Recent Publications

Tusa, L., Andreani, L., Khodadadzadeh, M., Contreras, C., Ivascanu, P., Gloaguen, R. and Gutzmer, J., 2019. Mineral Mapping and Vein Detection in Hyperspectral Drill-Core Scans: Application to Porphyry-Type Mineralization.

Rafiezadeh Shahi, K., Khodadadzadeh, M., Tusa, L., Ghamisi, P., Tolosana-Delgado, R. and Gloaguen, R., 2020. Hierarchical Sparse Subspace Clustering (HESSC): An Automatic Approach for Hyperspectral Image Analysis.

Rafiezadeh Shahi, K., Ghamisi, P., Rasti, B., Jackisch, R., Scheunders, P. and Gloaguen, R., 2020. Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm.

Rasti, B., Chang, Y., Dalsasso, E., Denis, L. and Ghamisi, P., 2021. Image Restoration for Remote Sensing: Overview and toolbox.

Booysen, R., Zimmermann, R., Lorenz, S., Gloaguen, R., Nex, P., Andreani, L. and Möckel, R., 2019. Towards Multiscale and Multisource Remote Sensing Mineral Exploration Using RPAS: A Case study in the Lofdal Carbonatite-Hosted REE Deposit, Namibia.

Kerna, M., Tusa, L., -Leißner, T., Gerald van den Boogaart, K. and Gutzmera, J., 2019. Optimal sensor selection for sensor-based sorting based on automated mineralogy data.

Flores, H., Lorenz, S., Jackisch, R., Tusa, L., Contreras, I., Zimmermann, R. and Gloaguen, R., 2021. UAS-Based Hyperspectral Environmental Monitoring of Acid Mine Drainage Affected Waters.

Liesenberg, V. and Gloaguen, R., 2012. Evaluating SAR polarization modes at L-band for forest classification purposes in Eastern Amazon, Brazil.

Sheykhmousa, M., Mahdianpari, M., Ghanbari, H., Mohammadimanesh, F., Ghamisi, P. and Homayouni, S., 2020. Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review.

Attarchi, S. and Gloaguen, R., 2014. Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran).

Barbosa, N., Andreani, L., Gloaguen, R. and Ratschbacher, L., 2021. Window-Based Morphometric Indices as Predictive Variables for Landslide Susceptibility Models.

Jakob, S., Zimmermann, R. and Gloaguen, R., 2017. The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data.