Sea ice in Canadian waters is monitored through an operational program conducted by Environment Canada. The program uses several remote sensing data sources and outputs a daily ice chart which is disseminated to marine users. The chart contains information on operational sea ice parameters; namely ice type, thickness, mechanical strength and surface roughness and topography. Data fusion techniques are being developed to assist ice information retrieval from remote sensing data, particularly radar imagery data. This paper presents a new data fusion method to combine co-located and co-incident data from radar, optical and passive microwave sensors into an ice parameter retrieval scheme. Examples are presented to show how ice surface temperature (derived from infrared sensors), microwave brightness temperature (observed from microwave radiometer) and radar imagery (from RADARSAT) can be combined to improve retrieval of ice types and thickness. In addition to ice parameter retrieval, the method facilitates analysis of sub-pixel information from a coarse-resolution data (e.g. SSM/I) using a background of fine-resolution data (e.g. RADARSAT). The method allows combining multi-sensors data in physical models to retrieve surface parameters that cannot otherwise be retrieved from a single sensor observations
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