Canadian Forest Service Publications

Assessing spectral measures of post-harvest forest recovery with field plot data. 2019. White, J.C., Saarinen, N., Kankare,V., Wulder, M.A., Hermosilla, T., Coops, N.C., Holopainen, M. Hyyppä, J., Vastaranta, M. Int J Appl Earth Obs Geoinformation 80, 102–114.

Year: 2019

Issued by: Pacific Forestry Centre

Catalog ID: 39899

Language: English

Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.1016/j.jag.2019.04.010

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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)11–15years. 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.

Plain Language Summary

Objective: The overarching goal of this research was to improve our understanding of the linkages between spectral metrics of forest recovery post-harvest—as derived from Landsat Time Series data—and manifestations of forest structure (height and cover) as measured from field plot data. The specific objectives of this study were threefold: (i) Are there significant differences in seedling plot attributes for plots with different rates of spectral recovery?; (ii) Do these attributes have predictive capacity for distinguishing between different rates of recovery?; (iii) Do other, independent spectral metrics, derived from LTS, provide additional predictive capacity for determining recovery rates?

Major findings: • Field plot data used to analyze LTS-derived spectral measures of recovery. • Significant differences in spectral recovery by dominant species and site types. • Recovery groups discriminated with an overall accuracy of 58% using field plots. • Height, dominant species, and ratio of deciduous to coniferous heights were top predictors. • Addition of change magnitude and Recovery Indicator increased accuracy by 20%. • Y2R80% metric provided a robust assessment of forest recovery post-harvest.