ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 471–476, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-471-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 471–476, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-471-2022
 
17 May 2022
17 May 2022

HYPERBLEND: SIMULATING SPECTRAL REFLECTANCE AND TRANSMITTANCE OF LEAF TISSUE WITH BLENDER

K. A. Riihiaho, T. Rossi, and I. Pölönen K. A. Riihiaho et al.
  • Faculty of Information Technology, University of Jyväskylä, 40100, Jyväskylä, Finland

Keywords: leaf optical properties model, simulation, ray tracing, hyperspectral imaging, remote sensing, open source

Abstract. Remotely sensing vegetation condition and health hazards requires modeling the connection of plants’ biophysical and biochemical parameters to their spectral response. Even though many models exist already, the field suffers from lack of access to program code. In this study, we will assess the feasibility of open-source 3D-modeling and rendering software Blender in simulating hyperspectral reflectance and transmittance of leaf tissue to serve as a base for a more advanced large-scale simulator. This is the first phase of a larger HyperBlend project, which will provide a fully open-source, canopy scale leaf optical properties model for simulating remotely sensed hyperspectral images. Test results of the current HyperBlend model show good agreement with real-world measurements with root mean squared error around 1‰. The program code is available at https://github.com/silmae/ hyperblend.