Exploiting Polygon Metadata to Understand Raster Maps - Accurate Polygonal Feature Extraction

Fandel Lin, Craig A. Knoblock, Basel Shbita, Binh Vu, Zekun Li, Yao Yi Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Locating undiscovered deposits of critical minerals requires accurate geological data. However, most of the 100,000 historical geological maps of the United States Geological Survey (USGS) are in raster format. This hinders critical mineral assessment. We target the problem of extracting geological features represented as polygons from raster maps. We exploit the polygon metadata that provides information on the geological features, such as the map keys indicating how the polygon features are represented, to extract the features. We present a metadata-driven machine-learning approach that encodes the raster map and map key into a series of bitmaps and uses a convolutional model to learn to recognize the polygon features. We evaluated our approach on USGS geological maps; our approach achieves a median F1 score of 0.809 and outperforms state-of-the-art methods by 4.52%.

Original languageEnglish (US)
Title of host publication31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2023
EditorsMaria Luisa Damiani, Matthias Renz, Ahmed Eldawy, Peer Kroger, Mario A. Nascimento
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400701689
DOIs
StatePublished - Nov 13 2023
Event31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2023 - Hamburg, Germany
Duration: Nov 13 2023Nov 16 2023

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Conference

Conference31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2023
Country/TerritoryGermany
CityHamburg
Period11/13/2311/16/23

Bibliographical note

Publisher Copyright:
© 2023 Owner/Author(s).

Keywords

  • image processing
  • polygon extraction
  • raster map

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