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

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

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

Kuvaus

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.
Alkuperäiskielienglanti
LehtiInternational Journal of Applied Earth Observation and Geoinformation
Vuosikerta80
Sivut102-114
Sivumäärä13
ISSN0303-2434
DOI - pysyväislinkit
TilaJulkaistu - elokuuta 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

Tieteenalat

  • 1171 Geotieteet
  • Landsat
  • Forest
  • Time series
  • Composite-to-Change
  • Seedling plot
  • Boreal
  • Regeneration

Lainaa tätä

White, Joanne C. ; Saarinen, Ninni ; Wulder, Michael A. ; Kankare, Ville ; Hermosilla, Txomin ; Coops, Nicholas C. ; Holopainen, Markus ; Hyyppä, Juha ; Vastaranta, Mikko. / Assessing spectral measures of post-harvest forest recovery with field plot data. Julkaisussa: International Journal of Applied Earth Observation and Geoinformation. 2019 ; Vuosikerta 80. Sivut 102-114.
@article{eb43b9adfed4401781a0a0541d04fa22,
title = "Assessing spectral measures of post-harvest forest recovery with field plot data",
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.",
keywords = "1171 Geosciences, Landsat, Forest, Time series, Composite-to-Change, Seedling plot, Boreal, Regeneration, Landsat, Forest, Time series, Composite-to-Change, Seedling plot, Boreal, Regeneration, LANDSAT TIME-SERIES, PRIVATELY-OWNED FORESTS, STRUCTURAL DEVELOPMENT, PICEA-ABIES, REFLECTANCE, DISTURBANCE, BOREAL, REGROWTH, REGENERATION, TRENDS",
author = "White, {Joanne C.} and Ninni Saarinen and Wulder, {Michael A.} and Ville Kankare and Txomin Hermosilla and Coops, {Nicholas C.} and Markus Holopainen and Juha Hyypp{\"a} and Mikko Vastaranta",
year = "2019",
month = "8",
doi = "10.1016/j.jag.2019.04.010",
language = "English",
volume = "80",
pages = "102--114",
journal = "International Journal of Applied Earth Observation and Geoinformation",
issn = "1569-8432",
publisher = "Elsevier Scientific Publ. Co",

}

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.; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko.

julkaisussa: International Journal of Applied Earth Observation and Geoinformation, Vuosikerta 80, 08.2019, s. 102-114.

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

TY - JOUR

T1 - Assessing spectral measures of post-harvest forest recovery with field plot data

AU - White, Joanne C.

AU - Saarinen, Ninni

AU - Wulder, Michael A.

AU - Kankare, Ville

AU - Hermosilla, Txomin

AU - Coops, Nicholas C.

AU - Holopainen, Markus

AU - Hyyppä, Juha

AU - Vastaranta, Mikko

PY - 2019/8

Y1 - 2019/8

N2 - 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.

AB - 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.

KW - 1171 Geosciences

KW - Landsat

KW - Forest

KW - Time series

KW - Composite-to-Change

KW - Seedling plot

KW - Boreal

KW - Regeneration

KW - Landsat

KW - Forest

KW - Time series

KW - Composite-to-Change

KW - Seedling plot

KW - Boreal

KW - Regeneration

KW - LANDSAT TIME-SERIES

KW - PRIVATELY-OWNED FORESTS

KW - STRUCTURAL DEVELOPMENT

KW - PICEA-ABIES

KW - REFLECTANCE

KW - DISTURBANCE

KW - BOREAL

KW - REGROWTH

KW - REGENERATION

KW - TRENDS

U2 - 10.1016/j.jag.2019.04.010

DO - 10.1016/j.jag.2019.04.010

M3 - Article

VL - 80

SP - 102

EP - 114

JO - International Journal of Applied Earth Observation and Geoinformation

JF - International Journal of Applied Earth Observation and Geoinformation

SN - 1569-8432

ER -