INCORPORATING REMOTE SENSING INTO A HYDROGEOLOGIC INVESTIGATION OF A PROTECTED WETLAND

The Wagner Natural Area (WNA) is a 260-hectare conservation area near Edmonton, Alberta. It includes numerous calcareous springs that flow throughout the year. Tamarack and mixed spruce forests, marl ponds, and meadows, as well as a large variety of rare orchid species, are found within this wetland. However, rapidly encroaching development threatens the survival of the unusual and rich biodiversity of WNA. Therefore, understanding the role that groundwater discharge plays in maintaining this wetland complex is critical for the protection of this area. A detailed geological, geophysical and hydrogeological study of the area is being undertaken to determine the interaction between groundwater, geological and surficial features, and vegetation observed at WNA. Remote sensing is being used to integrate surficial signals and flow features with the subsurface observations. Panchromatic and multi-spectral Quickbird images were acquired on 15 May 2006 showing the WNA at the center of each 10-kilometre by 6-kilometre image. The 4-band, 2.3m resolution multi-spectral data was processed using the Definiens Imaging program, eCognition, to perform a land cover classification using an object-based approach. Soil and vegetation surveys provided ground truthing data to verify the accuracy of the classification by comparing the landcover types assigned by the software to the soil and vegetation polygons from the surveys. The resultant land cover map in conjunction with the high resolution panchromatic data and topographic data obtained from a 25-metre digital elevation model provided an excellent foundation for displaying subsurface geological, geophysical and hydrogeological information. More importantly, this mapping technique clearly identified important surficial features and characteristics, such as marl ponds and phreatophytic vegetation, that are directly dependent on groundwater, as well as areas of variable saturation and local discharge, which are difficult to map in the field.