A minimum-volume oriented bounding box strategy for improving the performance of urban cellular automata based on vectorization and parallel computing technology

A minimum-volume oriented bounding box strategy for improving the performance of urban cellular automata based on vectorization and parallel computing technology

As an effective tool for simulating spatiotemporal urban processes in the real world, urban cellular automata (CA) models involve multiple data layers and complicated calibration algorithms, which make their computational capability become a bottleneck. Numerous approaches and techniques have been a...

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Bibliographic Details
Main Authors: Chang Xia, Bin Zhang, Haijun Wang, Si Qiao, Anqi Zhang
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:GIScience & Remote Sensing
Subjects:
urban cellular automata
bounding box
vectorization
parallel computing
geographical simulation
Online Access:http://dx.doi.org/10.1080/15481603.2019.1670974

Internet

http://dx.doi.org/10.1080/15481603.2019.1670974

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