GSV-SRTS: a heterogeneous landscape soil-canopy reflectance model over sloping terrain with an extended GSV and stochastic radiative transfer theory

Li, Siqi; Hu, Guyue; Li, Shaoda; Yang, Ronghao; Tan, Junxiang; Liu, Chenghao; Bian, Jinhu

doi:10.5194/gmd-19-3531-2026

Articles | Volume 19, issue 8

https://doi.org/10.5194/gmd-19-3531-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-3531-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 8

Model description paper

|

30 Apr 2026

Model description paper |

| 30 Apr 2026

GSV-SRTS: a heterogeneous landscape soil-canopy reflectance model over sloping terrain with an extended GSV and stochastic radiative transfer theory

Siqi Li, Guyue Hu, Shaoda Li, Ronghao Yang, Junxiang Tan, Chenghao Liu, and Jinhu Bian

Data sets

Soil datasets Siqi Li https://doi.org/10.6084/m9.figshare.30392938

Model code and software

GSV-SRTS model Siqi Li https://doi.org/10.6084/m9.figshare.30392938

Short summary

The GSV-SRTS (General spectral vector-stochastic radiative transfer model for sloping terrain) simulates radiative transfer for heterogeneous mountain forests, addressing slope-induced uncertainties in remote sensing. Validations with benchmark models and satellite data confirm its accuracy in red/NIR bands and its capability to capture canopy-terrain effects, offering a reliable tool for improved biophysical retrieval.