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Dr. Samantha T. Arundel is a research geographer in the Center of Excellence for Geospatial Information Science at the U.S. Geological Survey. Her research focuses on automating physical feature mapping and modeling using various techniques like traditional raster modeling, GEOBIA and machine learning.
Dr. Samantha T. Arundel (Sam) received her Ph.D. in geography from Arizona State University in 2000 and was an assistant and then associate professor at Northern Arizona University where her research focused on spatial modeling and automation of plant/climate relationships. In 2009, when she joined the USGS, she first served as raster specialist in the Ortho & Elevation section and as elevation and hydrography specialist for the Applied Research and Technology Branch. During this time, she led the contour generation development team in developing algorithms for automating contour production from 10-meter elevation data for the USTopo product; and served as the program manager for the automation of the National Elevation Dataset production, in its transition from Earth Resource Observation System (EROS) to the National Geospatial Technical Operations Center (NGTOC). In 2015, Sam moved to the Center of Excellence for Geospatial Information Science, the research section of the NGTOC, where she is a Research Geographer conducting research on automated terrain mapping and modeling using various techniques like traditional raster modeling, geographic object-based image analysis and machine learning.
Range, summit and valley polygons were automatically generated for GNIS points through geographic object-based image analysis (GEOBIA).
Image shows four quadrants with varying levels of details associated around 21 points.
Points are numbered and labeled:
Range, summit and valley polygons were automatically generated for GNIS points through geographic object-based image analysis (GEOBIA).
Image shows four quadrants with varying levels of details associated around 21 points.
Points are numbered and labeled:
Range, summit and valley polygons were automatically generated for GNIS points through geographic object-based image analysis (GEOBIA).
Image shows four quadrants with varying levels of details associated around 21 points.
Points are numbered and labeled:
Range, summit and valley polygons were automatically generated for GNIS points through geographic object-based image analysis (GEOBIA).
Image shows four quadrants with varying levels of details associated around 21 points.
Points are numbered and labeled: