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ISPRS Int. J. Geo-Inf. 2018, 7(7), 273; https://doi.org/10.3390/ijgi7070273

Using High-Performance Computing to Address the Challenge of Land Use/Land Cover Change Analysis on Spatial Big Data

1
Research Center of Government Geographic Information System, Chinese Academy of Surveying and Mapping, Beijing 100830, China
2
Institute of Geographical Sciences, Henan Academy of Sciences, Zhengzhou 450052, China
*
Authors to whom correspondence should be addressed.
Received: 30 April 2018 / Revised: 28 June 2018 / Accepted: 6 July 2018 / Published: 11 July 2018
(This article belongs to the Special Issue Geospatial Big Data and Urban Studies)
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Abstract

Land use/land cover change (LUCC) analysis is a fundamental issue in regional and global geography that can accurately reflect the diversity of landscapes and detect the differences or changes on the earth’s surface. However, a very heavy computational load is often unavoidable, especially when processing multi-temporal land cover data with fine spatial resolution using more complicated procedures, which often takes a long time when performing the LUCC analysis over large areas. This paper employs a graph-based spatial decomposition that represents the computational loads as graph vertices and edges and then uses a balanced graph partitioning to decompose the LUCC analysis on spatial big data. For the decomposing tasks, a stream scheduling method is developed to exploit the parallelism in data moving, clipping, overlay analysis, area calculation and transition matrix building. Finally, a change analysis is performed on the land cover data from 2015 to 2016 in China, with each piece of temporal data containing approximately 260 million complex polygons. It took less than 6 h in a cluster with 15 workstations, which was an indispensable task that may surpass two weeks without any optimization. View Full-Text
Keywords: LUCC analysis; spatial big data; high-performance computing; spatial decomposition LUCC analysis; spatial big data; high-performance computing; spatial decomposition
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kang, X.; Liu, J.; Dong, C.; Xu, S. Using High-Performance Computing to Address the Challenge of Land Use/Land Cover Change Analysis on Spatial Big Data. ISPRS Int. J. Geo-Inf. 2018, 7, 273.

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