Joanne C. White. (2024). Characterizing forest recovery following stand-replacing disturbances in boreal forests: contributions of optical time series and airborne laser scanning data. Silva Fennica vol. 58 no. 2 article id 23076. https://doi.org/10.14214/sf.23076

Keywords: regeneration; fire; time series; Landsat; harvest; forest change

Highlights: Remote sensing contributions to monitoring of post-disturbance forest recovery in the boreal are synthesized; Definitions of forest recovery need to be clear and measurable and will vary by application; Landsat time series represent a significant innovation in recovery assessments, but the boreal biome is underrepresented in this research; Opportunities for future research directions and priorities are highlighted.

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The success and rate of forest regeneration following disturbance has implications for sustainable forest management, climate change mitigation, and biodiversity, among others. Systematic monitoring of forest regeneration over large and often remote areas of the boreal forest is challenging. The use of remotely sensed data to characterize post-disturbance recovery in the boreal forest has been an active research topic for more than 30 years. Innovations in sensors, data policies, curated data archives, and increased computational power have enabled new insights into the characterization of post-disturbance forest recovery, particularly following stand-replacing disturbances. Landsat time series data have emerged as an important data source for post-disturbance forest recovery assessments, with Landsat’s 40-year archive of 30-m resolution data providing consistent observations on an annual time step and enabling retrospective capacity to establish spatially explicit recovery baselines. The application of remote sensing for monitoring post-disturbance forest recovery is a rapidly growing area of research globally; however, despite the large amount of disturbance and the disproportionate effects of climate change in the boreal, the boreal biome is relatively underrepresented in the remote sensing forest recovery literature. Herein, the past and present contributions of optical time series and airborne laser scanning data to the characterization of forest recovery in boreal forests are highlighted, and future research priorities are identified.

White, Canadian Forest Service, Pacific Forestry Centre, Natural Resources Canada, 506 West Burnside Road, Victoria, B.C., V8Z 1M5, Canada https://orcid.org/0000-0003-4674-0373 E-mail: joanne.white@nrcan-rncan.gc.ca

Category : Research note

article id 9986, category Research note

Ninni Saarinen, Joanne C. White, Michael A. Wulder, Annika Kangas, Sakari Tuominen, Ville Kankare, Markus Holopainen, Juha Hyyppä, Mikko Vastaranta. (2018). Landsat archive holdings for Finland: opportunities for forest monitoring. Silva Fennica vol. 52 no. 3 article id 9986. https://doi.org/10.14214/sf.9986

Keywords: National Forest Inventory; satellite; Landsat time series

Highlights: The 45-year Landsat archive contained 30 076 images for Finland by December 31, 2017; 16.3% of these were acquired within ±30 days of August 1 (northern hemisphere summer), have <70% cloud cover, and a 30 m spatial resolution; Using time series analyses, these data provide unique information that complements other datasets available for forest monitoring and assessment in Finland.

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There is growing interest in the use of Landsat data to enable forest monitoring over large areas. Free and open data access combined with high performance computing have enabled new approaches to Landsat data analysis that use the best observation for any given pixel to generate an annual, cloud-free, gap-free, surface reflectance image composite. Finland has a long history of incorporating Landsat data into its National Forest Inventory to produce forest information in the form of thematic maps and small area statistics on a variety of forest attributes. Herein we explore the spatial and temporal characteristics of the Landsat archive in the context of forest monitoring in Finland. The United States Geological Survey Landsat archive holds a total of 30 076 images (1972–2017) for 66 scenes (each 185 km by 185 km in size) representing the terrestrial area of Finland, of which 93.6% were acquired since 1984 with a spatial resolution of 30 m. Approximately 16.3% of the archived images have desired compositing characteristics (acquired within August 1 ±30 days, <70% cloud cover, 30 m spatial resolution). Data from the Landsat archive can augment forest monitoring efforts in Finland, provide new information for science and applications, and enable retrospective, systematic analyses to characterize the development of Finnish forests over the past three decades. The capacity to monitor trends based upon this multi-decadal record with the addition of new measurements is of benefit to multisource inventories and offers nationally comprehensive spatially-explicit datasets for a wide range of stakeholders and applications.

Saarinen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland; School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0003-2730-8892 E-mail: ninni.saarinen@helsinki.fi
White, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland; Canadian Forest Service, (Pacific Forestry Center), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada http://orcid.org/0000-0003-4674-0373 E-mail: joanne.white@canada.ca
Wulder, Canadian Forest Service, (Pacific Forestry Center), Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada https://orcid.org/0000-0002-6942-1896 E-mail: mike.wulder@canada.ca
Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: annika.kangas@luke.fi
Tuominen, Natural Resources Institute Finland (Luke), Bioeconomy and environment, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: sakari.tuominen@luke.fi
Kankare, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ville.kankare@helsinki.fi
Holopainen, Department of Forest Sciences, University of Helsinki, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: markus.holopainen@helsinki.fi
Hyyppä, Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02431 Masala, Finland E-mail: juha.hyyppa@nls.fi
Vastaranta, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland https://orcid.org/0000-0001-6552-9122 E-mail: mikko.vastaranta@uef.fi

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