Structural Factors Driving Boreal Forest Albedo in Finland. Kuusinen, N., Stenberg, P., Korhonen, L., Rautiainen, M., & Tomppo, E. 175:43–51.
Structural Factors Driving Boreal Forest Albedo in Finland [link]Paper  doi  abstract   bibtex   
[Highlights] [::] Analyzed factors driving fine spatial resolution changes in boreal forest albedo. [::] Based on field plot measurements, ALS data and albedos from Landsat-5 TM data. [::] Tree species, forest structure and understory affected albedo. [::] The dependency of albedo on forest structural variables was species-specific. [::] At high volumes albedo saturated and was mainly governed by tree species. [Abstract] Understanding the influence of forest structure on forest albedo, and thus on the energy exchange between the forest and the atmosphere, is urgently needed in areas with large forest cover and active forest management. Fine resolution albedo retrievals enable quantifying the relationships between forest variables and albedo also in patchy landscapes, such as in the managed forests in Fennoscandia. In this study, field plot data, airborne laser scanning (ALS) data and high resolution satellite albedo retrievals from Landsat were used to investigate the main factors influencing forest albedo in Central Finland in midsummer. Tree species, forest structure and understory (ground) vegetation composition all influenced forest albedo. The tree species-specific models were estimated on a subpixel scale by utilizing information on the proportions of each species within a plot. Tree species considerably improved the albedo prediction when added to a model containing only a structural variable, whereas a further addition of the site fertility class as a proxy of understory vegetation composition only slightly improved the model. Albedo decreased with increasing volume of growing stock, but the decrease leveled off at high volumes. The albedo of plots with high volume was instead mainly governed by tree species and was the lowest for Norway spruce, intermediate for Scots pine and highest for broadleaved species. Norway spruce albedo decreased almost linearly with increasing mean tree height. ALS-derived canopy cover explained fairly well the variation in albedo in the visible region, but the total shortwave albedo was better predicted by ALS-derived tree height. [Excerpt: Conclusions] Detecting the factors driving shortwave albedo change in boreal forests is important for assessing the influence of forest management actions on climate. High resolution satellite albedo data were used in this study to improve the spatial match of forest variables and albedo data in a patchy landscape compared to the use of coarse spatial resolution satellite albedos. Unmixing analysis was used to estimate species-specific relationships between forest variables and albedo. The coniferous, particularly spruce, albedo decreased almost linearly with increasing mean tree height. As the increase in height slowed down as the volume of growing stock increased, the decrease of albedo with increasing volume saturated at higher volumes. The albedo of spruce was higher than that of pine in the beginning of the rotation, but after the volume of growing stock had reached approximately 70 m3ha- 1 the reverse was true. The higher albedo for young spruce compared to young pine forests is at least partly explained by the on average higher site fertility and consequent differences in understory vegetation and site preparation. Broadleaved tree species had on average clearly higher albedo than coniferous species. For example, in stands with growing stock of 300 m3ha- 1, the broadleaved albedo was 0.038 units higher than pine and 0.053 units higher than spruce albedo. The results indicate that at average to large volumes of growing stock, moderate thinnings or selection cuttings might not have a remarkable effect on albedo, and the choice of tree species together with consideration of the rotation length would be the simplest ways to influence albedo through forest management. There are, however, limitations to the choice of tree species, understory vegetation, and stand structure, and therefore on the possibilities of modifying forest albedo caused by, for example, site fertility and geographical location. The simple models used here were not able to explain all the variation in forest albedo. This is not a surprise considering the possible error sources and the structural variability (e.g. grouping of trees, understory trees) in forest stands that could not be described by the used mean attributes. However, information on the effects of the commonly measured forest inventory variables on albedo is needed for practical purposes, such as for the evaluation of the influence of different management options on albedo and the subsequent decision making.
@article{kuusinenStructuralFactorsDriving2016,
  title = {Structural Factors Driving Boreal Forest Albedo in {{Finland}}},
  author = {Kuusinen, Nea and Stenberg, Pauline and Korhonen, Lauri and Rautiainen, Miina and Tomppo, Erkki},
  date = {2016-03},
  journaltitle = {Remote Sensing of Environment},
  volume = {175},
  pages = {43--51},
  issn = {0034-4257},
  doi = {10.1016/j.rse.2015.12.035},
  url = {http://mfkp.org/INRMM/article/13928353},
  abstract = {[Highlights]

