Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada
In this paper, we demonstrate the feasibility of using TanDEM-X (TX) interferometric coherence data for mapping forest height with 25-m pixels across a study area near Fort Simpson, Northwest Territories (NWT), Canada. Our simplified RVOG model locally estimates forest height by combining an optimiz...
Published in: | Canadian Journal of Remote Sensing |
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2019
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Online Access: | https://doi.org/10.1080/07038992.2019.1604119 https://doaj.org/article/6b0dee4016ee4cc3bab071c2e03fdcad |
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ftdoajarticles:oai:doaj.org/article:6b0dee4016ee4cc3bab071c2e03fdcad 2024-09-15T18:06:57+00:00 Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada Hao Chen André Beaudoin David A. Hill Shane R. Cloude Rob S. Skakun Maryse Marchand 2019-07-01T00:00:00Z https://doi.org/10.1080/07038992.2019.1604119 https://doaj.org/article/6b0dee4016ee4cc3bab071c2e03fdcad EN FR eng fre Taylor & Francis Group http://dx.doi.org/10.1080/07038992.2019.1604119 https://doaj.org/toc/1712-7971 1712-7971 doi:10.1080/07038992.2019.1604119 https://doaj.org/article/6b0dee4016ee4cc3bab071c2e03fdcad Canadian Journal of Remote Sensing, Vol 45, Iss 3-4, Pp 290-307 (2019) Environmental sciences GE1-350 Technology T article 2019 ftdoajarticles https://doi.org/10.1080/07038992.2019.1604119 2024-08-05T17:49:16Z In this paper, we demonstrate the feasibility of using TanDEM-X (TX) interferometric coherence data for mapping forest height with 25-m pixels across a study area near Fort Simpson, Northwest Territories (NWT), Canada. Our simplified RVOG model locally estimates forest height by combining an optimized estimation of TX interferometric coherence amplitude with the 20-m resolution Canadian Digital Elevation Model (CDEM) accounting for local slope variations. The initial map of TX height estimates provided R2 values of 0.78 and 0.88, mean errors (ME) of 1.66 m and 1.90 m, and root-mean-square errors (RMSE) of 2.7 m and 2.9 m when compared to independent height estimates derived from field plots and airborne LiDAR, respectively. We corrected the bias of TX height estimates using two variants of a LiDAR-based linear model. An application of three cover-specific linear adjustments provided the final TX height map with absolute ME ≤0.05 m and RMSE ≤2.09 m. The approach was tailored to poorly inventoried northern boreal regions through the use of archived TX data, the CDEM, a land cover map and airborne LiDAR transects. Our encouraging results support the perspective of wall-to-wall mapping of forest height across northern boreal forests in the NWT and beyond. Article in Journal/Newspaper Fort Simpson Northwest Territories Directory of Open Access Journals: DOAJ Articles Canadian Journal of Remote Sensing 45 3-4 290 307 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English French |
topic |
Environmental sciences GE1-350 Technology T |
spellingShingle |
Environmental sciences GE1-350 Technology T Hao Chen André Beaudoin David A. Hill Shane R. Cloude Rob S. Skakun Maryse Marchand Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada |
topic_facet |
Environmental sciences GE1-350 Technology T |
description |
In this paper, we demonstrate the feasibility of using TanDEM-X (TX) interferometric coherence data for mapping forest height with 25-m pixels across a study area near Fort Simpson, Northwest Territories (NWT), Canada. Our simplified RVOG model locally estimates forest height by combining an optimized estimation of TX interferometric coherence amplitude with the 20-m resolution Canadian Digital Elevation Model (CDEM) accounting for local slope variations. The initial map of TX height estimates provided R2 values of 0.78 and 0.88, mean errors (ME) of 1.66 m and 1.90 m, and root-mean-square errors (RMSE) of 2.7 m and 2.9 m when compared to independent height estimates derived from field plots and airborne LiDAR, respectively. We corrected the bias of TX height estimates using two variants of a LiDAR-based linear model. An application of three cover-specific linear adjustments provided the final TX height map with absolute ME ≤0.05 m and RMSE ≤2.09 m. The approach was tailored to poorly inventoried northern boreal regions through the use of archived TX data, the CDEM, a land cover map and airborne LiDAR transects. Our encouraging results support the perspective of wall-to-wall mapping of forest height across northern boreal forests in the NWT and beyond. |
format |
Article in Journal/Newspaper |
author |
Hao Chen André Beaudoin David A. Hill Shane R. Cloude Rob S. Skakun Maryse Marchand |
author_facet |
Hao Chen André Beaudoin David A. Hill Shane R. Cloude Rob S. Skakun Maryse Marchand |
author_sort |
Hao Chen |
title |
Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada |
title_short |
Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada |
title_full |
Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada |
title_fullStr |
Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada |
title_full_unstemmed |
Mapping Forest Height from TanDEM-X Interferometric Coherence Data in Northwest Territories, Canada |
title_sort |
mapping forest height from tandem-x interferometric coherence data in northwest territories, canada |
publisher |
Taylor & Francis Group |
publishDate |
2019 |
url |
https://doi.org/10.1080/07038992.2019.1604119 https://doaj.org/article/6b0dee4016ee4cc3bab071c2e03fdcad |
genre |
Fort Simpson Northwest Territories |
genre_facet |
Fort Simpson Northwest Territories |
op_source |
Canadian Journal of Remote Sensing, Vol 45, Iss 3-4, Pp 290-307 (2019) |
op_relation |
http://dx.doi.org/10.1080/07038992.2019.1604119 https://doaj.org/toc/1712-7971 1712-7971 doi:10.1080/07038992.2019.1604119 https://doaj.org/article/6b0dee4016ee4cc3bab071c2e03fdcad |
op_doi |
https://doi.org/10.1080/07038992.2019.1604119 |
container_title |
Canadian Journal of Remote Sensing |
container_volume |
45 |
container_issue |
3-4 |
container_start_page |
290 |
op_container_end_page |
307 |
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1810444304678649856 |