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International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems

IPMU 2018: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations pp 287–298Cite as

Spatio-Temporal Drought Identification Through Mathematical Morphology

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 854))

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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References

  1. Mishra, A.K., Singh, V.P.: A review of drought concepts. J. Hydrol. 391, 202–216 (2010). https://doi.org/10.1016/j.jhydrol.2010.07.012

    Article  Google Scholar 

  2. Tallaksen, L.M., Van Lanen, H.A.J.: Drought as a natural hazard: introduction. In: Tallaksen, L.M., Van Lanen, H.A.M. (eds.) Hydrological Drought Processes and Estimation Methods for Streamflow and Groundwater. Developments in Water Science, pp. 3–17. Elsevier, Amsterdam (2004)

    Google Scholar 

  3. Andreadis, K.M., Clark, E.A., Wood, A.W., Hamlet, A.F., Lettenmaier, D.P.: Twentieth-century drought in the conterminous United States. J. Hydrometeorol. 6(6), 985–1001 (2005). https://doi.org/10.1175/JHM450.1

    Article  Google Scholar 

  4. Lloyd-Hughes, B.: A spatio-temporal structure-based approach to drought characterisation. Int. J. Climatol. 32(3), 406–418 (2011). https://doi.org/10.1002/joc.2280

    Article  Google Scholar 

  5. McKee, T.B., Doesken, N.J., Kleist, J.: The relationship of drought frequency and duration to time scales. In: Proceedings of the Eight Conference on Applied Climatology, pp. 179–184. American Meteorological Society, Anaheim (1993)

    Google Scholar 

  6. Palmer, W.C.: Meteorologic drought. Research Paper 45, US Department of Commerce, Weather Bureau (1965)

    Google Scholar 

  7. Sheffield, J., Goteti, G., Wen, F., Wood, E.F.: A simulated soil moisture based drought analysis for the United States. J. Geophys. Res. 109, D24108 (2004). https://doi.org/10.1029/2004JD005182

  8. Sheffield, J., Wood, E.F.: Drought Past Problems and Future Scenarios. Earthscan, London (2011)

    Google Scholar 

  9. Sheffield, J., Wood, E.F.: Characteristics of global and regional drought, 1950–2000: an analysis of soil moisture data from off-line simulation of the terrestrial hydrological cycle. J. Geophys. Res. 112, D17115 (2007). https://doi.org/10.1029/2006JD008288

  10. Serra, J.: Introduction to mathematical morphology. Comput. Vis. Graph. Image Process. 35(3), 283–305 (1986)

    Article  Google Scholar 

  11. Soille, P., Pesaresi, M.: Advances in mathematical morphology applied to geoscience and remote sensing. IEEE Trans. Geosci. Remote Sens. 40(9), 2042–2055 (2002). https://doi.org/10.1109/TGRS.2002.804618

    Article  Google Scholar 

  12. Dufour, A., Tankyevych, O., Naegel, B., Talbot, H., Ronse, C., Baruthio, J., Dokládal, P., Passat, N.: Filtering and segmentation of 3D angiographic data: advances based on mathematical morphology. Med. Image Anal. 17, 147–164 (2013). https://doi.org/10.1016/j.media.2012.08.004

    Article  Google Scholar 

  13. Peters II, R.A., Nichols, J.A.: Rocket plume image sequence enhancement using 3D operators. IEEE Trans. Aerospace Electron. Syst. 33(2), 485–498 (1997)

    Article  Google Scholar 

  14. Paris, S., Sillon, F.: Robust acquisition of 3D informations from short image sequences. Graph. Models 65, 222–238 (2003)

    Article  Google Scholar 

  15. Pierret, A., Capowiez, Y., Belzunces, L., Moran, C.J.: 3D reconstruction and quantification of macropores using X-ray computed tomography and image analysis. Geoderma 106, 247–271 (2002). https://doi.org/10.1016/S0016-7061(01)00127-6

    Article  Google Scholar 

  16. Mao, X., Zhang, B., Deng, H., Zou, Y., Chen, J.: Three-dimensional morphological analysis method for geologic bodies and its parallel implementation. Comput. Geosci. 96, 11–22 (2016). https://doi.org/10.1016/j.cageo.2016.07.004

    Article  Google Scholar 

  17. Miralles, D.G., Holmes, T.R.H., De Jeu, R.A.M., Gash, J.H., Meesters, A.G.C.A., Dolman, A.J.: Global land-surface evaporation estimated from satellite-based observations. Hydrol. Earth Syst. Sci. 15, 453–469 (2011). https://doi.org/10.5194/hess-15-453-2011

    Article  Google Scholar 

  18. Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev. 10, 1903–1925 (2017). https://doi.org/10.5194/gmd-10-1903-2017

    Article  Google Scholar 

  19. McCarthy, J.J., Canziani, O.F., Leary, N.A., Dokken, D.J., White, K.S.: Working group II: impacts, adaptation, and vulnerability. Technical report, International Panel on Climate Change IPCC: Third Assessment Report (2001)

    Google Scholar 

  20. Byun, H.R., Wilhite, D.A.: Objective quantification of drought severity and duration. J. Clim. 12(9), 2747–2756 (1999)

    Article  Google Scholar 

  21. Haralick, R.M., Sternberg, S.R., Zhuang, X.: Image analysis using mathematical morphology. IEEE Trans. Pattern Anal. Mach. Intell. 9(4), 532–550 (1987)

    Article  Google Scholar 

  22. Serra, J., Vincent, L.: An overview of morphological filtering. Circ. Syst. Sig. Process. 11(1), 47–108 (1992)

    Article  MathSciNet  Google Scholar 

  23. Dougherty, E.R., Lotufo, R.A.: Hands-on morphological image processing. In: Tutorial Texts in Optical Engineering, p. 272. SPIE Publications (2003)

    Google Scholar 

  24. Soille, P.: Morphological Image Analysis: Principles and Applications. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-662-05088-0

    Book  MATH  Google Scholar 

  25. Yager, R.R.: Ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Trans. Syst. Man Cybern. 18, 183–190 (1988)

    Article  Google Scholar 

  26. Fullér, R., Majlender, P.: An analytic approach for obtaining maximal entropy OWA operator weights. Fuzzy Sets Syst. 124, 53–57 (2001). https://doi.org/10.1016/S0165-0114(01)00007-0

    Article  MathSciNet  Google Scholar 

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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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Authors and Affiliations

  1. KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, 9000, Ghent, Belgium

    Hilde Vernieuwe & Bernard De Baets

  2. Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, 9000, Ghent, Belgium

    Niko E. C. Verhoest

Authors
  1. Hilde Vernieuwe
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  2. Bernard De Baets
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  3. Niko E. C. Verhoest
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Corresponding author

Correspondence to Hilde Vernieuwe .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Universidad de Granada, Granada, Spain

    David A. Pelta

  5. Universidad de Málaga, Málaga, Málaga, Spain

    Inma P. Cabrera

  6. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  7. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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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

  • Print ISBN: 978-3-319-91475-6

  • Online ISBN: 978-3-319-91476-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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