Fusion of Hyper Spectral and Ground Penetrating Radar Data to Estimate Soil Moisture

@article{Riese2018FusionOH,
  title={Fusion of Hyper Spectral and Ground Penetrating Radar Data to Estimate Soil Moisture},
  author={Felix M. Riese and Sina Keller},
  journal={2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
  year={2018},
  pages={1-5}
}
  • Felix M. RieseS. Keller
  • Published 14 April 2018
  • Environmental Science
  • 2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
In this contribution, we investigate the potential of hyperspectral data combined with either simulated ground penetrating radar (GPR) or simulated (sensor-like) soil-moisture data to estimate soil moisture. We propose two simulation approaches to extend a given multi-sensor dataset which contains sparse GPR data. In the first approach, simulated GPR data is generated either by an interpolation along the time axis or by a machine learning model. The second approach includes the simulation of… 
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