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cartographer that may be used to generate smaller scale generalized ver-
sions of compilation-scale data. It should also reduce processing times for
mapping at much smaller scales, since one can anticipate that the center-
line will satisfactorily represent a stream network in its most simplified
form. A delineated centerline likewise provides a minimum level of priori-
tization within a data environment wherein it is difficult to maintain a
comprehensive and current channel hierarchy.
The work presented here also provides a working example of how various
forms of data enrichment can support automated generalization processing,
and add to the emerging body of knowledge about its various roles in
automated generalization. Early work (Plazanet et al. 1998) argued for en-
richment of additional geometric or procedural information. The value of
data enrichment within the generalization process has been more recently
cited by Neun et al. (2004), who encoded horizontal and vertical relation-
ships to support multiscale thematic and web mapping. Savino et al. (2010)
enrich a road data set to inform feature selection during generalization.
The work here focuses on enrichment of semantic attributes, establishing
which stream reaches mark the primary path of water through a hydro-
graphic basin. Research by the authors is ongoing to further enhance and
streamline the processing steps.
As Neun et al. (2008: 133) remark, knowledge exacted by the enrichment
process should be “… made available to other generalization operators”. In
every published example, enrichment is able to facilitate more complete
automation of generalization processing which would otherwise be compu-
tationally intensive, require domain expertise which is not widely avail-
able, or augment existing database information. Further developments and
extensions to database enrichment show great promise for continued auto-
mation of cartographic generalization.
Acknowledgments
This research is supported by USGS-CEGIS grant # 04121HS029, “Generalization and Data
Modeling for New Generation Topographic Mapping”. The authors also acknowledge comments
of reviewers which helped to strengthen the current version.
