• DocumentCode
    2123539
  • Title

    GIS spatial statistical analysis of groundwater in GTA, Canada

  • Author

    Zhang, Zhenghe ; Cheng, Qiuming

  • Author_Institution
    Dept. of Geogr., York Univ., Toronto, Ont., Canada
  • Volume
    4
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    2229
  • Abstract
    A number of geological, hydrological, and hydrogeological features related to the aquifers in the Oak Ridges Moraine area extracted from the MOEE water well data, digital geological map, remote sensed Landsat TM images were mapped and analyzed using statistical approaches and GIS. Using the flowing wells as training points, the weights of evidence model was applied to describe the spatial pattern of the high yield confined aquifers, and to measure the correlation between the flowing wells and the regional hydrogeological features. This has led to the identification of binary evidential features to predicting the potential distributions of confined aquifers. These binary patterns correlated to the locations of flowing wells were integrated using multivariate logistic regression model and a predictive map was created to illustrate the potential distributions of confined aquifers in the ORM area. It has been demonstrated that the weights of evidence and logistic regression models implemented in GIS can be used as effective analytical tools to predict the potential of high yield confined aquifers in the study area. The predictive result can be used to interpret the potentia interactions between ground water and surface water system such as river baseflow, ponds and lakes.
  • Keywords
    groundwater; Canada; GIS; GTA; Oak Ridges Moraine; Ontario; Toronto; aquifer; flowing well; groundwater; high yield confined aquifers; hydrology; river baseflow; spatial pattern; spatial statistical analysis; surface water; Data mining; Geographic Information Systems; Geologic measurements; Geology; Image analysis; Logistics; Predictive models; Remote sensing; Satellites; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
  • Print_ISBN
    0-7803-7536-X
  • Type

    conf

  • DOI
    10.1109/IGARSS.2002.1026503
  • Filename
    1026503