Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites

We developed a methodology for extending estimates of the presence-absence of trees and several tree species contained in the Canadian National Forest Inventory using nationally consistent Landsat data products. For a prototype boreal forest region of Newfoundland and Labrador, Canada, we modeled an...

Full description

Bibliographic Details
Main Authors: Guy E. I. Strickland, Joan E. Luther, Joanne C. White, Michael A. Wulder
Format: Article
Language:English
Published: Taylor & Francis Group 2020-09-01
Series:Canadian Journal of Remote Sensing
Online Access:http://dx.doi.org/10.1080/07038992.2020.1811083
_version_ 1797661153838497792
author Guy E. I. Strickland
Joan E. Luther
Joanne C. White
Michael A. Wulder
author_facet Guy E. I. Strickland
Joan E. Luther
Joanne C. White
Michael A. Wulder
author_sort Guy E. I. Strickland
collection DOAJ
description We developed a methodology for extending estimates of the presence-absence of trees and several tree species contained in the Canadian National Forest Inventory using nationally consistent Landsat data products. For a prototype boreal forest region of Newfoundland and Labrador, Canada, we modeled and assessed changes in the presence-absence of trees and tree species distributions over a 25-year period. Random Forest models of presence-absence of trees had an overall classification accuracy of 0.87 ± 0.019. For five tree species, overall classification accuracies were: 0.74 ± 0.017 for balsam fir; 0.75 ± 0.028 for black spruce; 0.64 ± 0.085 for trembling aspen; 0.64 ± 0.035 for tamarack; and 0.77 ± 0.041 for white birch. While the proportion of treed area increased by 8.5% over the 25-year period, the area occupied by black spruce declined by 13.5%. The area of balsam fir and white birch increased by 9.9% and 28.2%, respectively, while trembling aspen and tamarack changed by less than 5%. The map products developed and trends observed offer baseline information in support of long-term monitoring of treed area and tree species distributions. The demonstrated methods encourage development of spatially-explicit map products to complement spatially or temporally limited forest inventory datasets.
first_indexed 2024-03-11T18:40:43Z
format Article
id doaj.art-ead02dec06774cd49d9de35ad6f7273a
institution Directory Open Access Journal
issn 1712-7971
language English
last_indexed 2024-03-11T18:40:43Z
publishDate 2020-09-01
publisher Taylor & Francis Group
record_format Article
series Canadian Journal of Remote Sensing
spelling doaj.art-ead02dec06774cd49d9de35ad6f7273a2023-10-12T13:36:23ZengTaylor & Francis GroupCanadian Journal of Remote Sensing1712-79712020-09-0146556758410.1080/07038992.2020.18110831811083Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat CompositesGuy E. I. Strickland0Joan E. Luther1Joanne C. White2Michael A. Wulder3Canadian Forest Service (Atlantic Forestry Centre), Natural Resources CanadaCanadian Forest Service (Atlantic Forestry Centre), Natural Resources CanadaCanadian Forest Service (Pacific Forestry Centre), Natural Resources CanadaCanadian Forest Service (Pacific Forestry Centre), Natural Resources CanadaWe developed a methodology for extending estimates of the presence-absence of trees and several tree species contained in the Canadian National Forest Inventory using nationally consistent Landsat data products. For a prototype boreal forest region of Newfoundland and Labrador, Canada, we modeled and assessed changes in the presence-absence of trees and tree species distributions over a 25-year period. Random Forest models of presence-absence of trees had an overall classification accuracy of 0.87 ± 0.019. For five tree species, overall classification accuracies were: 0.74 ± 0.017 for balsam fir; 0.75 ± 0.028 for black spruce; 0.64 ± 0.085 for trembling aspen; 0.64 ± 0.035 for tamarack; and 0.77 ± 0.041 for white birch. While the proportion of treed area increased by 8.5% over the 25-year period, the area occupied by black spruce declined by 13.5%. The area of balsam fir and white birch increased by 9.9% and 28.2%, respectively, while trembling aspen and tamarack changed by less than 5%. The map products developed and trends observed offer baseline information in support of long-term monitoring of treed area and tree species distributions. The demonstrated methods encourage development of spatially-explicit map products to complement spatially or temporally limited forest inventory datasets.http://dx.doi.org/10.1080/07038992.2020.1811083
spellingShingle Guy E. I. Strickland
Joan E. Luther
Joanne C. White
Michael A. Wulder
Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites
Canadian Journal of Remote Sensing
title Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites
title_full Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites
title_fullStr Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites
title_full_unstemmed Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites
title_short Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites
title_sort extending estimates of tree and tree species presence absence through space and time using landsat composites
url http://dx.doi.org/10.1080/07038992.2020.1811083
work_keys_str_mv AT guyeistrickland extendingestimatesoftreeandtreespeciespresenceabsencethroughspaceandtimeusinglandsatcomposites
AT joaneluther extendingestimatesoftreeandtreespeciespresenceabsencethroughspaceandtimeusinglandsatcomposites
AT joannecwhite extendingestimatesoftreeandtreespeciespresenceabsencethroughspaceandtimeusinglandsatcomposites
AT michaelawulder extendingestimatesoftreeandtreespeciespresenceabsencethroughspaceandtimeusinglandsatcomposites