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envirnmental Informatics

Journal Article


Abstract


  • Environmental Informatics uses a panoply of tools from the statistics, mathematics,

    computing, and visualization disciplines. It uses these tools to reveal, quantify, and

    validate scientific hypotheses in the environmental sciences, with the quantification of

    uncertainty central to its approach. There is nowa strong recognition that scientificmodels

    need to incorporate stochastic components throughout: While it has always been recognized

    that data have a component of measurement error, attention is now being given

    to the quantification of model error, and it is becoming accepted by environmental scientists

    that probability models for the latter allow for a coherent way to make scientific

    inference. In Environmental Informatics, uncertaintymay be assigned not only to data sets

    of measurements but also to computer-generated climate-model output.Methodological

    advances, in the form of hierarchical statistical models and the accompanying computational

    developments, have expanded the scope of statistical analyses into very large

    spatial domains. This has led to studies of the dynamical evolution of entire spatial fields

    of geophysical variables, where results are given in terms of predictive distributions. Environmental

    Informatics is not only involved in characterizing the environment, it can also

    be used to make decisions about mitigation and adaptation strategies. The steps taken by

    environmental scientists, from data to information, from information to knowledge, and

    from knowledge to decisions, are all taken in the presence of uncertainty. Environmental

    Informatics encompasses all these aspects.

Publication Date


  • 2017

Citation


  • Cressie, N., Burden, S., Shumack, C., Zammit-Mangion, A. & Zhang, B. (2017). envirnmental Informatics. Wiley StatsRef, 1-8.

Number Of Pages


  • 7

Start Page


  • 1

End Page


  • 8

Abstract


  • Environmental Informatics uses a panoply of tools from the statistics, mathematics,

    computing, and visualization disciplines. It uses these tools to reveal, quantify, and

    validate scientific hypotheses in the environmental sciences, with the quantification of

    uncertainty central to its approach. There is nowa strong recognition that scientificmodels

    need to incorporate stochastic components throughout: While it has always been recognized

    that data have a component of measurement error, attention is now being given

    to the quantification of model error, and it is becoming accepted by environmental scientists

    that probability models for the latter allow for a coherent way to make scientific

    inference. In Environmental Informatics, uncertaintymay be assigned not only to data sets

    of measurements but also to computer-generated climate-model output.Methodological

    advances, in the form of hierarchical statistical models and the accompanying computational

    developments, have expanded the scope of statistical analyses into very large

    spatial domains. This has led to studies of the dynamical evolution of entire spatial fields

    of geophysical variables, where results are given in terms of predictive distributions. Environmental

    Informatics is not only involved in characterizing the environment, it can also

    be used to make decisions about mitigation and adaptation strategies. The steps taken by

    environmental scientists, from data to information, from information to knowledge, and

    from knowledge to decisions, are all taken in the presence of uncertainty. Environmental

    Informatics encompasses all these aspects.

Publication Date


  • 2017

Citation


  • Cressie, N., Burden, S., Shumack, C., Zammit-Mangion, A. & Zhang, B. (2017). envirnmental Informatics. Wiley StatsRef, 1-8.

Number Of Pages


  • 7

Start Page


  • 1

End Page


  • 8