H.R.F.I -'Basic Research Project
''GEONE''  Advanced geostatistical modelling for natural resources evaluation
 

The project's primary objective is to develop novel tools for the modeling of natural resources data by exploring modern covariance functions employing Euclidean and non-Euclidean spaces.

Technical University of Crete - Environmental Mining and Sustainable Development Research Unit

Contact Details                                                                                             

School of Mineral Resources Engineering

Technical University of Crete

Assistant Professor: Emmanouil Varouchakis

Tel: 00302821037642

Email: evarouchakis@tuc.gr

www.envi-stat.tuc.gr/en/home


News

14/11/2024 Final meeting 

10/11-12/11/2025 MedGU2025, Athens Greece

09/10-14/10/2025 IAMG 2025, Zhuhai, China

22/9-24/9/2025  GEONE in INCORCP 2025, Chania, Greece

28/05/2025 PhD Workshop - Geostatistics for Resources Estimation

27-28/05/2025 2nd progress meeting meeting

28/4-3/5/2025  GEONE in  EGU 2025 b Vienna, Greece

18/11-22/11/2024 PhD Workshop - Modern Geostatistics for Groundwater Bodies Characterization

15/11/2024 1st annual meeting 

02-06/09/2024 GEOSTAT2024, Azores Portugal

09-11/10/2024  GEONE in Sustain Istanbul 2024 Istanbul,Turkiye

19-21/6/2024  GEONE in  geoENV2024, Chania, Greece

14-19/4/2024  GEONE in  EGU 2024, Vienna, Greece

15/05/2024 1st progress meeting meeting

11/01/2024 Kick Off Meeting of GEONE Research Program

08/01/2024 Welcome to GEONE Website

 

Project Objectives

  • Gaussian anamorphosis of asymmetrically distributed natural resources data

  • Investigation of Euclidean and non-Euclidean distance metrics

  • Exploration of novel covariance functions

  • Investigation of modelling uni-multi-variate natural resources data

  • Case study applications

 

Publications

• Pavlides, M. D. Koltsidopoulou, M. Chrysanthi, E. A. Varouchakis. “A Kernel-Based Nonparametric Approach for Data Gaussian Anamorphosis” , Mathematical Geosciences (in press).

• M. K. Germanou, A. Pavlides, E A. Varouchakis. “Comparison of Geostatistical and Machine Learning Methods for Spatial Analysis of Natural Resources Data”, Mathematical Geosciences, DOI: 10.1007/s11004-025-10239-9

• M. Chrysanthi, A. Pavlides, E. A. Varouchakis. “A Bayesian Geostatistical Approach to Analyzing Groundwater Depth in Mining Areas”, Geosciences, 2025, 15(11), 410; https://doi.org/10.3390/geosciences15110410

• E.A. Varouchakis, M. D. Koltsidopoulou and A. Pavlides, 2025, “Designing Robust Covariance Models for Geostatistical Applications”, Stochastic Environmental Research and Risk Assessment, https://doi.org/10.1007/s00477-025-02982-6



Team Members

Technical University of Crete (BENEFICIARY)

Assistant Professor Emmanouil Varouchakis, PhD, School of Mineral Resources Engineering

Professor Dionissios Christopulos, PhD, School of Electrical and Electronic Engineering

Dr. Andreas Pavlidis, Mineral Resources Engineer, Postdoc Researcher, Geostatistics

Maria Koltsidopoulou, Electrical and Electronic Engineer, PhD candidate

Dr. Katerina Spanoudaki, Chemical Engineer

Antonis Lyronis, Electrical and Electronic Engineer, MSc

Maria Chrysanthi, Mineral Resources Engineer, MSc candidate

Maria Germanou, Electrical and Electronic Engineer (Student)

 

COLLABORATING ORGANISATIONS (NON-BENEFICIARIES)

Nazarbayev University,  School of Mining and Geosciences

CERENA/DER, Pavilhão deMinas, Instituto Superior Técnico

Universidad Católica del Norte Chile, Department of Metallurgical and Mining Engineering

Politecnico di Milano  Department of Civil and Environmental Engineering, MIPORE 

 


Funding

The research project is implemented in the framework of H.F.R.I call “Basic research Financing (Horizontal support of all Sciences)” under the National Recovery and Resilience Plan “Greece 2.0” funded by the European Union – NextGenerationEU (H.F.R.I. Project Number: 16537).