Remote Sensing Techniques in Monitoring Post-Fire Effects and Patterns of Forest Recovery in Boreal Forest Regions: A Review

Abstract

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.

Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems

“…quired over a single region have allowed for Landsat based time series analysis approaches. Since vegetation indices (or more generally spectral indices) from satellite imagery have been commonly used to monitor, analyze and map temporal and spatial dynamics of post-fire environments (Chu and Guo, 2014), spectral index time series analysis has been a multitemporal procedure particularly useful to monitor post-fire vegetation (Bastos et al, 2011;Chen et al, 2014;Dubovyk et al, 2015;Lanorte et al, 2014;Riaño et al, 2002;van Leeuwen et al, 2010).…”

Standardized Time-Series and Interannual Phenological Deviation: New Techniques for Burned-Area Detection Using Long-Term MODIS-NBR Dataset

“…), which affects differently the values of NBR, NDVI and other spectral indices [41,43]. According to Chu and Guo [44], the environmental variation and the vegetation stratification should be considered to achieve a reasonable operating model for monitoring fire effects. Therefore, burned-area mapping in environments with high natural variability can adopt a flexible approach, considering specific adjustments for each landscape.…”

Development of a New Daily-Scale Forest Fire Danger Forecasting System Using Remote Sensing Data

“…However, it has many positive impacts, such as helping forest regeneration, enriching soil nutrient regimes, killing insects and diseases, etc. [3,4]. In order to suppress fires, Canada has spent in the range of CAD $500 million to $1 billion every year on average during the last decade [1].…”