FIELD DATA COLLECTION AND GROUND-TRUTHING OF GEOSPATIAL AND HYDROLOGIC ANALYSES OF WATERSHEDS NEAR KANGERLUSSAUQ, GREENLAND

Navigation and terrain analyses in remote areas such as the Greenlandic arctic are difficult due to the lack of large-scale cartographic products. Existing maps of the Kangerlussuaq area are at scales of 1:100,000, or less, with 25-meter contours. Better detailed maps are needed for watershed delineation, predicting stream locations, and effective spatial distribution of sample sites. Additionally, a basemap is necessary to facilitate the presentation and recognition of spatial trends that may be present in sample data. Such maps can be created, hydrologically analyzed, and taken to the field for testing using ASTER Global Digital Elevation Models, Landsat 7 satellite imagery, an iPhone, and the ArcGIS 10.0 suite. For work around the Kangerlussuaq region in Greenland, 10-meter contours were interpolated using ArcGIS’s standard functions. Stream locations and relative sizes were modeled using a custom built toolbox and Python scripting. Watersheds were delineated using the included hydrology toolset and classified as either proglacial or deglaciated using Landsat imagery composed to maximize thermal and visual contrast. These newly created maps were loaded into Avenza PDF Maps on an iPhone 5 and used for field data collection, compilation (e.g. location, water sample parameters, sample site photographs) and ground-truthing of predicted hydrology. Maps created contained hydrologic data not commercially available and could be easily tailored for the task at hand. In July 2013, the improved maps were taken to the field for ground-truthing and were used to identify water sampling sites. Watershed delineation proved to be significantly more accurate than predicting stream location, likely due to the seasonal nature of arctic rivers. Potentially flowing watersheds could therefore be identified in advance, greatly streamlining the water sample selection process. Enhanced contour intervals facilitated ease of navigation to selected sample sites. The generated maps lacked local names and reference points, a feature that future cartographic products could certainly benefit from. The iPhone proved to be a powerful field data collection tool as it updated position in real time on the created maps and streamlined digital data entry and publication of georeferenced data tables and photos to Dropbox and Google Earth.