GeoNatShapes: a natural feature reference dataset for mapping and AI training
These data were compiled for the use of training natural feature machine learning (GeoAI) detection and delineation. The natural feature classes include the Geographic Names Information System (GNIS) feature types Basins, Bays, Bends, Craters, Gaps, Guts, Islands, Lakes, Ridges and Valleys, and are an areal representation of those GNIS point features. Features were produced using heads-up digitizing from 2018 to 2019 by Dr. Sam Arundel's team at the U.S. Geological Survey, Center of Excellence for Geospatial Information Science, Rolla, Missouri, USA, and Dr. Wenwen Li's team in the School of Geographical Sciences at Arizona State University, Tempe, Arizona, USA. Figure 1 shows the areal boundary (cyan) of Bachelor Canyon, a GNIS valley feature, and a bounding box for machine learning training (black) relative to the data sources used in its delineation: A) the historical topographic map, B) respective NAIP imagery and C) 3DEP elevation data stretched and shaded.
Citation Information
Publication Year | 2020 |
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Title | GeoNatShapes: a natural feature reference dataset for mapping and AI training |
DOI | 10.5066/P9X5BN1L |
Authors | Samantha T Arundel, WenWen Li, Sizhe Wang, Arthur Chan, Nadia Ariani, Majid S. Mohamed |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Southwest Biological Science Center - Flagstaff, AZ, Headquarters |
Rights | This work is marked with CC0 1.0 Universal |