Mapping and Monitoring Boreal Forest Regrowth Dynamics using Satellite Data Products
Abstract
We used field measurements of canopy light interception (Fpar) and indirectly estimated LAI at numerous burn regrowth sites in interior Alaska to assess satellite data products of these same variables. Fire severity varied across the range of burn sites depending on a number of conditions, and aspen, willow, spruce and herbaceous vegetation has regrown in heterogeneous mixtures, heights and densities. Fpar and LAI estimates were made using handheld instruments in order to characterize spatial and temporal variability in regrowth and to produce Fpar maps using IKONOS and Landsat imagery. A set of custom manufactured solar cells also operated nearly continuously through the active growing seasons. A sensitivity analysis of the indirect canopy LAI estimates with different instruments revealed those factors most critical to accurate retrievals, and allowed us to provide error estimates. Substantial temporal and spatial variability in Fpar across the sites and through time was largely captured by the MODIS Fpar products, but there were notable differences associated with vegetation cover types, ground cover and regrowth stage. There were also differences in vegetation indices based on the higher resolution maps. The MODIS tree cover ("continuous fields") products were effective at capturing differences in burns of various ages across interior Alaska. We also analyzed two AVHRR time series, extracting 10-day Fpar values for the larger burn scars within a Canadian fire database and comparing anomalies with unburned areas in the same ecoregions. Results show significant fire-related anomalies, and associated recovery trajectories. The linkages between boreal fire disturbance and associated regrowth carbon dynamics have direct relevance to numerous ongoing research programs, including the USGCRP North American Carbon Program.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2004
- Bibcode:
- 2004AGUFM.B51B0950G
- Keywords:
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- 1600 GLOBAL CHANGE (New category);
- 1640 Remote sensing