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Framing data science, analytics and statistics around the digital earth concept

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  • E. Marian Scott

Abstract

Environmental data science can be shaped around the concepts of data streams (or the data deluge), and both data driven and process models. Together they lead to the concept of a digital earth. In this short opinion piece, I reflect on some of the challenges in truly realizing the digital earth concept.

Suggested Citation

  • E. Marian Scott, 2023. "Framing data science, analytics and statistics around the digital earth concept," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
    • Handle: RePEc:wly:envmet:v:34:y:2023:i:2:n:e2732
    DOI: 10.1002/env.2732
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    References listed on IDEAS

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    1. Jerome H. Friedman, 2001. "The Role of Statistics in the Data Revolution?," International Statistical Review, International Statistical Institute, vol. 69(1), pages 5-10, April.
    2. C. J. Wilkie & C. A. Miller & E. M. Scott & R. A. O'Donnell & P. D. Hunter & E. Spyrakos & A. N. Tyler, 2019. "Nonparametric statistical downscaling for the fusion of data of different spatiotemporal support," Environmetrics, John Wiley & Sons, Ltd., vol. 30(3), May.
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    Cited by:

    1. Wesley S. Burr & Nathaniel K. Newlands & Andrew Zammit‐Mangion, 2023. "Environmental data science: Part 2," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
    2. Sara Zapata‐Marin & Alexandra M. Schmidt & Scott Weichenthal & Eric Lavigne, 2023. "Modeling temporally misaligned data across space: The case of total pollen concentration in Toronto," Environmetrics, John Wiley & Sons, Ltd., vol. 34(8), December.

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