[::] Analyzed factors driving fine spatial resolution changes in boreal forest albedo. [::] Based on field plot measurements, ALS data and albedos from Landsat-5 TM data. [::] Tree species, forest structure and understory affected albedo. [::] The dependency of albedo on forest structural variables was species-specific. [::] At high volumes albedo saturated and was mainly governed by tree species.

[Abstract]

Understanding the influence of forest structure on forest albedo, and thus on the energy exchange between the forest and the atmosphere, is urgently needed in areas with large forest cover and active forest management. Fine resolution albedo retrievals enable quantifying the relationships between forest variables and albedo also in patchy landscapes, such as in the managed forests in Fennoscandia. In this study, field plot data, airborne laser scanning (ALS) data and high resolution satellite albedo retrievals from Landsat were used to investigate the main factors influencing forest albedo in Central Finland in midsummer. Tree species, forest structure and understory (ground) vegetation composition all influenced forest albedo. The tree species-specific models were estimated on a subpixel scale by utilizing information on the proportions of each species within a plot. Tree species considerably improved the albedo prediction when added to a model containing only a structural variable, whereas a further addition of the site fertility class as a proxy of understory vegetation composition only slightly improved the model. Albedo decreased with increasing volume of growing stock, but the decrease leveled off at high volumes. The albedo of plots with high volume was instead mainly governed by tree species and was the lowest for Norway spruce, intermediate for Scots pine and highest for broadleaved species. Norway spruce albedo decreased almost linearly with increasing mean tree height. ALS-derived canopy cover explained fairly well the variation in albedo in the visible region, but the total shortwave albedo was better predicted by ALS-derived tree height.

[Excerpt: Conclusions]

Detecting the factors driving shortwave albedo change in boreal forests is important for assessing the influence of forest management actions on climate. High resolution satellite albedo data were used in this study to improve the spatial match of forest variables and albedo data in a patchy landscape compared to the use of coarse spatial resolution satellite albedos. Unmixing analysis was used to estimate species-specific relationships between forest variables and albedo. The coniferous, particularly spruce, albedo decreased almost linearly with increasing mean tree height. As the increase in height slowed down as the volume of growing stock increased, the decrease of albedo with increasing volume saturated at higher volumes. The albedo of spruce was higher than that of pine in the beginning of the rotation, but after the volume of growing stock had reached approximately 70 m3ha- 1 the reverse was true. The higher albedo for young spruce compared to young pine forests is at least partly explained by the on average higher site fertility and consequent differences in understory vegetation and site preparation. Broadleaved tree species had on average clearly higher albedo than coniferous species. For example, in stands with growing stock of 300 m3ha- 1, the broadleaved albedo was 0.038 units higher than pine and 0.053 units higher than spruce albedo. The results indicate that at average to large volumes of growing stock, moderate thinnings or selection cuttings might not have a remarkable effect on albedo, and the choice of tree species together with consideration of the rotation length would be the simplest ways to influence albedo through forest management. There are, however, limitations to the choice of tree species, understory vegetation, and stand structure, and therefore on the possibilities of modifying forest albedo caused by, for example, site fertility and geographical location. The simple models used here were not able to explain all the variation in forest albedo. This is not a surprise considering the possible error sources and the structural variability (e.g. grouping of trees, understory trees) in forest stands that could not be described by the used mean attributes. However, information on the effects of the commonly measured forest inventory variables on albedo is needed for practical purposes, such as for the evaluation of the influence of different management options on albedo and the subsequent decision making.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13928353,~to-add-doi-URL,albedo,anthropic-feedback,boreal-forests,climate,feedback,finland,forest-management,forest-resources,ground-vegetation,tree-species,understorey}
}
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