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Automated extraction of areal extents for GNIS Summit features using the eminence core method

June 30, 2020

An important objective of the U.S. Geological Survey (USGS) is to enhance the Geographic Names Information System (GNIS) by automatically associating boundaries with terrain features that are currently spatially represented as two-dimensional points. In this paper, the discussion focuses on experiments for mapping GNIS Summit features using the eminence core region-growing method, which maps the area between a peak and its key col (saddle). A secondary goal of this project is to improve the positional accuracy of GNIS Summit features, since those locations were derived long ago and need to be snapped to local morphometric peaks detected from analysis of the highest-resolution digital elevation models (DEMs). The eminence cores delineated for a subset of GNIS Summit features were compared visually against basemaps and manually digitized polygons created by USGS staff. The comparisons revealed substantial differences between the computationally derived eminence cores and the manually generated polygons. Results clearly suggest that the default core delineation method tested must be modified to “roll back” or truncate growth of unreasonably large cores to smaller extents that would match people’s intuitive expectations. However, these results are far more encouraging than any method tested previously, since this method guarantees a 1-1 correspondence between polygons and GNIS Summit features.

Citation Information

Publication Year 2020
Title Automated extraction of areal extents for GNIS Summit features using the eminence core method
DOI 10.30437/GEOMORPHOMETRY2020_10
Authors Gaurav Sinha, Samantha Arundel
Publication Type Conference Paper
Publication Subtype Conference Paper
Index ID 70236801
Record Source USGS Publications Warehouse
USGS Organization Center for Geospatial Information Science (CEGIS)