Assessing spectral measures of post-harvest forest recovery with field plot data

White, Joanne C. Saarinen, Ninni Wulder, Michael A. Kankare, Ville Hermosilla, Txomin Coops, Nicholas C. Hyyppa, Juha Vastaranta, Mikko Holopainen, Markus

Assessing spectral measures of post-harvest forest recovery with field plot data

White, Joanne C. 1Saarinen, Ninni 2Wulder, Michael A. 1Kankare, Ville 2Hermosilla, Txomin 1Coops, Nicholas C. 3Hyyppa, Juha 4Vastaranta, Mikko 5Holopainen, Markus2
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作者信息

  • 1. Nat Resources Canada, Canadian Forest Serv, Pacific Forestry Ctr, 506 West Burnside Rd, Victoria, BC V8Z 1M5, Canada
  • 2. Univ Helsinki, Dept Forest Sci, POB 27, FIN-00014 Helsinki, Finland
  • 3. Univ British Columbia, Fac Forestry, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
  • 4. Natl Land Survey Finland, Finnish Geospatial Res Inst FGI, Dept Remote Sensing & Photogrammetry, Geodeetinrinne 2, Masala 02431, Finland
  • 5. Univ Eastern Finland, Sch Forest Sci, POB 111, Joensuu 80101, Finland
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Abstract

Information regarding the nature and rate of forest recovery is required to inform forest management, monitoring, and reporting activities. Delayed establishment or return of forests has implications to harvest rotations and carbon uptake, among others, creating a need for spatially-explicit, large-area, characterizations of forest recovery. Landsat time series (LTS) has been demonstrated as a means to quantitatively relate forest recovery, noting that there are gaps in our understanding of the linkage between spectral measures of forest recovery and manifestations of forest structure and composition. Field plots provide a means to better understand the linkage between forest characteristics and spectral recovery indices. As such, from a large set of existing field plots, we considered the conditions present for the year in which the co-located pixel was considered spectrally recovered using the Years to Recovery (Y2R) metric. Y2R is a long-term metric of spectral recovery that indicates the number of years required for a pixel to return to 80% of its pre-disturbance Normalized Burn Ratio value. Absolute and relative metrics of recovery at 5 years post-disturbance were also considered. We used these three spectral recovery metrics to predict the stand development class assigned by the field crew for 284 seedling plots with an overall accuracy of 73.59%, with advanced seedling stands more accurately discriminated (omission error, OE = 15.74%) than young seedling stands (OE = 49.84%). We then used field-measured attributes (e.g. height, stem density, dominant species) from the seedling plots to classify the plots into three spectral recovery groups, which were defined using the Y2R metric: spectral recovery in (1) 1-5 years, (2) 6-10 years, or (3) 11-15 years. Overall accuracy for spectral recovery groups was 61.06%. Recovery groups 1 and 3 were discriminated with greater accuracy (producer's and user's accuracies > 66%) than recovery group 2 ( < 50%). The top field-measured predictors of spectral recovery were mean height, dominant species, and percentage of stems in the plot that were deciduous. Variability in stand establishment and condition make it challenging to accurately discriminate among recovery rates within 10 years post-harvest. Our results indicate that the long-term metric Y2R relates to forest structure and composition attributes measured in the field and that spectral development post-disturbance corresponds with expectations of structural development, particularly height, for different species, site types, and deciduous abundance. These results confirm the utility of spectral recovery measures derived from LTS data to augment landscape-level assessments of post-disturbance recovery.

Key words

Landsat/Forest/Time series/Composite-to-Change/Seedling plot/Boreal/Regeneration

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出版年

2019
International journal of applied earth observation and geoinformation

International journal of applied earth observation and geoinformation

SCI
ISSN:0303-2434
被引量10
参考文献量79
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