Canadian Forest Service Publications
Completion and updating of a Landsat-based land cover polygon layer for Alberta, Canada. 2014. Castilla, G.; Hird, J.; Hall, R.J.; Schieck, J.; McDermid, J. Canadian Journal of Remote Sensing 40(2):92-109.
Year: 2014
Issued by: Northern Forestry Centre
Catalog ID: 35609
Language: English
Availability: PDF (request by e-mail)
Available from the Journal's Web site. †
DOI: 10.1080/07038992.2014.933073
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Abstract
We describe the creation of a GIS vector layer of land cover polygons for the entire province of Alberta, Canada, based upon preexisting, Landsat-derived, land cover raster datasets circa 2000 that were produced by the Canadian federal government. Our novel spatial and semantic generalization algorithm begins with a morphological segmentation of the original Landsat imagery used in the classification, and then assigns classes to the segments based on the land cover labels of pixels inside the segments, using sequential rules that account for contextual and size factors in addition to class preponderance. An object-based accuracy assessment followed, which allowed us to correct issues and refine the polygon map. The enhanced map, which was later updated to circa 2010 conditions using Landsat imagery from that time period and ancillary GIS information on natural and anthropogenic disturbances, consists of 1 million land cover polygons belonging to 11 classes and has an overall accuracy of 75%. This methodology could be employed in other jurisdictions with similar raster datasets to create a more intense spatial generalization than that provided by a conventional raster to vector conversion.
Plain Language Summary
Land cover maps provide an overview of the spatial distribution of vegetation and other resources across a territory. Existing land cover datasets for the province of Alberta, Canada, were either incomplete, too coarse, outdated, or of unknown accuracy. To address these problems, we created a digital map of the land cover of Alberta circa 2010, which consists of a patchwork of about one million polygons of irregular shape, each representing a uniform area in terms of land cover. To create this map, we developed a new method that re-uses pre-existing information containing land cover and disturbances such as from fire and harvesting, along with a novel framework for assessing the thematic and spatial accuracy of the polygons. This method could be applied to other jurisdictions having similar datasets.