High-Resolution Imagery and Terrain Model for Collaborative Research of Environmental Change at Barrow, Alaska

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This projects will create and release of three suites of spatial data products. The first is high-resolution, orthorectified radar imagery (ORRI, with 1.25 m grid cell spacing) and a co-registered, high-resolution Digital Elevation Model (DEM; 5 m grid cell spacing; 1 m vertical accuracy). The second suite is satellite imagery purchased through AeroMap U.S., specifically orthorectified panchromatic (0.7 m grid cells) and multispectral (2.8 m grid cells) imagery acquired by DigitalGlobe with the new QuickBird satellite. Third is a time-series set of orthorectified air-photo mosaics. After processing, the DEM and imagery would be made available to all NSF-funded researchers through the ARCSS Data Coordination Center.In the vicinity of Barrow, Alaska including the Barrow Environmental Observatory (BEO) there are more than 35 currently funded NSF research projects. These multi- and interdisciplinary studies primarily address local to global effects of environmental sensitivity and climate change. Many of the projects utilize quantitative spatial analysis through remote sensing and Geographic Information Systems (GIS). Others would utilize high-resolution spatial datasets if they were available. On a project by project basis, research groups work piecemeal with spatial data for their own, small, disconnected field areas. Sharing datasets is difficult due to differences in map projection, datum, data format, extent, and distribution channels. This new activity will provide the research community high-resolution data and images resulting in tangible scientific benefits across numerous disciplines, increasing the efficiency and significance of current and future research. On-going projects that would benefit are research on ecosystem dynamics, terrestrial-atmospheric fluxes of greenhouse gases, landscape dynamics, coastal flooding and erosion, permafrost melting, other environmental responses to unprecedented arctic warming, and other topics. These environmentally and societally relevant scientific problems can be addressed in new ways and with greater success using digital topography and imagery. By orders of magnitude, the spatial datasets would be more precise, accurate, and useful than existing data layers. They would permit state-of-the-art analysis for years to come, and would establish a temporal baseline for decades of change-detection studies. This vision is shared by this proposal's twelve collaborators from eight research institutions. With shared needs for high quality spatial information, a modest effort now would leverage results and promote interdisciplinary collaboration.