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  4. SenSE: Community SAR ScattEring model
 
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2026
Journal Article
Title

SenSE: Community SAR ScattEring model

Abstract
SenSE is a comprehensive community framework designed for radiative transfer (RT) modeling in the active microwave domain. It summarizes various RT models developed for synthetic aperture radar (SAR) to simulate backscatter responses from open soil and vegetated land surfaces, primarily in agricultural settings. This integration encompasses different models for scattering and emission across various surfaces, providing a cohesive operational structure.
One of the framework’s most significant advantages is its modular design, which allows for the easy substitution and analysis of different surface and canopy scattering models within a single system. This flexibility facilitates seamless model exchange, enhancing the framework’s adaptability and utility. The SenSE package currently includes several surface models such as Oh92 (Y. Oh et al., 1992), Oh04 (Yisok Oh, 2004), Dubois95 (Dubois et al., 1995), IEM
(Fung et al., 1992), and the surface component of the Water Cloud Model (WCM) (Attema & Ulaby, 1978). For canopy modeling, it supports models like SSRT (Roo et al., 2001; Ulaby & Long, 2014) and WCM (Attema & Ulaby, 1978). Additionally, the framework incorporates the dielectric mixing model by Dobson et al. (1985), available in various versions for converting soil moisture content to a dielectric constant. SenSE also includes essential utility functions, such as those for frequency-wavelength conversion and calculating Fresnel reflectivity coefficients, further enhancing its analytical capabilities. For more detailed information, users are directed to the ReadtheDocs documentation and the original sources of each model, ensuring comprehensive access to technical details and
operational guidelines.
Author(s)
Weiß, Thomas
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Löw, Alexander
Ludwig-Maximilians-Universität München
Journal
The journal of open source software : JOSS. Online journal  
Open Access
File(s)
Download (242.7 KB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.21105/joss.07612
10.24406/publica-8916
Additional link
Full text
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Bioeconomy

  • Research Line: Computer vision (CV)

  • Research Line: Machine learning (ML)

  • LTA: Monitoring and control of processes and systems

  • Computer vision

  • Application frameworks

  • Applied research

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