SPASTC: a Spatial Partitioning Algorithm for Scalable Travel-time Computation

Author(s): Alexander Michels, Jinwoo Park, Jeon-Young Kang, and Shaowen Wang

We present a Spatial Partitioning Algorithm for Scalable Travel-time Computation (SPASTC). Calculating travel-time catchments over large spatial extents is computationally intensive, with previous work limiting their spatial extent to minimize computational burden or overcoming the computational burden with advanced cyberinfrastructure. SPASTC is designed for domain decomposition of travel-time catchment calculations with a user-provided memory limit on computation. SPASTC realizes this through spatial partitioning that preserves spatial relationships required to compute travel-time zones and respects a user-provided memory limit. This al- lows users to efficiently calculate travel-time catchments within a given memory limit and represents a significant speed-up over computing each catchment separately. We demonstrate SPASTC by computing spatial accessibility to hospital beds across the conterminous United States. Our case study shows that SPASTC achieves significant efficiency and scalability making the computation of travel-time catchment up to 51 times faster. Check out the full paper here:

Keywords: cyberGIS, parallel computing, Spatial Accessibility, spatial domain decomposition

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Alexander Michels

University of Illinois at Urbana-Champaign

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