1,722,450 research outputs found
The Roy Bose simultaneous confidence interval approach to multivariate multitemporal pairwise comparisons within and between objects
Full text linkGeocomputation 2007, NUI Maynooth, Ireland, 3rd to 5th September 2007MANOVA and Roy-Bose simultaneous confidence intervals when combined with distribution matrices of ordered differences and ordered difference component vectors define the he Roy Bose simultaneous confidence interval approach to multivariate multitemporal pairwise comparisons within and between objects. While the objects used in this experiment were species of trees, the methodology may be equally applicable to any class of objects which exhibit multitemporal and multivariate changes in p-dimensional response profiles or vectors with time. The methodology is most easily applied to balanced data.Author has checked copyrightDG 22/11/1
Geocomputation and open source software: components and software stacks.
Full text linkGeocomputation, with its necessary focus on software development and methods innovation, has enjoyed a close relationship with free and open source software communities. These extend from communities providing the numerical infrastructure for computation, such as BLAS (Basic Linear Algebra Subprograms),through language communities around Python, Java and others, to communities supporting spatial data handling, especially the projects of the Open Source Geospatial Foundation. This chapter surveys the stack of software components available for geocomputation from these sources, looking in most detail at the R language and environment, and how OSGeo projects have been interfaced with it. In addition, attention will be paid to open development models and community participation in software development. Since free and open source geospatial software has also achieved a successively greater presence in proprietary software as computational platforms evolve, the chapter will close with some indications of future trends in software component stacks, using Terralib as an example.Geocomputation; Open source software
Geocomputation with R
Full text linkBook Review of:
Geocomputation with R.
Robin LovelaceJakub Nowosad & Jannes Muenchow . Geocomputation with R. Chapman and Hall/CRC Press: UK, 2019, 335 pp. ISBN: 9781138304512, £66.99 (hbk), ISBN: 9780203730058, £60.29 (eBook) Resources and code: https://geocompr.robinlovelace.net
Reviewed by: Chris Brunsdon, National Centre for Geocomputation, Maynooth University, Irelan
GeoComputation, Second Edition
No full textA revision of Openshaw and Abraharts seminal work, 'GeoComputation, Second Edition' retains influences of its originators while also providing updated, state-of-the-art information on changes in the computational environment. In keeping with the field's development, this new edition takes a broader view and provides comprehensive coverage across the field of GeoComputation
Geocomputation and Spatial Analytics. GeoComputation 2019
No full textGeocomputation and spatial analytics have a shared history, and often times the distinction between the two areas is less than clear. While both occupy a place under the banner ofGIScience, the emergence of spatial data science as a more broadly consuming grouping perhaps makes any distinctions less significant. Irrespective of the overarching label ornaming preference, there are lessons to be learned about specification, representation, implementation and interpretation, all of which have implications for openness. This paper provides a comparative overview, delving into the nuances of geocomputation and spatial analytics. This is done to make a number of points associated with recent trends in open spatial data science.</div
Geocomputation: a primer
No full textBook synopsis: Geocomputation A Primer edited by Paul A Longley Sue M Brooks Rachael McDonnell School of Geographical Sciences, University of Bristol, UK and Bill Macmillan School of Geography, University of Oxford, UK This book encompasses all that is new in geocomputation. It is also a primer - that is, a book which sets out the foundations and scope of this important emergent area from the same contemporary perspective. The catalyst to the emergence of geocomputation is the new and creative application of computers to devise and depict digital representations of the Earth's surface. The environment for geocomputation is provided by geographical information systems (GIS), yet geocomputation is much more than GIS. Geocomputation is a blend of research-led applications which emphasise process over form, dynamics over statics, and interaction over passive response. This book presents a timely blend of current research and practice, written by the leading figures in the field. It provides insights to a new and rapidly developing area, and identifies the key foundations to future developments. It should be read by all who seek to use geocomputational methods for solving real world problems
GeoComputation 2019 front matter. GeoComputation 2019
No full textThis is the front matter for the GeoComputation 2019 conference, including welcome, figshare Collections definition, programme, the Spatial Data Science with Python workshop, membership of the organising committee, membership of the international scientific review committee, and sponsors
International Journal of Geographical Information Science A strategy for raster-based geocomputation under different parallel computing platforms A strategy for raster-based geocomputation under different parallel computing platforms
No full textThe demand for parallel geocomputation based on raster data is constantly increasing with the increase of the volume of raster data for applications and the complexity of geocomputation processing. The difficulty of parallel programming and the poor portability of parallel programs between different parallel computing platforms greatly limit the development and application of parallel raster-based geocomputation algorithms. A strategy that hides the parallel details from the developer of raster-based geocomputation algorithms provides a promising way towards solving this problem. However, existing parallel raster-based libraries cannot solve the problem of the poor portability of parallel programs. This paper presents such a strategy to overcome the poor portability, along with a set of parallel raster-based geocomputation operators (PaRGO) designed and implemented under this strategy. The developed operators are compatible with three popular types of parallel computing platforms: graphics processing unit supported by compute unified device architecture, Beowulf cluster supported by message passing interface (MPI), and symmetrical multiprocessing cluster supported by MPI and open multiprocessing, which make the details of the parallel programming and the parallel hardware architecture transparent to users. By using PaRGO in a style similar to sequential program coding, geocomputation developers can quickly develop parallel raster-based geocomputation algorithms compatible with three popular parallel computing platforms. Practical applications in implementing two algorithms for digital terrain analysis show the effectiveness of PaRGO
Increasing GeoComputational Interoperability: Towards a Standard GeoComputation API
No full textThe progress of GeoCompuation research has brought us a rich set of effective computational methods for solving geospatial problems. To increase the interoperability of these methods, we have to deal with the diversity and heterogeneity ingrained in the plurality and inclusiveness of GeoComputation. Current GeoComputational interoperability research mostly focuses on interoperability issues related to geospatial data and services producing it instead of the computational methods in GeoComputation. To address this deficiency, we propose a framework to increase the interoperability of computational methods in GeoComputation. To demonstrate the utility of the proposed framework, we adapted and implemented much of the new Java Data Mining API to support the integration of data mining methods with GeoComputation tools to provide better solutions for geospatial problems
Understanding geocomputation education: A survey and syllabi informed review
No full textGeocomputation is an interdisciplinary area of practice, intersecting at least three core areas: geographic and spatial analysis, computational approaches, and highperformance computing power. Along with the affordances of geographic information science (GIS), geography, spatial data, programming, and computation, geocomputation serves as a merger in different ways and forms to produce investigations into spatial science and geography with computational assistance. We explore the nature of teaching and learning in this variant and rapidly changing geocomputation education space through survey and syllabi review of geocomputation courses. In analyzing and summarizing responses and syllabus content, we find an area of educational practice based on a rough agglomeration of GIS, computer science, and programming, but with divergent approaches, resources, and learning methods within course structures. Given the general review here of the form of function of geocomputation courses, we present a community focused resource to continue this transformative work of understanding and linking how this area of practice functions
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