Large-area land cover mapping based on remotely sensed data often requires combining individual or large groups of classified images to produce final map products. Operational and logistical considerations are typically confronted when classifying medium spatial resolution satellite imagery (i.e., Landsat), with the mapping partitioned by spectral, ecological, or political considerations, or combinations thereof. Visual discontinuities can emerge at the locations where logistically based production zones join. Transparent and systematic approaches for addressing discontinuities are desired for the Earth Observation for Sustainable Development of Forests (EOSD) project. This large-area land cover mapping project is producing map products for Canada's forested ecozones. A distributed implementation plan, largely based on grouping provincial and territorial political units, was followed for production. Scene-to-scene discontinuities are rare within each production zone and are primarily related to image acquisition date and phenological state. In contrast, discontinuities can emerge at the production zone boundaries because of differences in support data available or more commonly because of differences in the attribution of density classes. Of the over 475 scenes classified for the EOSD project, it is estimated that fewer than 30 (about 6.3% of total) will require processing to minimize the cross-boundary discontinuity. Options for mitigating the discontinuities are described and demonstrated in the context of different scenarios of overlap found along the EOSD production zone boundaries (complete overlap, partial overlap, and no overlap) using two subsets of a Landsat scene along the shared provincial border between British Columbia and Alberta, Canada. Analysis of image gradients provides a quantitative basis for identification of discontinuities and also relates the results of the likelihood-based relabelling process. Through this process, only density descriptors of cover types are altered, largely maintaining classification integrity. The process as presented is generic and is suitable for addressing edge discontinuities that can emerge when undertaking a large-area land cover classification project.
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