Canadian Forest Service Publications

Multiscale satellite and spatial information and analysis framework in support of a large-area forest monitoring and inventory update. 2009. Wulder, M.A.; White, J.C.; Gillis, M.D.; Walsworth, N.; Hansen, M.C.; Potapov, P. Environmental Monitoring and Assessment 170(1-4): 417-433.

Year: 2009

Available from: Pacific Forestry Centre

Catalog ID: 30386

Language: English

CFS Availability: Order paper copy (free), PDF (download)

Available from the Journal's Web site.
DOI: 10.1007/s10661-009-1243-8

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Abstract

Many countries undertake a national forest inventory to enable statistically valid monitoring in support of national and international reporting of forest conditions and change. Canada’s National Forest Inventory (NFI) program is designed to operate on a 10-year remeasurement cycle, with an interim report produced at the 5-year mid-point. The NFI is a sample-based inventory, with approximately 18,850 2 ×2-km photo plots across the country, distributed on a 20×20-km grid of sample points; these photo plots are the primary data source for the NFI. Capacity to provide annual monitoring information is required to keep policy and decision makers apprised of current forest conditions. In this study, we implemented a multistage monitoring framework and used a Moderate Resolution Imaging Spectroradiometer (MODIS) change product to successfully identify 78% of the changes in forest cover area that were captured with a Landsat change detection approach. Of the NFI photo plots that were identified by both the Landsat and MODIS approaches as having changes in forest cover, the proportion of change area within the plots was similar (R 2 = 0.78). Approximately 70% of the Landsat-derived change events occupied less than 40% of a single MODIS pixel, and more than 90% of the change events of this size were successfully detected with the MODIS product. Finally, MODIS estimates of the proportion of forest cover change at the NFI photo plot level were comparable to change estimates for the ecoregions as a whole (R 2 = 0.95). High-temporal, low-spatial resolution imagery such as MODIS, in combination with other remotely sensed data sources, can provide information on disturbance events within a national forest inventory remeasurement cycle, thereby satisfying the interim information needs of policy and decision makers as well as the requirements of national and international reporting commitments.

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