Preliminary Results of Shoreline Delineation using Thermal Imagery Maryellen Sault, Jason Woolard, Stephen White and Jon Sellars NOAA’s National Geodetic Survey, Remote Sensing Division

Objectives Develop shoreline extraction procedures using a commercial off-the-shelf broadband thermal imager. Compare thermal derived shoreline with GPS-derived shoreline. Assess the geo-positional accuracy.

Study Area

Sensor Parameters TABI Broadband push-broom imager Collects data between 8 to 12 nanometers Spectral resolution of 4,000 nanometers 48 degrees Field of View (FOV) DSS Medium format airborne digital sensor 0.15 to 1 m GSD 35 mm Zeiss Lens (55.4 degrees FOV) 55 mm Zeiss Lens (37 degrees FOV)

Sensors TABI DSS TABI DSS

NOAA Twin Otter

Acquisition Constraints Weather Swath Width Time of day Tides

Tide Coordination DSS TABI (MHW)

Data Acquisition Parameters Flying Height359 m (1,200 ft) AGL Flying Speed115 knots Swath Width326 m Image GSD1 m Flying Height1524 m (5,000 ft) AGL Flying Speed115 knots Footprint1020 m Image GSD0.25 m TABI DSS

Kinematic GPS Shoreline

Accuracy Assessment

Ground Control Point Identification

DSS Accuracy Assessment Results RMSE X = 0.21 m RMSE Y = 0.18 m RMSE Z = 0.51 m Total RMSE = 0.28 m N = 38 GSD = 0.25m

TABI Accuracy Assessment Results RMSE X = 1.01 m RMSE Y = 0.81 m Total RMSE = 1.67 m N = 11 GSD = 1.0 m

Temperature Profile

Preliminary Shoreline Extraction Results GPS MHW (generalized) MHW

Preliminary Shoreline Extraction Results

Lessons Learned Acquisition constraints must be taken into account during mission planning Obtaining reference data is critical to assessing the positional accuracy of the data products Determining the stage of tide during the time of data acquisition is crucial when trying to extract shoreline Preliminary results indicate that shoreline can be auto-extracted from thermal imagery