Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada
Global land cover information is required to initialize land surface and Earth system models. In recent years, new land cover (LC) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdated. This study assesses the applicability of the C...
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ftdoajarticles:oai:doaj.org/article:968b4a6c45224bd681a0a3134f46f682 2023-05-15T18:31:02+02:00 Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada Libo Wang Paul Bartlett Darren Pouliot Ed Chan Céline Lamarche Michael A. Wulder Pierre Defourny Mike Brady 2019-09-01T00:00:00Z https://doi.org/10.3390/rs11192286 https://doaj.org/article/968b4a6c45224bd681a0a3134f46f682 EN eng MDPI AG https://www.mdpi.com/2072-4292/11/19/2286 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11192286 https://doaj.org/article/968b4a6c45224bd681a0a3134f46f682 Remote Sensing, Vol 11, Iss 19, p 2286 (2019) land cover forest cover plant functional type land surface model class canada Science Q article 2019 ftdoajarticles https://doi.org/10.3390/rs11192286 2022-12-31T16:08:34Z Global land cover information is required to initialize land surface and Earth system models. In recent years, new land cover (LC) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdated. This study assesses the applicability of the Climate Change Initiative (CCI) LC product for use in the Canadian Land Surface Scheme (CLASS) through comparison with finer resolution datasets over Canada, assisted with reference sample data and a vegetation continuous field tree cover fraction dataset. The results show that in comparison with the finer resolution maps over Canada, the 300 m CCI product provides much improved LC distribution over that from the 1 km GLC2000 dataset currently used to provide initial surface conditions in CLASS. However, the CCI dataset appears to overestimate needleleaf forest cover especially in the taiga-tundra transition zone of northwestern Canada. This may have partly resulted from limited availability of clear sky MEdium Resolution Imaging Spectrometer (MERIS) images used to generate the CCI classification maps due to the long snow cover season in Canada. In addition, changes based on the CCI time series are not always consistent with those from the MODIS or a Landsat-based forest cover change dataset, especially prior to 2003 when only coarse spatial resolution satellite data were available for change detection in the CCI product. It will be helpful for application in global simulations to determine whether these results also apply to other regions with similar landscapes, such as Eurasia. Nevertheless, the detailed LC classes and finer spatial resolution in the CCI dataset provide an improved reference map for use in land surface models in Canada. The results also suggest that uncertainties in the current cross-walking tables are a major source of the often large differences in the plant functional types (PFT) maps, and should be an area of focus in future work. Article in Journal/Newspaper taiga Tundra Directory of Open Access Journals: DOAJ Articles Canada Remote Sensing 11 19 2286 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
land cover forest cover plant functional type land surface model class canada Science Q |
spellingShingle |
land cover forest cover plant functional type land surface model class canada Science Q Libo Wang Paul Bartlett Darren Pouliot Ed Chan Céline Lamarche Michael A. Wulder Pierre Defourny Mike Brady Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada |
topic_facet |
land cover forest cover plant functional type land surface model class canada Science Q |
description |
Global land cover information is required to initialize land surface and Earth system models. In recent years, new land cover (LC) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdated. This study assesses the applicability of the Climate Change Initiative (CCI) LC product for use in the Canadian Land Surface Scheme (CLASS) through comparison with finer resolution datasets over Canada, assisted with reference sample data and a vegetation continuous field tree cover fraction dataset. The results show that in comparison with the finer resolution maps over Canada, the 300 m CCI product provides much improved LC distribution over that from the 1 km GLC2000 dataset currently used to provide initial surface conditions in CLASS. However, the CCI dataset appears to overestimate needleleaf forest cover especially in the taiga-tundra transition zone of northwestern Canada. This may have partly resulted from limited availability of clear sky MEdium Resolution Imaging Spectrometer (MERIS) images used to generate the CCI classification maps due to the long snow cover season in Canada. In addition, changes based on the CCI time series are not always consistent with those from the MODIS or a Landsat-based forest cover change dataset, especially prior to 2003 when only coarse spatial resolution satellite data were available for change detection in the CCI product. It will be helpful for application in global simulations to determine whether these results also apply to other regions with similar landscapes, such as Eurasia. Nevertheless, the detailed LC classes and finer spatial resolution in the CCI dataset provide an improved reference map for use in land surface models in Canada. The results also suggest that uncertainties in the current cross-walking tables are a major source of the often large differences in the plant functional types (PFT) maps, and should be an area of focus in future work. |
format |
Article in Journal/Newspaper |
author |
Libo Wang Paul Bartlett Darren Pouliot Ed Chan Céline Lamarche Michael A. Wulder Pierre Defourny Mike Brady |
author_facet |
Libo Wang Paul Bartlett Darren Pouliot Ed Chan Céline Lamarche Michael A. Wulder Pierre Defourny Mike Brady |
author_sort |
Libo Wang |
title |
Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada |
title_short |
Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada |
title_full |
Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada |
title_fullStr |
Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada |
title_full_unstemmed |
Comparison and Assessment of Regional and Global Land Cover Datasets for Use in CLASS over Canada |
title_sort |
comparison and assessment of regional and global land cover datasets for use in class over canada |
publisher |
MDPI AG |
publishDate |
2019 |
url |
https://doi.org/10.3390/rs11192286 https://doaj.org/article/968b4a6c45224bd681a0a3134f46f682 |
geographic |
Canada |
geographic_facet |
Canada |
genre |
taiga Tundra |
genre_facet |
taiga Tundra |
op_source |
Remote Sensing, Vol 11, Iss 19, p 2286 (2019) |
op_relation |
https://www.mdpi.com/2072-4292/11/19/2286 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11192286 https://doaj.org/article/968b4a6c45224bd681a0a3134f46f682 |
op_doi |
https://doi.org/10.3390/rs11192286 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
19 |
container_start_page |
2286 |
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1766214684743041024 |