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An Informatics Approach for Smart Evaluation of Water Quality Related Ecosystem Services

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Data Science (ICDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9208))

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Abstract

Understanding the relationship between water quality and ecosystem services valuation requires a broad range of approaches and methods from the domains of environmental science, ecology, physics and mathematics. The fundamental challenge is to decode the association between ‘ecosystem services geography’ with water quality distribution in time and in space. This demands the acquisition and integration of vast amounts of data from various domains in many formats and types. Here we present our system development concept to support the research in this field. We outline a technological approach that harnesses the power of data with scientific analytics and technology advancement in the evolution of a data ecosystem to evaluate water quality. The framework integrates the mobile applications and web technology into citizen science, environmental simulation and visualization. We describe a schematic design that links water quality monitoring and technical advances via collection by citizen scientists and professionals to support ecosystem services evaluation. These would be synthesized into big data analytics to be used for assessing ecosystem services related to water quality. Finally, the paper identifies technical barriers and opportunities, in respect of big data ecosystem, for valuating water quality in ecosystem services assessment.

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Acknowledgments

We thank technical support of Mr. Biren Rathod and Neil Bailey in developing web platforms. This work is under the support of NERC national capability fund and Earthwatch Institute’s collaborative grant.

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Correspondence to Weigang Yan .

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Yan, W., Hutchins, M., Loiselle, S., Hall, C. (2015). An Informatics Approach for Smart Evaluation of Water Quality Related Ecosystem Services. In: Zhang, C., et al. Data Science. ICDS 2015. Lecture Notes in Computer Science(), vol 9208. Springer, Cham. https://doi.org/10.1007/978-3-319-24474-7_24

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  • DOI: https://doi.org/10.1007/978-3-319-24474-7_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24473-0

  • Online ISBN: 978-3-319-24474-7

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