2004091014585000FALSE20040910140938002005102010435700{3732A781-E132-4C2D-B3B8-CDA13514629B}Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 4; ESRI ArcCatalog 8.3.0.800 This vector data set represents the Seaward Landfast Ice Edge (SLIE) along the coast of Northern Alaska (West of Barrow) and Northwest Canada (East to the Mackenzie Delta) for the study area which ranges from approximately 133 to 160 degrees West and 68 to 72.5 degrees North. Landfast sea ice is a seasonal phenomena in the Alaskan Arctic and throughout its annual existence, between formation in late fall and break-up in late spring, it is shaped by a range of thermodynamic and dynamic forces (Barry et al. 1979; Shapiro and Metzner, 1989). The most apparent changes are those in landfast ice area and extent when floes of ice attach to and break off from its seaward edge. The position of the SLIE over the course of the year generally advances offshore to a stable position in mid-winter before retreating with the onset of spring. However, higher frequency changes in position also occur on timescales of days to weeks, which are generally small but occasionally affect the full width of the landfast ice. The location and stability of the SLIE at any point in time affects the activities of people and wildlife in the coastal arctic as it marks the boundary between stationary, continuous sea ice and drifting deforming pack ice. It is a vital consideration for people hunting or working on the ice in determining where food sources might be or where spilt oil might go. Since landfast ice occupies the shallowest water in the arctic, its presence or absence is also important for coastal process such as erosion and sediment entrainment. These data were compiled by the University of Alaska Fairbanks to meet contract requirements for the US Mineral Management Service: Mapping and Characterization of Recurring Spring Leads and Landfast ice in the Beaufort and Chukchi Seas (AK-03-06) The files names associated with the landfast ice shapefiles derived from Radarsat mosaics are prefixed with an "r". The year and time period covering each delineation is noted with a range consisting of the day of the year for the first and last Radarsat mosaic used. For descriptive purposes, the following abbreviations are used as placeholders for real values to illustrate the naming convention: "d" = day of year and "Y" = Year. This convention follows as "rYY_ddd_ddd" where the vector based landfast ice extent derived from 2001 Radarsat mosaics covering a 16 day period would be "r01_279_295shape". Definition of landfast sea ice: The seaward landfast ice edge has been delineated from colocated Radarsat SAR imagery based on the following criteria, which are used to define landfast ice 1) The ice is contiguous with the coast 2) The ice exhibits no detectable motion over approximately 20 days The pixel size of the imagery is 100m, with a stated geolocation accuracy of 200m. The time period for which the ice must remain stationary was chosen to represent a number of synoptic periods and therefore exclude ice that temporarily comes to rest adjacent to the coast without any mechanism to hold it in place while weather patterns change. The exact time period cannot be stated universally, since ice motion, or lack thereof, is determined by examination of 3 consecutive mosaics, the time interval between which is not constant. Furthermore, each mosaic represents a time-span of between 3 and 4 days and so there maybe different time seperations between different points in any two mosaics. A more detailed explanation of the definition and delineation of the seaward landfast ice edge can be found at mms.gina.alaska.edu en University of Alaska Fairbanks 20051231 raster digital data http://mms.gina.alaska.edu r01_304_320saSee extended abstract on "Landfast sea ice extent and variability in the Alaskan Arctic derived from SAR imagery" presented at the International Geoscience and Remote Sensing Symposium, September 20-24, 2004, Anchorage, Alaska. 1996 2004 ground condition Complete None planned -160.813048-133.82419572.62029768.714097-236180.000000719220.0000002180119.0000002509919.000000 Aquatic Sciences and Fisheries Thesaurus raster landfastsea icegrounded ice Dictionary of Alaska Place Names Arctic Ocean Chukchi SeaBeaufort SeaNorth SlopeAlaskaCanada None. Any hardcopies or published datasets utilizing these data sets shall clearly indicate their source. If the user has modified the data in any way they are obligated to describe the types of modifications that they have performed. User specifically agrees not to misrepresent these datasets, nor to imply that any changes that they made were approved by the University of Alaska. Vector DatasetThe funding for this effort was provided by the US Mineral Management Service for Mapping and Characterization of Recurring Spring Leads and Landfast ice in the Beaufort and Chukchi Seas (AK-03-06, MMS-71707) Dr. Hajo EickenGeophysical InstituteUnversity of Alaska Fairbanksmailing and physical address

903 Koyukuk Dr., P.O. Box 757320

FairbanksAlaska99775-7320USA907-474-7280907-474-7290Barry, R, R.E. Moritz and J.C. Rogers,19791documentCold Regions Science and Technology1, pp129-152Shapiro, L.H and R.C. Metzner1989documentGeophysical Institute ReportUAG-R (132)Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 4; ESRI ArcCatalog 8.3.0.800r01_304_320sa-236180719220250991921801191-160.813048-133.82419572.62029768.7140971 20051020 Nuna Technologies Allison Graves Gaylord Owner / GIS Specialist mailing address

P.O. Box 1483

Homer AK 99723-1483 USA 907.399.1120 nunatech@usa.net 907.235.3476 FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time enNone.If the user has modified the data in any way they are obligated to describe the types of modifications they have performed in the supporting metadata file. User specifically agrees not to imply that changes they made were approved by the University of Alaska.None.UnclassifiedNone.http://www.esri.com/metadata/esriprof80.htmlESRI Metadata Profile ISO 19115 Geographic Information - MetadataDIS_ESRI1.0dataset UAF Geographic Information Network of Alaska (GINA) Dr. Virgil (Buck) Sharpton mailing and physical address

