M.S. Thesis Defense Kimberly Horan The Use of Coincident Synthetic Aperture Radar and Visible Imagery to Aid in the Analysis of Photon-Counting Lidar Data Sets Over Complex Ice/Snow Surfaces Thursday, 1 August 2013, 1:00 pmCarlson Bldg. 3215 (DIRS Lab) 

Chester F. Carlson Center for Imaging Science

M.S. Thesis Defense

Kimberly Horan

The Use of Coincident Synthetic Aperture Radar

and Visible Imagery to Aid in the Analysis of

Photon-Counting Lidar Data Sets

Over Complex Ice/Snow Surfaces

Advisor: Dr. John Kerekes

Thursday, 1 August 2013, 1:00 pm 

Carlson Bldg. 3215 (DIRS Lab)

Abstract

Multi-sensor data fusion is becoming an increasingly useful tool for improving our understanding of complex environments, and can be an effective means of predicting sea level rise due to change in the mass balance of large glaciers in the Arctic and Antarctic.  A novel approach to remote sensing of the continuously changing polar environment involves the fusion of coincident Radarsat-2 (RS-2) synthetic aperture radar (SAR) imagery and Landsat 7 visible/near-infrared imagery, with digital elevation models (DEM) developed from Multiple Altimeter Beam Experimental Lidar (MABEL) data sets.

MABEL is a scaled down model of the lidar altimeter that will eventually be flown on ICESat-2, and provides dense along-track and moderate slope (cross-track) elevation data over narrow (~198 m) aircraft transects.  Because glacial terrain consists of steep slopes, crevices, glacial lakes, and outflow into the sea, accurate slope information is critical to our understanding of any changes that may be happening in the ice sheets.   Radarsat-2 is a C-band radar, operating at a wavelength of 5.55 cm, chosen partly for its ability to image the Earth under all atmospheric conditions, including clouds.  The SAR images not only provide spatial context for the elevation data found using the lidar, but also offer key insights into the consistency of the snow and ice making up the glacier, giving us some idea of mean temperature on the ice sheet.  Finally, wherever possible, Landsat 7 images provide us with information on the extent of the glacier, and additional understanding of surface conditions.

To aid in the fusion of the three data sets, proper preparation of each data set must first be performed.  For the lidar data, this required the development of a new data reduction technique, based on statistical analysis, to reduce the number of received photons to those representing the ground return.  Accordingly, the raw SAR images require calibration, speckle reduction, and geocorrection, before they can be used.  Landsat 7 bands are selected to provide the most contrast between rock and snow, and compiled into a three-band red, green, blue (RGB) image.  By analyzing images and data taken only a short time apart, we are able to accurately compare glacial surface features, with the goal of increasing our understanding of how the glacier is changing over time.