@unpublished{ShakiFischer2014,
  author    = {Shaki, Samuel and Fischer, Martin H.},
  title     = {Removing spatial responses reveals spatial concepts even in a culture with mixed reading habits},
  series = {Frontiers in human neuroscienc},
  volume    = {8},
  journal   = {Frontiers in human neuroscienc},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {1662-5161},
  doi       = {10.3389/fnhum.2014.00966},
  pages     = {2},
  year      = {2014},
  language  = {en}
}
@misc{MorishitaLazeckyWrightetal.2020,
  author    = {Morishita, Yu and Lazecky, Milan and Wright, Tim J. and Weiss, Jonathan R. and Elliott, John R. and Hooper, Andy},
  title     = {LiCSBAS},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1078},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-47243},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-472431},
  pages     = {31},
  year      = {2020},
  abstract  = {For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.},
  language  = {en}
}
@article{MorishitaLazeckyWrightetal.2020,
  author    = {Morishita, Yu and Lazecky, Milan and Wright, Tim J. and Weiss, Jonathan R. and Elliott, John R. and Hooper, Andy},
  title     = {LiCSBAS},
  series = {Remote sensing},
  volume    = {12},
  journal   = {Remote sensing},
  number    = {3},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs12030424},
  pages     = {29},
  year      = {2020},
  abstract  = {For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (similar to km) relative displacements with an accuracy of <1 cm/epoch and similar to 2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.},
  language  = {en}
}