Dr. Samantha T. Arundel
Senior Science Advisor
National Geospatial Program
U.S. Geological Survey
Presentation Title:
An Intelligent National Map:
Coordinating Structured Analysis and Scientific Validation Across Authoritative Geospatial Data
Presentation Summary:
The U.S. Geological Survey’s National Map provides a consistent, authoritative foundation for elevation, hydrography, transportation, and land cover data across the United States. However, the increasing complexity of spatial problems has outpaced platforms built around static layer access or manual analysis. An Intelligent National Map (INM) is being developed as a modular framework that supports structured queries, coordinated model workflows, and transparent review of analytic results. Rather than serving as a single tool, an INM organizes existing federal datasets into reusable workflows that support spatial reasoning and policy-relevant analysis.
Each workflow is initiated through a user query and proceeds through configured steps for data retrieval, transformation, modeling, and review. All inputs are drawn directly from agency-maintained sources, including the 3D Elevation Program (3DEP), the National Hydrography Dataset (NHD), and land cover datasets such as LCMAP. Results are tied to specific records and returned with complete provenance documentation. Instead of replicating or warehousing data, an INM issues structured queries against live repositories using defined interfaces and schema constraints.
About | Dr. Samantha T. Arundel
Dr. Samantha T. Arundel is the Director of the Center of Excellence for Geospatial Information Science (CEGIS) at the U.S. Geological Survey (USGS) and serves as the Senior Science Advisor to the Director of the National Geospatial Program (NGP). She is a recognized leader in GeoAI research and operationalization, focusing on automating geospatial data processing, terrain analysis, and feature detection to enhance national mapping capabilities.
Dr. Arundel has been instrumental in advancing automation for USGS geospatial workflows, including the 3D Elevation Program (3DEP). She actively works to bridge the gap between applied GeoAI research and operational geospatial production, ensuring that machine learning and AI solutions are effectively integrated into USGS mapping and data analysis efforts. She leads the development of an Intelligent National Map (INM), a modular platform that uses coordinated agents and authoritative USGS datasets to support query-driven spatial analysis and scientific validation.
She is deeply engaged in international geospatial collaborations, contributing to the International Cartographic Association (ICA) and related commissions. She also plays a key role in shaping AI strategies and policies for geospatial science, with active participation in conferences such as the American Association of Geographers, ACM Sigspatial, Trillion-pixel Challenge, Geospatial World Forum, AI for Good, and the International Mapping Leaders Forum.
Prior to joining the USGS in 2009, Dr. Arundel was an assistant and then associate professor of geography at Northern Arizona University. She holds a Ph.D. in Geography from Arizona State University.