Author

C. Kontoes

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Open access Sep 2026

A Machine Learning Framework for Flood Risk Assessment With Imbalanced Data

This study presents a machine‐learning framework for identifying areas of elevated flood risk using imbalanced, high‐dimensional geospatial datasets. Using the Mandra River Basin in Greece as a case study, an extreme gradient boosting (XGBoost) classifier was trained on 11 flood‐related features including hydrologica...

A. Tsouni, C. Panagiotou, Charalampos Konstantinou et al. · Journal of Flood Risk Manage... · 0 citations

Jul 2026

Space2Ground 2.0: A Multi-Source Dataset and Framework for Agricultural Monitoring through Fusion of Street-Level and Satellite Imagery

Accurate and scalable parcel-level agricultural monitoring remains challenging because satellite Earth Observation alone provides only an overhead perspective of agricultural parcels, while optical observations are further affected by cloud-induced temporal gaps. This paper presents Space2Ground 2.0, a multi-source fra...

Iason Tsardanidis, Alkiviadis Koukos, George Choumos et al. · arXiv.org · 0 citations

Open access Sep 2026

An Explainable Machine Learning Framework for Predicting West Nile Virus and Uncovering Key Transmission Drivers

Abstract This study introduces Disease Vector Intelligence (DVI), an explainable Machine Learning (ML) framework developed within the EYWA (EarlY WArning system for mosquito‐borne diseases) ecosystem. DVI integrates big Earth Observation (EO), socioeconomic, and estimated mosquito abundance data to predict the presence...

Dimitrios Sainidis, Konstantinos Tsaprailis, Charalampos Kontoes · GeoHealth · 0 citations