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Creative Commons Attribution-Share Alike 4.0 License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.

Abstract

The research paper reports on the generation of geospatial footprints from geoparsed text associated with geocrowdsourced platial data collected and stored in the George Mason University Geocrowdsourcing Testbed (GMU-GcT). The GMU-GcT facilitates study of social dynamics, quality assessment, data contribution patterns, and position validation for geocrowdsourced geo data, with a primary purpose of mapping transient obstacles and navigation hazards in a dynamic urban environment. This paper reports on the automated generation of spatial footprints using open-source software, and discusses the role of automated spatial footprints in quality assessment for automated position validation. A detailed, local gazetteer is used to store placenames and placename variants including abbreviated, slang, former, and jargon-based instances. Obstacle reports containing location descriptions are geoparsed and processed with the help of the GMU-GcT gazetteer to generate geospatial footprints, which are used in a quality assessment process to validate the position of obstacle reports. Continuing research with the GMU-GcT has produced fifteen characteristic footprints types, which are generated and grouped into simple, complex, and ambiguous categories. The opensource tools used for generating these footprints are MapBox, MapBox.js, TURF.js, jQuery, and Bootstrap.

DOI

https://doi.org/10.7275/R5GT5KC1

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