A theoretical approach to the use of cyberinfrastructure in geographical analysis Export

@article{Wang09, abstract = {This paper presents a theoretical approach that has been developed to capture the computational intensity and computing resource requirements of geographical data and analysis methods. These requirements are then transformed into a common framework, a grid-based representation of a spatial computational domain, which supports the efficient use of emerging cyberinfrastructure environments. Two key types of transformational functions (data-centric and operation-centric) are identified and their relationships are explained. The application of the approach is illustrated using two geographical analysis methods: inverse distance weighted interpolation and the \  spatial statistic. We describe the underpinnings of these two methods, present their conventional sequential algorithms, and then address their latent parallelism based on a spatial computational domain representation. Through the application of this theoretical approach, the development of domain decomposition methods is decoupled from specific high-performance computer architectures and task scheduling implementations, which makes the design of generic parallel processing solutions feasible for geographical analyses.}, address = {Bristol, PA, USA}, author = {Wang, Shaowen and Armstrong, Marc P.}, citeulike-article-id = {4162553}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1517588}, citeulike-linkout-1 = {http://dx.doi.org/10.1080/13658810801918509}, citeulike-linkout-2 = {http://www.ingentaconnect.com/content/tandf/tgis/2009/00000023/00000002/art00003}, doi = {10.1080/13658810801918509}, issn = {1365-8816}, journal = {Int. J. Geogr. Inf. Sci.}, keywords = {geospatial, grid-computing, partitioning}, number = {2}, pages = {169--193}, posted-at = {2009-10-28 16:07:41}, priority = {2}, publisher = {Taylor \& Francis, Inc.}, title = {A theoretical approach to the use of cyberinfrastructure in geographical analysis}, url = {http://dx.doi.org/10.1080/13658810801918509}, volume = {23}, year = {2009} }

TY - JOUR ID - Wang09 L3 - citeulike-article-id:4162553 N2 - This paper presents a theoretical approach that has been developed to capture the computational intensity and computing resource requirements of geographical data and analysis methods. These requirements are then transformed into a common framework, a grid-based representation of a spatial computational domain, which supports the efficient use of emerging cyberinfrastructure environments. Two key types of transformational functions (data-centric and operation-centric) are identified and their relationships are explained. The application of the approach is illustrated using two geographical analysis methods: inverse distance weighted interpolation and the   spatial statistic. We describe the underpinnings of these two methods, present their conventional sequential algorithms, and then address their latent parallelism based on a spatial computational domain representation. Through the application of this theoretical approach, the development of domain decomposition methods is decoupled from specific high-performance computer architectures and task scheduling implementations, which makes the design of generic parallel processing solutions feasible for geographical analyses. IS - 2 JF - Int. J. Geogr. Inf. Sci. SN - 1365-8816 AD - Bristol, PA, USA EP - 193 TI - A theoretical approach to the use of cyberinfrastructure in geographical analysis PB - Taylor \& Francis, Inc. VL - 23 SP - 169 KW - geospatial KW - grid-computing KW - partitioning AU - Wang, Shaowen AU - Armstrong, Marc PY - 2009/// UR - http://dx.doi.org/10.1080/13658810801918509 ER -