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

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dc.contributor University of Helsinki, Department of Forest Sciences en
dc.contributor University of Helsinki, Forest Health Group en
dc.contributor University of Helsinki, Forest Health Group en
dc.contributor University of Helsinki, Department of Forest Sciences en
dc.contributor University of Helsinki, University of Eastern Finland, Joensuu en
dc.contributor.author White, Joanne C.
dc.contributor.author Saarinen, Ninni
dc.contributor.author Wulder, Michael A.
dc.contributor.author Kankare, Ville
dc.contributor.author Hermosilla, Txomin
dc.contributor.author Coops, Nicholas C.
dc.contributor.author Holopainen, Markus
dc.contributor.author Hyyppä, Juha
dc.contributor.author Vastaranta, Mikko
dc.date.accessioned 2019-06-26T09:24:02Z
dc.date.available 2019-06-26T09:24:02Z
dc.date.issued 2019-08
dc.identifier.citation White , J C , Saarinen , N , Wulder , M A , Kankare , V , Hermosilla , T , Coops , N C , Holopainen , M , Hyyppä , J & Vastaranta , M 2019 , ' Assessing spectral measures of post-harvest forest recovery with field plot data ' , International Journal of Applied Earth Observation and Geoinformation , vol. 80 , pp. 102-114 . https://doi.org/10.1016/j.jag.2019.04.010 en
dc.identifier.issn 0303-2434
dc.identifier.other PURE: 124055559
dc.identifier.other PURE UUID: eb43b9ad-fed4-4017-81a0-a0541d04fa22
dc.identifier.other RIS: urn:D91C6DAB40E7D154F36ECB53A408161D
dc.identifier.other WOS: 000470951000010
dc.identifier.other ORCID: /0000-0003-2730-8892/work/58957315
dc.identifier.other ORCID: /0000-0001-6552-9122/work/58958329
dc.identifier.uri http://hdl.handle.net/10138/303478
dc.description.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. sv
dc.format.extent 13
dc.language.iso eng
dc.relation.ispartof International Journal of Applied Earth Observation and Geoinformation
dc.rights en
dc.subject 1171 Geosciences en
dc.subject Landsat en
dc.subject Forest en
dc.subject Time series en
dc.subject Composite-to-Change en
dc.subject Seedling plot en
dc.subject Boreal en
dc.subject Regeneration en
dc.subject Landsat en
dc.subject Forest en
dc.subject Time series en
dc.subject Composite-to-Change en
dc.subject Seedling plot en
dc.subject Boreal en
dc.subject Regeneration en
dc.subject LANDSAT TIME-SERIES en
dc.subject PRIVATELY-OWNED FORESTS en
dc.subject STRUCTURAL DEVELOPMENT en
dc.subject PICEA-ABIES en
dc.subject REFLECTANCE en
dc.subject DISTURBANCE en
dc.subject BOREAL en
dc.subject REGROWTH en
dc.subject REGENERATION en
dc.subject TRENDS en
dc.title Assessing spectral measures of post-harvest forest recovery with field plot data en
dc.type Article
dc.description.version Peer reviewed
dc.identifier.doi https://doi.org/10.1016/j.jag.2019.04.010
dc.type.uri info:eu-repo/semantics/other
dc.type.uri info:eu-repo/semantics/publishedVersion
dc.contributor.pbl
dc.contributor.pbl
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