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Full-Text Articles in Social and Behavioral Sciences
A Parallel Computing Approach To Fast Geostatistical Areal Interpolation, Qingfeng Guan, Phaedon Kyriakidis, Michael Goodchild
A Parallel Computing Approach To Fast Geostatistical Areal Interpolation, Qingfeng Guan, Phaedon Kyriakidis, Michael Goodchild
Department of Geography: Faculty Publications
Areal interpolation is the procedure of using known attribute values at a set of (source) areal units to predict unknown attribute values at another set of (target) units. Geostatistical areal interpolation employs spatial prediction algorithms, i.e., variants of Kriging, which explicitly incorporate spatial autocorrelation and scale differences between source and target units in the interpolation endeavor. When all the available source measurements are used for interpolation, i.e., when a global search neighborhood is adopted, geostatistical areal interpolation is extremely computationally intensive. Interpolation in this case requires huge memory space and massive computing power, even with the dramatic improvement introduced by …
A General-Purpose Parallel Raster Processing Programming Library Test Application Using A Geographic Cellular Automata Model, Qingfeng Guan, Keith C. Clarke
A General-Purpose Parallel Raster Processing Programming Library Test Application Using A Geographic Cellular Automata Model, Qingfeng Guan, Keith C. Clarke
Department of Geography: Faculty Publications
A general-purpose parallel Raster Processing programming Library (pRPL) was developed and applied to speed up a commonly used Cellular Automaton model with known tractability limitations. The library is suitable for use by geographic information scientists with basic programming skills, but who lack knowledge and experience of parallel computing and programming. pRPL is a general-purpose programming library that provides generic support for raster processing, including local-scope, neighborhood-scope, regional-scope, and global-scope algorithms as long as they are parallelizable. The library also supports multi-layer algorithms. Besides the standard data domain decomposition methods, pRPL provides a spatially-adaptive quad-tree-based decomposition to produce more evenly distributed …
Prpl: An Open-Source General-Purpose Parallel Raster Processing Programming Library, Qingfeng Guan
Prpl: An Open-Source General-Purpose Parallel Raster Processing Programming Library, Qingfeng Guan
Department of Geography: Faculty Publications
pRPL is an open-source general-purpose programming library developed by the author to parallelize almost any raster-processing algorithm with any arbitrary neighborhood configuration, and support any data type. This paper introduces the advanced features of pRPL, compares it with other similar programming libraries, and demonstrates the performance of a parallel geographic Cellular Automata (CA) model developed using pRPL with real-world datasets. In conclusion, pRPL effectively reduces the development complexity of parallel programming, and efficiently reduces the computing time.