Publications

Supervised Learning for Positional Accuracy Improvement of Historical Maps: A Systematic Comparison and Validation

K Vantas, V Mirkopoulou

Transactions in GIS 29(4): e70076, 2025

• DOI

Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition

K Vantas, V Mirkopoulou

Geomatics 5(2): 16, 2025

• DOI
• Source

Extreme Rainfall Analysis Including Seasonality in Athens, Greece

K Vantas, A Loukas

Environmental and Earth Sciences Proceedings 32(1): 1, 2025 (8th International Electronic Conference on Water Sciences, ECWS-8)

• DOI
• Source

Adaptation of the Engelund-Hansen formula to Nestos River, Greece

K Vantas, K Kaffas, E Sidiropoulos, V Hrissanthou

7th IAHR Europe Congress 1: 74–75, 2022

• PDF
• Source

Improving the positional accuracy of cadastral maps via Machine Learning methods

K Vantas

MSc thesis, School of Law, Aristotle University of Thessaloniki, Greece

• DOI

Soil erosion modelling: A bibliometric analysis

N Bezak, P Borrelli, K Vantas, et al.

Environmental Research 197: 111087, 2021

• PDF
• DOI
• Source

Knowledge discovery using clustering analysis of rainfall timeseries

K Vantas, E Sidiropoulos

EGU General Assembly 2021, EGU21-14758

• PDF
• DOI
• Source
• Slides

Intra-storm pattern recognition through fuzzy clustering

K Vantas, E Sidiropoulos

Hydrology 8(2): 57, 2021

• PDF
• DOI
• Source

Extending the Applicability of the Meyer–Peter and Müller Bed Load Transport Formula

E Sidiropoulos, K Vantas, V Hrissanthou, T Papalaskaris

Water 13(20): 2817, 2021

• PDF
• DOI
• Source

Soil erosion modelling: A global review and statistical analysis

P Borrelli, C Alewell, K Vantas, et al.

Science of The Total Environment 780: 146494, 2021

• PDF
• DOI
• Source

Estimating rainfall erosivity from daily precipitation using generalized additive models

K Vantas, E Sidiropoulos, C Evangelides

Environmental Sciences Proceedings 2(1): 21, 2020 (4th EWaS International Conference)

• PDF
• DOI
• Source
• The 4th EWaS International Conference

Estimating current and future rainfall erosivity in Greece using regional climate models and spatial quantile regression forests

K Vantas, E Sidiropoulos, A Loukas

Water 12(3): 687, 2020

• PDF
• DOI
• Source

A global bibliometric perspective on soil erosion modelling

N Bezak, P Borrelli, K Vantas, et al.

EGU General Assembly 2020, EGU2020-2919

• PDF
• DOI
• Source

Optimal temporal distribution curves for the classification of heavy precipitation using hierarchical clustering on principal components

K Vantas, E Sidiropoulos, M Vafeiadis

Global NEST Journal 21(4): 530–538, 2019

• PDF
• DOI
• Source

Rainfall Erosivity and Its Estimation: Conventional and Machine Learning Methods

K Vantas, E Sidiropoulos, C Evangelides

In Soil Erosion – Rainfall Erosivity and Risk Assessment, IntechOpen, 2019

• PDF
• DOI

Robustness Spatiotemporal Clustering and Trend Detection of Rainfall Erosivity Density in Greece

K Vantas, E Sidiropoulos, A Loukas

Water 11(5): 1050, 2019

• PDF
• DOI
• Source

A data driven approach for the temporal classification of heavy rainfall using Self-Organizing Maps

K Vantas, E Sidiropoulos, C Evangelides

EGU General Assembly 2019, EGU2019-10680

• PDF
• Source
• Poster
• EGU 2019

Spatial groundwater resource allocation by means of extremal optimization, combined with a cellular automata component

E Sidiropoulos, K Vantas, C Evangelides

EGU General Assembly 2019, EGU2019-10923

• PDF
• Source

Temporal and elevation trend detection of rainfall erosivity density in Greece

K Vantas, E Sidiropoulos, A Loukas

3rd International Electronic Conference on Water Sciences (ECWS-3), 2018

• PDF
• DOI
• Source
• 3rd International Electronic Conference on Water Sciences

hyetor: R package to analyze fixed interval precipitation time series

K Vantas

Zenodo, version 0.0.0.9001

• DOI
• Source
• Code

hydroscoper: R interface to the Greek National Data Bank for Hydrological and Meteorological Information

K Vantas

Journal of Open Source Software 3(23): 625, 2018

• PDF
• DOI

Rainfall temporal distribution in Thrace by means of an unsupervised machine learning method

K Vantas, E Sidiropoulos, M Vafeiadis

Protection and Restoration of the Environment XIV, 555–564, 2018

• PDF
• Source
• Protection and Restoration of the Environment

Determination of rainfall erosivity in the framework of data science using machine learning and geostatistics methods

K Vantas

PhD thesis, Aristotle University of Thessaloniki, Greece

• DOI
• Source

Imputation of erosivity values under incomplete rainfall data by machine learning methods

K Vantas, E Sidiropoulos

European Water 57: 193–199, 2017

• PDF
• Source

Modeling distribution system water quality with HYDROSIM model

S Yannopoulos, K Vantas, C. Tzimopoulos, C. Evaggelidis

EWRA Seventh International Conference, 487–494, 2009

• PDF
• Source

Modeling water quality in distribution networks

K Vantas

MSc thesis, Aristotle University of Thessaloniki, Greece