Impact of urban land-cover classification on groundwater recharge uncertainty

E.M. Ampe, I. Hamel, E. Salvadore, Jeff Dams, I. Bashir, L. Demarchi, J. Cheung-Wai Chan, H. Sahli, Frank Canters, Okke Batelaan

    Research output: Contribution to journalArticle

    19 Citations (Scopus)

    Abstract

    Objective and detailed mapping of urban land-cover types over large areas is important for hydrological modelling, as most man-made land-cover consist of sealed surfaces which strongly reduce groundwater recharge. Moreover, impervious surfaces are the predominant type in urbanized areas and can lead to increased surface runoff. Classification of man-made objects in urbanized areas is not straightforward due to similarity in spectral properties. This study examines the use of hyperspectral CHRIS-Proba images for complex urban land-cover classification of the Woluwe River catchment, Brussels, Belgium. Two methods are compared: 1) a multiscale region-based classification approach, which is based on a causal Markovian model being defined on a Multiscale Region Adjacency Tree and a set of nonparametric dissimilarity measures; and 2) a pixel based classification method with a Mahalanobis distance classifier. Multiscale region-based classification results in a Kappa value of 0.95 while pixel-based classification has a slightly lower Kappa value of 0.92. The impact of the classification method on the hydrology is estimated with the application of the WetSpass physically-based distributed water balance model. The model uncertainty is assessed with the use of a Monte Carlo simulation. Model results show that the region-based classification yields to a higher yearly recharge than the pixel-based classification. The overall uncertainty, quantified by the Monte Carlo method is lower for the region-based classification than for the pixel-based classification. The presented study indicates that the selection of the classification technique is of critical importance for the outcome of hydrological models.

    Original languageEnglish
    Article number6264066
    Pages (from-to)1859-1867
    Number of pages9
    JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    Volume5
    Issue number6
    DOIs
    Publication statusPublished - 2012

    Fingerprint Dive into the research topics of 'Impact of urban land-cover classification on groundwater recharge uncertainty'. Together they form a unique fingerprint.

  • Cite this

    Ampe, E. M., Hamel, I., Salvadore, E., Dams, J., Bashir, I., Demarchi, L., Cheung-Wai Chan, J., Sahli, H., Canters, F., & Batelaan, O. (2012). Impact of urban land-cover classification on groundwater recharge uncertainty. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(6), 1859-1867. [6264066]. https://doi.org/10.1109/JSTARS.2012.2206573