Operational mapping of the land cover of the forested area of Canada with Landsat data: EOSD land cover program

Wulder, Michael A.; Dechka, J.A.; Gillis, M A; Luther, Joan E.; Hall, Ronald J.; Beaudoin, A.; Franklin, Steven E.

doi:10.5558/tfc791075-6

Cited by 136 publications

(76 citation statements)

References 21 publications

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“…The Canadian EOSD land-cover dataset was developed by the Canadian Forest Service and Canadian Space Agency. The EOSD dataset was produced using Landsat images acquired in circa-2000 (Wulder et al 2003). The dataset covers the forested area of Canada, about half of the Canada landmass, and the nonforested northern portions and agricultural southern portions of the country were not mapped (Wulder et al 2003).…”

Section: Assessment Against National Land-cover Datasetsmentioning

confidence: 99%

“…The EOSD dataset was produced using Landsat images acquired in circa-2000 (Wulder et al 2003). The dataset covers the forested area of Canada, about half of the Canada landmass, and the nonforested northern portions and agricultural southern portions of the country were not mapped (Wulder et al 2003). User's and producer's accuracies of water were >91% (Wulder et al 2006).…”

Section: Assessment Against National Land-cover Datasetsmentioning

confidence: 99%

“…the Moderate-resolution Imaging Spectroradiometer [MODIS]). However, most inland water bodies are too small to be globally relative to the MODIS water mask (Carroll et al 2009) and to two established national datasets, the U.S. National Land Cover Database (NLCD) (Homer et al 2004) and the Canadian Earth Observation for Sustainable Development of Forests (EOSD) land-cover dataset (Wulder et al 2003). …”

Section: Introductionmentioning

confidence: 99%

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A global, high-resolution (30-m) inland water body dataset for 2000: first results of a topographic–spectral classification algorithm

Feng

Sexton

Channan

et al. 2015

International Journal of Digital Earth

294

190

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The science and management of terrestrial ecosystems require accurate, high-resolution mapping of surface water. We produced a global, 30-m-resolution inland surface water dataset with an automated algorithm using Landsat-based surface reflectance estimates, multispectral water and vegetation indices, terrain metrics, and prior coarse-resolution water masks. The dataset identified 3,650,723 km 2 of inland water globally -nearly three quarters of which was located in North America (40.65%) and Asia (32.77%), followed by Europe (9.64%), Africa (8.47%), South America (6.91%), and Oceania (1.57%). Boreal forests contained the largest portion of terrestrial surface water (25.03% of the global total), followed by the nominal 'inland water' biome (16.36%), tundra (15.67%), and temperate broadleaf and mixed forests (13.91%). Agreement with respect to the Moderate-resolution Imaging Spectroradiometer water mask and Landsat-based national land-cover datasets was very high, with commission errors <4% and omission errors <14% relative to each. Most of these were accounted for in the seasonality of water cover, snow and ice, and clouds -effects which were compounded by differences in image acquisition date relative to reference datasets. The Global Land Cover Facility (GLCF) inland surface water dataset is available for open access at the GLCF website (http://www.landcover.org).

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Section: Assessment Against National Land-cover Datasetsmentioning

confidence: 99%

Section: Assessment Against National Land-cover Datasetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A global, high-resolution (30-m) inland water body dataset for 2000: first results of a topographic–spectral classification algorithm

Feng

Sexton

Channan

et al. 2015

International Journal of Digital Earth

294

190

View full text Add to dashboard Cite

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“…3. Landsat Enhanced Thematic Mapper Plus (ETMþ) land-cover map (Wulder et al (2003); GeoTiffs available online at http://eosd.cfs.nrcan.gc.ca). Up to 24 land-cover classes are identified in each vegetation zone.…”

Section: Digital Vegetation Zone Map Of Québec (Mrnfpq 2003) An Ecozmentioning

confidence: 99%

Model effects on GLAS-based regional estimates of forest biomass and carbon

Nelson

2010

International Journal of Remote Sensing

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Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 Â 10 6 km 2 study area in the Province of Québec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass) 0.5 serves as the dependent variable. The use of different models in Québec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 AE 0.28 Gt to 5.29 AE 0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t ha -1 and when GLAS 75th percentile heights fall below 7 m.

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“…These maps allow differentiation between coniferous forests and open land. They were developed by the Canadian Forest Service from LANDSAT-ETM+ imagery (Wulder et al, 2003). They cover almost all of the continental territory of Canada and are available free online (http://www.…”

Section: Land Covermentioning

confidence: 99%

Adaptation of the SNOWMAP algorithm for snow mapping over eastern Canada using Landsat-TM imagery

Chokmani

Dever

Bernier

et al. 2010

Hydrological Sciences Journal

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The snow mapping algorithm SNOWMAP was adapted to Landsat-TM data and to the context of eastern Canada. Six Landsat-5 TM scenes were used. It was found that the original version of SNOWMAP greatly underestimates snow cover extent. The modification made to the original algorithm, by cancelling the minimum threshold of 0.1 on the NDVI value, allows gaps to be filled in. In addition, a spatial correction procedure applied to the modified SNOWMAP algorithm results improves snow detection under coniferous forests. Based on a limited data set of ground-based observations (only 40 sites were available), the modified SNOWMAP seems to perform better in snow detection than the original version of the algorithm. An application case is presented in order to demonstrate the relevance of the modified SNOWMAP results as a high spatial-resolution reference for the validation of historical snow maps derived from medium spatial-resolution satellite data.

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Operational mapping of the land cover of the forested area of Canada with Landsat data: EOSD land cover program

Cited by 136 publications

References 21 publications

A global, high-resolution (30-m) inland water body dataset for 2000: first results of a topographic–spectral classification algorithm

A global, high-resolution (30-m) inland water body dataset for 2000: first results of a topographic–spectral classification algorithm

Model effects on GLAS-based regional estimates of forest biomass and carbon

Adaptation of the SNOWMAP algorithm for snow mapping over eastern Canada using Landsat-TM imagery

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