A Parallel Processing Model for Accelerating High-Resolution Geo-Spatial Accessibility Analysis

Abstract

Accessibility is an important issue in transport geography, land planning, and many other related fields. Accessibility problems become computationally demanding when involving high-resolution requirements. Using conventional methods, providing high-resolution accessibility analysis for real-time decision support remains a challenge. In this paper, we present a parallel processing model, named HiAccess, to solve the high-resolution accessibility analysis problems in real time. One feature of HiAccess is a fast road network construction method, in which the road network topology is determined by traversing the original road nodes only once. The parallel strategies of HiAccess are fully optimized with few repeated computations. Moreover, a simple, efficient, and highly effective map generalization method is proposed to reduce computation load without an accuracy loss. The flexibility of HiAccess enables it to work well when applied to different accessibility analysis models. To further demonstrate the applicability of HiAccess, a case study of settlement sites selection for poverty alleviation in Xiangxi, Central China, is carried out. The accessibility of jobs, health care, educational resources, and other public facilities are comprehensively analyzed for settlement sites selection. HiAccess demonstrates the striking performance of measuring highresolution (using 100 m × 100 m grids) accessibility of a city (in total over 250k grids, roads with 232k segments, and 40 facilities) in 1 sec without preprocessing, while ArcGIS takes nearly 1 h to achieve a less satisfactory result. In additional experiments, HiAccess is tested on much larger data sets with excellent performance.

Keywords

• Geo-computation
• geo-spatial accessibility
• parallel programming
• road network construction
• map generalization