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...
Published in: | Canadian Journal of Remote Sensing |
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2020
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ftdoajarticles:oai:doaj.org/article:ead02dec06774cd49d9de35ad6f7273a 2023-11-12T04:21:22+01:00 Extending Estimates of Tree and Tree Species Presence-Absence through Space and Time Using Landsat Composites Guy E. I. Strickland Joan E. Luther Joanne C. White Michael A. Wulder 2020-09-01T00:00:00Z https://doi.org/10.1080/07038992.2020.1811083 https://doaj.org/article/ead02dec06774cd49d9de35ad6f7273a EN FR eng fre Taylor & Francis Group http://dx.doi.org/10.1080/07038992.2020.1811083 https://doaj.org/toc/1712-7971 1712-7971 doi:10.1080/07038992.2020.1811083 https://doaj.org/article/ead02dec06774cd49d9de35ad6f7273a Canadian Journal of Remote Sensing, Vol 46, Iss 5, Pp 567-584 (2020) Environmental sciences GE1-350 Technology T article 2020 ftdoajarticles https://doi.org/10.1080/07038992.2020.1811083 2023-10-15T00:36:30Z 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. Article in Journal/Newspaper Newfoundland Directory of Open Access Journals: DOAJ Articles Canada Newfoundland Tamarack ENVELOPE(-121.170,-121.170,57.650,57.650) Canadian Journal of Remote Sensing 46 5 567 584 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English French |
topic |
Environmental sciences GE1-350 Technology T |
spellingShingle |
Environmental sciences GE1-350 Technology T 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 |
topic_facet |
Environmental sciences GE1-350 Technology T |
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. |
format |
Article in Journal/Newspaper |
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 |
title |
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_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_sort |
extending estimates of tree and tree species presence-absence through space and time using landsat composites |
publisher |
Taylor & Francis Group |
publishDate |
2020 |
url |
https://doi.org/10.1080/07038992.2020.1811083 https://doaj.org/article/ead02dec06774cd49d9de35ad6f7273a |
long_lat |
ENVELOPE(-121.170,-121.170,57.650,57.650) |
geographic |
Canada Newfoundland Tamarack |
geographic_facet |
Canada Newfoundland Tamarack |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_source |
Canadian Journal of Remote Sensing, Vol 46, Iss 5, Pp 567-584 (2020) |
op_relation |
http://dx.doi.org/10.1080/07038992.2020.1811083 https://doaj.org/toc/1712-7971 1712-7971 doi:10.1080/07038992.2020.1811083 https://doaj.org/article/ead02dec06774cd49d9de35ad6f7273a |
op_doi |
https://doi.org/10.1080/07038992.2020.1811083 |
container_title |
Canadian Journal of Remote Sensing |
container_volume |
46 |
container_issue |
5 |
container_start_page |
567 |
op_container_end_page |
584 |
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1782336815875751936 |