903 Koyukuk Drive

Fairbanks Alaska 99775-7320 USA 907.474.6663 buck.sharpton@gina.alaska.edu President's Professor of Remote Sensing8:00 a.m. - 5:00 p.m. AST Downloadable Data The University of Alaska makes no express or implied warranties (including warranties of merchantability and fitness) with respect to the character, function, or capabilities of the electronic services or products or their appropriateness for any users purposes. In no event will the University of Alaska be liable for any incidental, indirect, special, consequential or other damages suffered by the user or any other person or entity whether from the use of the electronic services or products, any failure thereof or otherwise, and in no event will the State of Alaska's liability to the requestor or anyone else exceed the fee paid for the electronic service or product. ESRI Grid 2004 ESRI Grid 0.631 0.631 http://mms.gina.alaska.edu web browser and/or FTP None These data will be made available at the request of the US Mineral Management Service via online tools provided by the Geographic Information Network of Alaska (GINA) at the University of Alaska Fairbanks. 19961015 20040715 002file://\\NUNALAPTOP\F_drive_20040902\MMS\MetadataTemplates\Revised20040914\SLIE_GRID_templateLocal Area Network0.631Raster DatasetVectorGCS_North_American_1983NAD_1983_Albersrow and columnmeters100.000000100.000000Albers Conical Equal Area55.00000065.000000-154.00000050.0000000.0000000.000000North American Datum of 1983Geodetic Reference System 806378137.000000298.257222NAD_1983_Albers2955410032981001 Landfast Ice Edge Band 1 ESRI Table2 FID Feature ID of shapefile ESRI FIDFeature ID of shapefile ESRI ObjectIDOID400 ShapeFeature ClassESRIShapeFeature Class = Polygon ESRIAreaArea of polygon ESRIAreaArea of polygon Automatically calculated by ArcGIS Perimeterperimeter of polygon ESRIPerimeterperimeter of polygon Automatically calculated by ArcGIS r###_###_Internal Feature Number ESRI / UAFr###_###_r = derived from Radarsat; # = represents day of year where each file is comprised of a date from a range of datesESRI / UAFr###_###_IDInternal Identifier ESRI / UAFr###_###_IDInternal Identifier where r = derived from Radarsat; # = represents day of year where each file is comprised of a date from a range of dates; appended by ID for IdentifierESRI / UAFGRID_CODE Grid code for cell value ESRIValue = 255 landfast iceDerived from Radarsat imagery 20051020 Map projection and datum were confirmed and checked to conform with base data sets and imagery. It should be noted that water on the surface of the ice will affect the backscatter, without necessarily affecting the stability of the ice or causing it to move. This situation is common in the Spring. Thus, if the ice immediately beyond a flooded area exhibits consistency, then the SLIE line is drawn beyond the flooded area. This is consistent with our definition of SLIE (Seaward Landfast Ice Edge.) As the ice at the mouth of a river becomes unstable during the Spring, a "hole" may develop in the landfast ice which we will not detect with this approach. This will be discussed further in reports associated with this study. Complete. A combination of automated and manual techiques have been employed to derive the Seaward Landfast Ice Edge (SLIE) shown in this data set. The study area was divided into 10 subregions in order to obtain subscenes from 460 x 460 km RADARSAT scenes that were free from mosaicking edges prior to calculating the gradient fields. Custom IDL scripts were utilized to derive the net difference between gradient fields of 3 consecutive, colocated Radarsat subscenes. The average period between scenes is 10 days. A semi-automated procedure was developed to consider 3 consecutive mosaics at a time representing an average period of 20 days. From these a magnitude image of the horizontal and vertical components of gradient difference is created. The landfast ice is characterized by dark regions of low gradient difference adjacent to the land and typically bounded by bright, linear regions of high gradient difference. The SLIE is identified by bright regions of high gradient difference. After thresholding the image at a gray value corresponding to a net backscatter gradient difference of 8 dB / km, the SLIE is more easily detected and can be manually delineated. A technique for automatically delineating the SLIE from the gradient difference images proves elusive at this time, since the SLIE can be less distinct in some areas or misidentification of a SLIE, e.g., in areas of ice surface flooding can occur. For this reason, the SLIE is manually delineated over gradient image mosaics using the corresponding source imagery for interpretation. 2004 Andy Mahoney University of Alaska Fairbanks, Geophysical Institute PhD Candidate mailing and physical address

903 Koyukuk Dr., P.O. Box 757320

Fairbanks AK 99775-7320 USA 907-474-5648 Mahoney@gi.alaska.edu business hours Email preferred. 907-474-7290 IDL 6.1 Allison Graves GaylordNuna TechnologiesOwner / GIS Specialist907.235.3476907.235.3476nunatech@usa.netEmail preferred.mailing address

POB 1483

HomerAK99603USAENVI 4.0 / ArcGIS 8.32004SLIE is manually delineated over gradient image mosaics compiled from the 10 subscenes using ENVI image processing software. Each SLIE delineation is processed and exported to GeoTIFF format using IDL routines. ArcGIS ArcToolbox batch utilities are then used to convert each GeoTiff to a 100 meter cell ArcGIS Grid file and then to a Shapefile. Low resolution browse images (*.bmp format) were generated using ArcCatalog. These browse images were then converted to *.jpg format for display on the LILIFECS web site. Final processing included a batch import of the appropriate FGDC compliant metadata template. The data sets were then bundled (and compressed) with Winzip for posting to the web. +/- 3 pixels based on co-location techniques of source imagery.300Visual inspection.