GESTALT: Geospatially Enhanced Search with Terrain Augmented Location Targeting
Published in The 2nd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data, 2023
Geographic information systems (GIS) provide users with a means to efficiently search over spatial data given certain key pieces of information, like the coordinates or exact name of a location of interest. Current GIS capabilities do not enable users to search for locations using imperfect or incomplete information easily. In these cases, GIS tools help narrow down a region of interest, but users must conduct a manual last-mile search to find the exact location of interest within that region. This typically involves the user visually inspecting many remote sensing or street-view images to identify distinct landmarks or terrain features that match the partial information provided. This step of the search process is a bottleneck. Taking inspiration from the way humans recall and search for information, we present the Geospatially Enhanced Search with Terrain Augmented Location Targeting (GESTALT), an endto-end pipeline for extracting geospatial data, transforming it into coherent spatial relations, storing those relations, and searching over them. We contribute a new Swan Valley Wineries dataset and a proof of concept architecture that includes multiple methods for querying spatial configurations of objects, handling uncertainty in the information known about a location or object, and accounting for the fuzzy boundaries between locations.
@inproceedings{osullivan2023a,
title={GESTALT: Geospatially Enhanced Search with Terrain Augmented Location Targeting},
author={O'Sullivan, Kent and Schneider, Nicole R and Rasheed, Aleeza and Samet, Hanan},
booktitle={Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data},
pages={1--8},
year={2023}
}