@article{wang_comparison_2019,
	title = {Comparison and Assessment of Regional and Global Land Cover Datasets for Use in {CLASS} over Canada},
	volume = {11},
	issn = {2072-4292},
	url = {https://www.mdpi.com/2072-4292/11/19/2286},
	doi = {10.3390/rs11192286},
	abstract = {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({LC}) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdated.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 {GLC}2000 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.},
	number = {19},
	journaltitle = {Remote Sensing},
	author = {Wang, Libo and Bartlett, Paul and Pouliot, Darren and Chan, Ed and Lamarche, Céline and Wulder, Michael A. and Defourny, Pierre and Brady, Mike},
	date = {2019-09-30},
}