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Fily, M.

Publications and source records attributed to Fily, M..

Simulation of the Microwave Emission of Multi-layered Snowpacks Using the Dense Media Radiative Transfer Theory: the DMRT-ML Model

DMRT-ML is a physically based numerical model designed to compute the thermal microwave emission of a given snowpack. Its main application is the simulation of brightness temperatures at frequencies in the range 1-200 GHz similar to those acquired routinely by spacebased microwave radiometers. The model is based on the Dense Media Radiative Transfer (DMRT) theory for the computation of the snow scattering and extinction coefficients and on the Discrete Ordinate Method (DISORT) to numerically solve the radiative transfer equation. The snowpack is modeled as a stack of multiple horizontal snow layers and an optional underlying interface representing the soil or the bottom ice. The model handles both dry and wet snow conditions. Such a general design allows the model to account for a wide range of snow conditions. Hitherto, the model has been used to simulate the thermal emission of the deep firn on ice sheets, shallow snowpacks overlying soil in Arctic and Alpine regions, and overlying ice on the large icesheet margins and glaciers. DMRT-ML has thus been validated in three very different conditions: Antarctica, Barnes Ice Cap (Canada) and Canadian tundra. It has been recently used in conjunction with inverse methods to retrieve snow grain size from remote sensing data. The model is written in Fortran90 and available to the snow remote sensing community as an open-source software. A convenient user interface is provided in Python.

snowpacks↗

Opening and closing of sea ice leads - Digital measurements from synthetic aperture radar

An algorithm that uses two sequential SAR digital images to measure the opening and closing of sea ice leads is introduced. The methods used to analyze the SAR images is described, including the mesh of tie points and the classification of leads and ice. The results of the anaylsis are compared with independent manual measurements, showing that the cells covering each lead are best interpreted as opening or closing in a group, rather than individually. Also, consideration is given to an automated algorithm for grouping cells, the possibility of simplifying the method, and the relationship between the opening and closing measurements and the theory of their parametric relation to mean deformation.

Fily, M.↗

Quantitative use of satellite SAR imagery of sea ice

An automatic technique to obtain ice motion based on maximizing cross-correlation and employing a strategy of nested calculations has been developed and used to obtain displacements of more than 2000 tie-points on a 2 km mesh grid. The mean displacement error is 250 m and is as low as manual data error of 150 m on rigid pieces. The method allows tie-points to be found on a regular grid in a fully automatic fashion. Full resolution data are not needed to maximize the accuracy of displacement measurements, a result which is significant for SAR images, with their large amounts of data.

Fily, M.↗

Extracting sea ice data from satellite SAR imagery

With the prospect operational satellite SAR's by the end of the decade, there is a clear need to develop automated algorithms for the extraction of geophysical data about sea ice from high resolution radar imagery. To this end, techniques were developed for distinguishing ice from open water and for resolving the details of deformation within areas 100 km square imaged by SEASAT SAR. The classification of ice and open water is based on the creation of two bands of lower resolution image data: local average brightness, and the local variance of brightness. In the space of these two variables, ice and open water are separated into two distinct clusters. The deformation is found on a 3.4 km mesh by local cross-correlations of the brightness. Comparison with manually determined deformation shows room for improvement in regions of high deformation by using smaller areas for cross-correlation. Th concentration and deformation data are used together to determine localized regions of the scene where open water is produced or lost.

Fily, M.↗