Abstract
Buffer and overlay analysis are fundamental operations which are widely used in Geographic Information Systems (GIS) for resource allocation, land planning, and other relevant fields. Real-time buffer and overlay analysis for large-scale spatial data remains a challenging problem because the computational scales of conventional data-oriented methods expand rapidly with data volumes. In this paper, we present HiBO, a visualization-oriented buffer-overlay analysis model which is less sensitive to data volumes. In HiBO, the core task is to determine the value of pixels for display. Therefore, we introduce an efficient spatial-index-based buffer generation method and an effective set-transformation-based overlay optimization method. Moreover, we propose a fully optimized hybrid-parallel processing architecture to ensure the real-time capability of HiBO. Experiments on real-world datasets show that our approach is capable of handling ten-million-scale spatial data in real time. An online demonstration of HiBO is provided (http://www.higis.org.cn: 8080/hibo).
Highlights
A buffer is defined as the zone with a certain width around a geometric geographic feature, according to a specified buffer distance, and an overlay creates a composite map by combining the geometry and attributes of multiple data layers [1]
In Spatial-Index-Based Buffer Generation (SIBBG), we employ R-tree to determine whether a pixel is in the buffers of spatial objects
This paper presents a parallel processing model, HiBO, for real-time buffer-overlay analysis when the data scale becomes extremely large
Summary
A buffer is defined as the zone with a certain width around a geometric geographic feature, according to a specified buffer distance, and an overlay creates a composite map by combining the geometry and attributes of multiple data layers [1]. Shen [10] proposed a parallel vector buffer generation method, HPBM, based on Spark [18], and conducted an experiment on a high-performance cluster which compared HBPM to three optimized parallel methods and the popular GIS software programs (Table 2); as shown, HBPM outperformed the other traditional data-oriented methods and is able to generate buffers for 597k linestring objects in around 3 min As another example, Puri [16] presented a parallel GIS system, MPI-GIS, for polygon overlay processing of two GIS layers which employs R-tree for efficient indexing and identification of potentially intersecting sets of polygon objects; using MPI-GIS, the processing time of hundred-thousand-scale datasets is in the ten-second-level
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
