The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains
Sustainable forest management requires information on the spatial distribution, composition, and structure of forests. However, jurisdictions with large tracts of noncommercial forest, such as the Northwest Territories (NWT) of Canada, often lack detailed forest information across their land base. T...
Published in: | Remote Sensing |
---|---|
Main Authors: | , , , , , , , , , |
Format: | Text |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute
2022
|
Subjects: | |
Online Access: | https://doi.org/10.3390/rs14051108 |
id |
ftmdpi:oai:mdpi.com:/2072-4292/14/5/1108/ |
---|---|
record_format |
openpolar |
spelling |
ftmdpi:oai:mdpi.com:/2072-4292/14/5/1108/ 2023-08-20T04:08:49+02:00 The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains Guillermo Castilla Ronald J. Hall Rob Skakun Michelle Filiatrault André Beaudoin Michael Gartrell Lisa Smith Kathleen Groenewegen Chris Hopkinson Jurjen van der Sluijs agris 2022-02-24 application/pdf https://doi.org/10.3390/rs14051108 EN eng Multidisciplinary Digital Publishing Institute Forest Remote Sensing https://dx.doi.org/10.3390/rs14051108 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 5; Pages: 1108 forest vegetation inventory LiDAR GLAS Landsat PALSAR-1 k-NN boreal forest Northwest Territories Text 2022 ftmdpi https://doi.org/10.3390/rs14051108 2023-08-01T04:16:26Z Sustainable forest management requires information on the spatial distribution, composition, and structure of forests. However, jurisdictions with large tracts of noncommercial forest, such as the Northwest Territories (NWT) of Canada, often lack detailed forest information across their land base. The goal of the Multisource Vegetation Inventory (MVI) project was to create a large area forest inventory (FI) map that could support strategic forest management in the NWT using optical, radar, and light detection and ranging (LiDAR) satellite remote sensing anchored on limited field plots and airborne LiDAR data. A new landcover map based on Landsat imagery was the first step to stratify forestland into broad forest types. A modelling chain linking FI plots to airborne and spaceborne LiDAR was then developed to circumvent the scarcity of field data in the region. The developed models allowed the estimation of forest attributes in thousands of surrogate FI plots corresponding to spaceborne LiDAR footprints distributed across the project area. The surrogate plots were used as a reference dataset for estimating each forest attribute in each 30 m forest cell within the project area. The estimation was based on the k-nearest neighbour (k-NN) algorithm, where the selection of the four most similar surrogate FI plots to each cell was based on satellite, topographic, and climatic data. Wall-to-wall 30 m raster maps of broad forest type, stand height, crown closure, stand volume, total volume, aboveground biomass, and stand age were created for a ~400,000 km2 area, validated with independent data, and generalized into a polygon GIS layer resembling a traditional FI map. The MVI project showed that a reasonably accurate FI map for large, remote, predominantly non-inventoried boreal regions can be obtained at a low cost by combining limited field data with remote sensing data from multiple sources. Text Northwest Territories taiga Taiga plains MDPI Open Access Publishing Northwest Territories Canada Remote Sensing 14 5 1108 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
forest vegetation inventory LiDAR GLAS Landsat PALSAR-1 k-NN boreal forest Northwest Territories |
spellingShingle |
forest vegetation inventory LiDAR GLAS Landsat PALSAR-1 k-NN boreal forest Northwest Territories Guillermo Castilla Ronald J. Hall Rob Skakun Michelle Filiatrault André Beaudoin Michael Gartrell Lisa Smith Kathleen Groenewegen Chris Hopkinson Jurjen van der Sluijs The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains |
topic_facet |
forest vegetation inventory LiDAR GLAS Landsat PALSAR-1 k-NN boreal forest Northwest Territories |
description |
Sustainable forest management requires information on the spatial distribution, composition, and structure of forests. However, jurisdictions with large tracts of noncommercial forest, such as the Northwest Territories (NWT) of Canada, often lack detailed forest information across their land base. The goal of the Multisource Vegetation Inventory (MVI) project was to create a large area forest inventory (FI) map that could support strategic forest management in the NWT using optical, radar, and light detection and ranging (LiDAR) satellite remote sensing anchored on limited field plots and airborne LiDAR data. A new landcover map based on Landsat imagery was the first step to stratify forestland into broad forest types. A modelling chain linking FI plots to airborne and spaceborne LiDAR was then developed to circumvent the scarcity of field data in the region. The developed models allowed the estimation of forest attributes in thousands of surrogate FI plots corresponding to spaceborne LiDAR footprints distributed across the project area. The surrogate plots were used as a reference dataset for estimating each forest attribute in each 30 m forest cell within the project area. The estimation was based on the k-nearest neighbour (k-NN) algorithm, where the selection of the four most similar surrogate FI plots to each cell was based on satellite, topographic, and climatic data. Wall-to-wall 30 m raster maps of broad forest type, stand height, crown closure, stand volume, total volume, aboveground biomass, and stand age were created for a ~400,000 km2 area, validated with independent data, and generalized into a polygon GIS layer resembling a traditional FI map. The MVI project showed that a reasonably accurate FI map for large, remote, predominantly non-inventoried boreal regions can be obtained at a low cost by combining limited field data with remote sensing data from multiple sources. |
format |
Text |
author |
Guillermo Castilla Ronald J. Hall Rob Skakun Michelle Filiatrault André Beaudoin Michael Gartrell Lisa Smith Kathleen Groenewegen Chris Hopkinson Jurjen van der Sluijs |
author_facet |
Guillermo Castilla Ronald J. Hall Rob Skakun Michelle Filiatrault André Beaudoin Michael Gartrell Lisa Smith Kathleen Groenewegen Chris Hopkinson Jurjen van der Sluijs |
author_sort |
Guillermo Castilla |
title |
The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains |
title_short |
The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains |
title_full |
The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains |
title_fullStr |
The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains |
title_full_unstemmed |
The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains |
title_sort |
multisource vegetation inventory (mvi): a satellite-based forest inventory for the northwest territories taiga plains |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14051108 |
op_coverage |
agris |
geographic |
Northwest Territories Canada |
geographic_facet |
Northwest Territories Canada |
genre |
Northwest Territories taiga Taiga plains |
genre_facet |
Northwest Territories taiga Taiga plains |
op_source |
Remote Sensing; Volume 14; Issue 5; Pages: 1108 |
op_relation |
Forest Remote Sensing https://dx.doi.org/10.3390/rs14051108 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs14051108 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
5 |
container_start_page |
1108 |
_version_ |
1774721351070777344 |