3D Remote Sensing  

CloudCT is a space mission, directly derived from my Ph.D. research, to launch 10 pico-satellites that will orbit in a formation and gather multi-view observations of the atmosphere. CloudCT, lead by Yoav Schechner, Ilan Koren and Klaus Schilling has won ERC Synergy funding of 14 Million Euro.​ For more information see the ClouCT page linked above and a mission concept clip below.


This mission is a joint collaboration with Weizmann Institute, Israel, and Zentrum für Telematik, Germany.

Research description

Recent advances in multi-view high-resolution instruments and computation power enable, in principle, 3D volumetric recovery of clouds. This is in contrast to current retrievals, which rely heavily on plane-parallel models and 1D radiative transfer. Plane-parallel models do not express the true 3D nature of the atmosphere, thus biasing retrievals. We pose and solve an inverse problem of passive atmospheric scatterer 3D tomography. The approach fits a microphysical 3D volumetric model of scatterers to multi-angular/multi-spectral images. The forward model is a numerical 3D radiative transfer solver. Model to data fit is posed as a high-dimensional optimization problem. The optimization is computationally tractable on large scales, thanks to an efficient algorithm we developed.


This is joint work with the Jet Propulsion Laboratory (NASA-Caltech), California, USA.


Pyshdom performs 3D reconstruction of cloud microphysical properties from multi-angle, multi-spectral solar reflected radiation using a non-linear optimization procedure [2,4]. The core radiative transfer routines are sourced from the Fortran SHDOM (Spherical Harmonic Discrete Ordinate Method for 3D Atmospheric Radiative Transfer) code by Frank K. Evans. The python package was created by Aviad Levis, Amit Aides, and Jesse Loveridge. See the GitHub page for installation and case examples.



  1. Aviad Levis, Yoav Y. Schechner, Anthony B. Davis, Jesse Loveridge, "Multi-View Polarimetric Scattering Cloud Tomography and Retrieval of Droplet Size", Remote Sens. 2020.

  2. Tamar Loeub, Aviad Levis, Vadim Holodovsky, and Yoav Schechner, "Monotonicity Prior for Cloud Tomography", ECCV, 2020.

  3. Amit Aides, Avid Levis, Vadim Holodovsky, Yoav Schechner, Dietrich Althausen, and Adi Vainiger, "Distributed Sky Imaging Radiometry and Tomography", Proc. IEEE ICCP, 2020.

  4. Felipe A. Mejia, Ben Kurtz, Aviad Levis, Íñigo de la Parra, Jan Kleissl, "Cloud tomography applied to sky images: A virtual testbed", Solar Energy, 2018.

  5. Aviad Levis, Yoav Y. Schechner, Anthony B. Davis, Multiple-Scattering Microphysics Tomography, Proc. IEEE CVPR, 2017.

  6. Vadim Holodovsky, Yoav Y. Schechner, Anat Levin, Aviad Levis, Amit Aides, “In-Situ Multi-View Multi-Scattering Stochastic Tomography, Proc. IEEE ICCP, 2016.

  7. Aviad Levis, Yoav Y. Schechner, Amit Aides, Anthony B. Davis, Airborne three-dimensional cloud tomography”, Proc. IEEE ICCV, 2015.

  8. Danny Veikherman, Amit Aides, Yoav Y. Schechner and Aviad Levis,Clouds in The Cloud”, Proc. ACCV, 2014.

© 2017 Aviad Levis