Speaker
Description
Recent work on identifying suitable sites for the next-generation gravitational wave observatory, Cosmic Explorer (CE), includes site visits, efforts to build relationships with relevant communities surrounding promising sites, characterizing costs of construction, and finding suitable sites based on scientific thresholds. The common theme amongst these complementary efforts is Geographic Information Systems (GIS). GIS, like many other forms of data science, has a blooming community of researchers integrating their domain expertise with Artificial Intelligence (AI) to find spatial patterns in noisy data with non-linear relationships. In GIS, deploying AI into spatial analysis is referred to as GeoAI. With promising sites for Cosmic Explorer identified at the national scale, local analysis requires the use of GeoAI [DS1.1]to forecast future sources of anthropogenic noise as well as environmental hazards to Cosmic Explorer at potentially promising sites. This presentation explores how GeoAI will be used in local-scale and site level analysis to predict future land use (a principal concern for anthropogenic noise) and flood hazard simulation mapping in often remote, sparsely mapped portions of the contiguous United States. GeoAI will be key to bring CE to realization as local-scale and site level analysis will require spatial analysis that utilizes neural networks and deep learning.