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
Link To Document