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RELEASED in 2018

SCobi simulator

open sourced

fully polarimetric

modular

supplies phase information

Available at GitHub

SCoBi Source Code

There is no installation requirement for the current version. In other words, it can be directly run from within the source code when it is downloaded.

The source folder contains both the input and lib folders. The lib folder contains the code needed to run the SCoBi simulator, and the input folder includes the system, configuration, Rx_antenna_pattern, and vegetation folders. Each of these folders within the input folder includes some number of default input files with the distribution.

Help SCoBi Improve : Please send us an email via the following address to make requests or to report any bugs through using the software: impress@uga.edu

The SCoBi software can be accessed from the following GitHub repository

SCoBi Tutorials.

Publications

Scobi Publications

Mehmet Kurum, Manohar Deshpande, Alicia T Joseph, Peggy E O’Neill, Roger H Lang, Orhan Eroglu: SCoBi-Veg: A generalized bistatic scattering model of reflectometry from vegetation for signals of opportunity applications. In: IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 2, pp. 1049–1068, 2018.
Orhan Eroglu, Mehmet Kurum, John Ball: Response of GNSS-R on dynamic vegetated terrain conditions. In: IEEE journal of selected topics in applied earth observations and remote sensing, vol. 12, no. 5, pp. 1599–1611, 2019.
Orhan Eroglu, Dylan R Boyd, Mehmet Kurum: The signals of opportunity coherent bistatic scattering simulator: A free open source framework [software and data sets]. In: IEEE Geoscience and Remote Sensing Magazine, vol. 8, no. 3, pp. 63–75, 2020.
Dylan Boyd, Mehmet Kurum, Orhan Eroglu, Ali Cafer Gurbuz, James L Garrison, Benjamin R Nold, Manuel A Vega, Jeffrey R Piepmeier, Rajat Bindlish: SCoBi Multilayer: a signals of opportunity reflectometry model for multilayer dielectric reflections. In: Remote Sensing, vol. 12, no. 21, pp. 3480, 2020.
Dylan Ray Boyd, Ali Cafer Gurbuz, Mehmet Kurum, James L Garrison, Benjamin R Nold, Jeffrey R Piepmeier, Manuel Vega, Rajat Bindlish: Cramer–rao lower bound for soop-r-based root-zone soil moisture remote sensing. In: IEEE journal of selected topics in applied earth observations and remote sensing, vol. 13, pp. 6101–6114, 2020.
D. R. Boyd, M. Kurum: A Nested Facet Method of the Kirchhoff Approximation for Large-Scale Land Scattering. In: IEEE Transaction on Geosciences and Remote Sensing, vol. 62, no. 2002915, 2024.