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Link to original content: https://doi.org/10.1007/978-3-319-91476-3_24
Spatio-Temporal Drought Identification Through Mathematical Morphology | SpringerLink
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Spatio-Temporal Drought Identification Through Mathematical Morphology

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (IPMU 2018)

Abstract

Droughts are initiated by a lack of precipitation over a large area and a long period of time. In order to be able to estimate the possible impacts of droughts, it is important to identify and characterise these events. Describing a drought is, however, not such an easy task as it represents a spatio-temporal phenomenon, with no clear start and ending, trailing from one place to another. This study tries to objectively identify droughts in space and time by applying operators from mathematical morphology. On the basis of the identified droughts, OWA operators are employed to characterise the events in order to aid farmers, water managers, etc. in coping with these events.

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Acknowledgement

This work was performed in the framework of the STEREO-project SR/00/302 (‘Hydras+’), funded by the Belgian Science Policy.

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Correspondence to Hilde Vernieuwe .

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Vernieuwe, H., De Baets, B., Verhoest, N.E.C. (2018). Spatio-Temporal Drought Identification Through Mathematical Morphology. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-319-91476-3_24

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  • DOI: https://doi.org/10.1007/978-3-319-91476-3_24

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  • Publisher Name: Springer, Cham

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