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...

Tags: Alabama, Alaska, American Samoa, Arizona, Arkansas, All tags... California, Colorado, Connecticut, Delaware, Florida, GeoAI, Geography, Georgia, Hawaii, Idaho, Illinois, Indiana, Information Sciences, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, USGS Science Data Catalog (SDC), United States of America, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming, basin, bays, craters, deep learning, geography, geoscientificInformation, geospatial artificial intelligence, geospatial datasets, imageryBaseMapsEarthCover, islands, lakes, natural features, object detection, ridges, training data, valleys, Fewer tags