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Joanne White, Michael Wulder, Geordie HobartCanadian Forest Service
Txomin Hermosilla, Nicholas CoopsUniversity of British Columbia
Landsat Science Team MeetingJuly 11-13, 2017
Demonstrating Landsat’s capacity to inform forest monitoring, reporting,
and policy development
Victoria
How big are Canada’s forests?
Canada’s forests: Context
• Area of Canada = 998.4 million ha• 60% forested ecosystems• 40% treed• 20% managed
• 10% of global forests; 30% of global boreal forests
• 93% of forest land is publicly owned• 77% under provincial/territorial jurisdiction (13)
Canada’s forests: Context
Information needs for forest monitoring• GoC has national and international reporting
commitments and obligations, national programs (National Forest Inventory, Carbon Accounting)
• Need information that is synoptic, consistent, spatially explicit, sufficiently detailed to capture anthropogenic impacts, and national in scope
• Long baseline useful to determine trends, define present, and inform future
Motivation
Much needed information is not available or is not available in the required form Better information = better outcomes for
science, policy, and management
It is important for nations to produce and stand behind high quality data products used for science, reporting, and monitoring Proactive: develop and share the narratives
around Canada’s forested ecosystems
Key attributes for Canada’s NFI and Carbon Accounting programs
Basic attributes: Land cover Crown closure Age Species Height Volume Biomass
Disturbance-related attributes:
Pre-disturbance land cover Post-disturbance land cover Disturbance agent Disturbance year Disturbance extent (area) Disturbance intensity
White, J.C., Wulder, M.A., Hobart, G,W., Luther, J.E., Hermosilla, T., Griffiths, P., Coops, N.C., Hall, R.J., Hostert, P., Dyk, A., Guindon. L. 2014. Pixel-based image compositing for large-area dense time series applications and science. Canadian Journal of Remote Sensing, 40(3): 192–212.
What is required to meet this motivation?
Landsat data is key to meeting these information needs Has requisite spatial and temporal
characteristics Objective: Demonstrate operational potential
for Landsat-based national information products over very large areas
Key national outcomes (to date)What do we know now that we did not know before?
Open-access data product for wildfire and harvest (1985-2010) https://opendata.nfis.org/mapserver/nfis-change_eng.html
Key national outcomesWhat do we know now that we did not know before?
25-year, spatially-explicit, national record of forest harvesting activity at 30 m
White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment, 194: 303–321. https://doi.org/10.1016/j.rse.2017.03.035
Key national outcomes What do we know now that we did not know before?
National, spatially-explicit assessment of trends in areas impacted by wildfire and harvest in Canada's forested ecosystems
White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment, 194: 303–321. https://doi.org/10.1016/j.rse.2017.03.035
Characterized trends in forest recovery by disturbance type and ecological regions
Key national outcomes What do we know now that we did not know before?
White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment, 194: 303–321. https://doi.org/10.1016/j.rse.2017.03.035
A spatial framework for assessing relative rates of recovery and vegetation return following stand replacing disturbance Integration with ground plot
information
Key national outcomes What do we know now that we did not know before?
https://doi.org/10.1016/j.foreco.2015.11.015
Key national outcomes (in progress)
Time series of annual land cover Harmonized across sectors (forests, agriculture) Linking land cover change to land use in “transactional
environments” (forest-agriculture interface) Annual forest structure (e.g., height, biomass) Linking samples of airborne LiDAR with Landsat Information for unmanaged forest areas
Time series of forest structure dynamics Extending estimates of forest structure through time
Conclusions
Forest (and terrestrial) monitoring information needs are increasingly complex: Spatially explicit, wall-to-wall, temporally
dense Current and archival Landsat data enable
generation of information products for terrestrial monitoring that otherwise would not be available
Operational potential for large areas needs to be realized and demonstrated to promote uptake
16/801616/52
Thank you!Mike [email protected]
@mikewulder
Publications:
https://www.researchgate.net/profile/Joanne_White2
https://www.researchgate.net/profile/Michael_Wulder
16
This research was undertaken as part of the “National Terrestrial Ecosystem Monitoring System (NTEMS): Timely and detailed
national cross-sector monitoring for Canada” project jointly funded by the Canadian Space Agency (CSA) Government Related Initiatives Program (GRIP) and the Canadian Forest Service (CFS) of Natural
Resources Canada.
Special acknowledgement to:
Joanne [email protected]