Abstract
The frequency and severity of forest fires, coupled with changes in spatial and temporal precipitation and temperature patterns, are likely to severely affect the characteristics of forest and permafrost patterns in boreal eco-regions. Forest fires, however, are also an ecological factor in how forest ecosystems form and function, as they affect the rate and characteristics of tree recruitment. A better understanding of fire regimes and forest recovery patterns in different environmental and climatic conditions will improve the management of sustainable forests by facilitating the process of forest resilience. Remote sensing has been identified as an effective tool for preventing and monitoring forest fires, as well as being a potential tool for understanding how forest ecosystems respond to them. However, a number of challenges remain before remote sensing practitioners will be able to better understand the effects of forest fires and how vegetation responds afterward. This article attempts to provide a comprehensive review of current research with respect to remotely sensed data and methods used to model post-fire effects and forest recovery patterns in boreal forest regions. The review reveals that remote sensing-based monitoring of post-fire effects and forest recovery patterns in boreal forest regions is not only limited by the gaps in both field data and remotely sensed data, but also the complexity of far-northern fire regimes, climatic conditions and environmental conditions. We expect that the integration of different remotely sensed data coupled with field campaigns can provide an important data source to support the monitoring of post-fire effects and forest recovery patterns. Additionally, the variation and stratification of pre- and post-fire vegetation and environmental conditions should be considered to achieve a reasonable, operational model for monitoring post-fire effects and forest patterns in boreal regions.
Highlights
Forests are subject to a variety of disturbances that are themselves strongly influenced by climate change and human activities [1]
Even though several of these studies were not conducted in post-fire boreal zones, they are included in this review, because their remote sensing techniques can be potentially applied to post-fire boreal forest research
-Diverse omission and commission errors in different methods and ecosystems; -Result depends on the selection of the training dataset; -Proposed algorithms may be inapplicable to other study sites; -Required composite images of pre-fire year, fire year and post-fire year to account for variations of fire regimes and vegetation phenology
Summary
Forests are subject to a variety of disturbances that are themselves strongly influenced by climate change and human activities [1]. The ecological effects of boreal forest fires are highly variable, difficult to predict and are influenced by fire regimes, vegetation cover, permafrost condition, topography, soil properties and local climate [7,13,14,15] An example of this is the potential shift in dominant evergreen conifer forests to deciduous forests in North America due to high fire severity and frequency in the last two decades [16]. This paper will first examine the terminology and the ecological impacts of fire in controlling the recovery of post-fire boreal forest ecosystems, will look at the recent remote sensing methods and data that have been applied in the literature for mapping the post-fire effects of burned areas and burn severity in boreal forest regions. It examines existing remote sensing studies on post-fire effects and forest recovery patterns, which allows for the anticipation of some sources of uncertainties and limitations of such research, suggests opportunities and future directions of monitoring post-fire boreal forests through the use of remote sensing
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