously possible • Data fusion from multiple RS and Geographic Information System (GIS) datasets • National time series of Canada’s forests • Big Data challenge: computing, data management and specialized staff expertise • Resource challenges

  14. Back Pocket Slides Only

  15. Land Cover: Earth Observation for the Sustainable Development of Forests (EOSD) WRS > 1200 images 480 WRS with > 10% forest cover 800 MHa mapped Landsat 7 ETM+ Circa 2000 imagery 23 land cover classes Completed 2006 Wulder, M. A., White, J.C., Cranny, M., Hall, R.J., Luther, J.E., Beaudoin, A., Goodenough, D.G., Dechka, J.A. 2008. Monitoring Canada’s Forests Part 1: Completion of the EOSD Land Cover Project. Canadian Journal of Remote Sensing, 34(6): 549–562.

  16. CFS RS Investments

  17. What are the forest fragmentation patterns of Canada’s forests? 95 metrics 4 spatial extents: 1:250,000 NTS 1:50,000 NTS 1 km x 1 km 1 ha x 1 ha http://tree.pfc.forestry.ca/ Wulder, M.A., White, J.C., Han, T., Coops, N.C., Cardille, J.A., Holland, T., Grills, D. 2008. Monitoring Canada’s forests. Part 2: National forest fragmentation and pattern. Canadian Journal of Remote Sensing, 34: 563–584.

  18. Method and product to annually map severe forest disturbances Photo credit: The Canadian encyclopedia Photo credit: NRCan-CFS Photo credit: NRCan-CFS Goals 1- Improve the original CCRS approach to detect severe disturbances (type, intensity) 2- Implement it operationally (starting from 2000 to 2011 …) CFS & CCRS Forest change product CFS CCRS • North American Land Change Monitoring System (NALCMS) • NFI • Carbon modelling (NFCMARS) • Many others CFS: Luc Guindon, Pierre Bernier, André Beaudoin and Ron Hall CCRS: Darren Pouliot and Rasim Latifovic

  19. Detection Inventory polygons Fire Harvesting Floods Annual change detection (from 2000 to 2011) CCRS collaboration

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