Canadian Forest Service Publications
Annual mapping of large forest disturbances across Canada’s forests using 250 m MODIS imagery from 2000 to 2011. 2014. Guindon, L.; Bernier, P.Y.; Beaudoin, A.; Pouliot, D.; Villemaire, P.; Hall, R.J.; Latifovic, R.; St-Amant, R. Can. J. For. Res. 44:1545-1554.
Available from: Laurentian Forestry Centre
Catalog ID: 35803
CFS Availability: PDF (request by e-mail)
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Disturbances such as fire and harvesting shape forest dynamics and must be accounted for when modelling forest properties. However, acquiring timely disturbance information for all of Canada's large forest area has always been challenging. Therefore, we developed an approach to detect annual forest change resulting from fire, harvesting, or flooding using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery at 250 m spatial resolution across Canada and to estimate the within-pixel fractional change (FC). When this approach was applied to the period from 2000 to 2011, the accuracy of detection of burnt, harvested, or flooded areas against our validation dataset was 82%, 80%, and 85%, respectively. With FC, 77% of the area burnt and 82% of the area harvested within the validation dataset were correctly identified. The methodology was optimized to reduce the commission error but tended to omit smaller disturbances as a result. For example, the omitted area for harvest blocks greater than 80 ha was less than 14% but increased to between 38% and 50% for harvest blocks of 20 to 30 ha. Detection of burnt and harvested areas in some regions was hindered by persistent haze or cloud cover or by insect outbreaks. All resulting data layers are available as supplementary material.
Plain Language Summary
Canada’s managed forests, most of which are found in the boreal forest, cover close to 230 million hectares. On average, forest fires burn 1% of this land annually, and annual harvesting covers 0.5%. These disturbances are part of the natural dynamics of these forests and must be taken into account when developing models for predicting forest attributes. Although several remote sensing tools already exist, and they cover Canada's forests in whole or in part at resolutions of 1 km or less, few are updated regularly or can be used to identify types of disturbances.
The objective of this project was therefore to develop a tool for annual mapping of large forest disturbances (fire, harvests and flooded areas) for all of Canada, at a resolution of 250 m x 250 m. Applied to MODIS satellite data, the models developed during this project capture between 75% and 80% of fires and harvested areas on the ground. The tool includes annual harvest, fire and flooded area maps from 2000 to 2011 for all of Canada.
This mapping tool makes it possible to rapidly conduct strategic analyses requiring data on recent and past disturbances over large areas, such as the impact of insect outbreaks or vulnerability to climate change.
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