Interactions des ondes radar avec la végétation L’interaction des micro-ondes avec la végétation donne lieu à des processus extrèmement variés à la surface du globe,…

Rugosité de surface

Qu’est-ce qu’une surface rugueuse ? La rugosité du sol est l’un des facteurs importants qui influencent la rétrodiffusion radar. La rugosité est une propriété commune…


Effects of imaging geometry Now you know that a radar system is looking to the side, away from the nadir line below the sensor. This…


Interacciones de las microondas con la vegetación La relación entre los diferentes tipos de vegetación y los procesos de scattering resultantes son complejos y bastante…

Resumen parámetros geométricos

¿Qué parámetros influyen en la retrodispersión del radar? La superficie de la Tierra es un objetivo complejo. Múltiples parámetros juegan un papel significativo en la…

Rugosidad de la superficie

Midiendo un mundo rugoso… La rugosidad de la superficie es un parámetro importante que influye en nuestra señal de backscattering radar. Las superficies naturales pueden…

Overview of geometrical parameters

Which parameters influence the radar backscatter? The Earth’s surface is a complex target. Multiple parameters play a significant role in the strength of the radar…

Surface Roughness

Sensing a rough world … The surface roughness is a major parameter influencing our radar backscatter signal. Natural surfaces can generally be considered to be…


  • Bourgeau-Chavez, L.L., Lee, Y.M., Battaglia, M., Endres, S.L., Laubach, Z.M. & Scarbrough, K. (2016): Identification of
    Woodland Vernal Pools with Seasonal Change PALSAR Data for Habitat Conservation. In: Remote Sensing, 8, 490.
  • Clinuvel (2019):Understanding the Electromagnetic Spectrum. <https://www.clinuvel.com>.
  • Centre for Remote Imaging, Sensing & Processing (CRISP, 2001): SAR Imaging – Frequency, Polarisation and Incident Angle. Microwave Frequency. <https://crisp.nus.edu.sg/~research/tutorial/freqpol.htm>.
  • Edmund Optics Inc. (2019): Introduction to Polarization.
  • Esch, S. (2018): Determination of Soil Moisture and Vegetation Parameters from Spaceborne C-Band SAR on Agricultural
    Areas. Dissertation. University of Cologne.
  • European Space Agency (ESA, 2013): Satellite frequency bands. <https://www.esa.int/Applications/Telecommunications_Integrated_Applications/Satellite_frequency_bands>
  • European Space Agency (ESA, 2014): Special Features of ASAR.
  • European Space Agency (ESA, 2019): Radar Course 2. <https://earth.esa.int/..,>.
  • European Space Agency (ESA, 2019): Radar Course 3. <https://earth.esa.int/..,>.
  • Evans, T. (2013): Habitat Mapping of the Brazilian Pantanal using Synthetic Aperture Radar Imagery and Object Based
    Image Analysis. <Evans Master Thesis>.
  • Flores-Anderson, A.I., Herndon, K.E., Thapa, R.B. & Cherrington, E. (2018): The Synthetic Aperture Radar (SAR)
    Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation.
  • Gaber, A., Soliman, F., Koch, M. & El.Baz, F. (2015): Using full-polarimetric SAR data to characterize the surface
    sediments in desert areas: A case study in El-Gallaba Plain, Egypt. In: Remote Sensing of Environment, 162, 11-28.
  • Jagdhuber, T. (2012): Soil parameter retrieval under vegetation cover using SAR polarimetry. Ph.D. dissertation, Univ.
    Potsdam, Germany [Online]. Available: http//: opus.kobv.de.
  • Jack, H. (2013). Manufacturing Processes. Surfaces. <http://engineeronadisk.com/V3/engineeronadisk-67.html>.
  • Jet Propulsion Laboratory (JPL, 2019): Polarimetry. <https://nisar.jpl.nasa.gov/technology/polsar/>.
  • Le Toan, T. (2007): Introduction to SAR Remote Sensing. Advanced Training Course on Land Remote Sensing. <https://earth.esa.int/landtraining07/D1LA1-LeToan.pdf>.
  • Meng, H., Wang, X., Chong, J., Wei, X. & Kong, W. (2017): Doppler Spectrum-Based NRCS Estimation Method for Low
    Scattering Areas in Ocean SAR Images. In: Remote Sensing, 9, 219.
  • Moreira, A., Prats-Iraola, P., Younis, M., Krieger, G., Hajnsek, I. & Papathanassiou, K. P. (2013): A Tutorial on Synthetic
    Aperture Radar. In: IEEE Geoscience and Remote Sensing.
  • Nave, R. (2005): HyperPhysics. The Rayleigh Criterion.
  • National Aeronautics and Space Administration, Science Mission Directorate (NASA, 2010): Introduction to the Electromagnetic Spectrum. Retrieved [10.03.2020], from NASA Science website: http://science.nasa.gov/ems/01_intro
  • Pohl, C., Tempfli, K., & Huurneman, G.C. (2004): Active Sensors. In: Kerle, N., Janssen, L.L.F. & Huurneman, G.C. (Editors): Principles of Remote Sensing. An introductory textbook. ITC Educational Textbook Series, 95-120.
  • Richards, J.A. (2009): Remote Sensing with Imaging Radar.  <https://www.springer.com/de/book/9783642020193>.
  • Schumann, G.J.-P. & Moller, D.K. (2015): Microwave remote sensing of flood inundation. In: Physics and Chemistry of
    the Earth
    , 83, 84-95.
  • Small, D. (2011): Flattening Gamma: Radiometric Terrain Correction for SAR Imagery. In: IEEE Transactions on
    Geoscience and Remote Sensing
    , 49, 3081-3093.
  • Utah State University (2019): Orchard irrigation. <https://www.intermountainfruit.org/orchard-irrigation/swc>.
  • Woodhouse, I. H. (2006): Introduction to microwave remote sensing. Taylor & Francis, New York.