Expertises
Earth and Planetary Sciences
- Machine Learning
- Augmentation
- Cartography
- Core
- Drill
- Mineral
Computer Science
- Cross-Validation
- Artificial Neural Network
Organisaties
Publicaties
2025
A dissimilarity-adaptive cross-validation method for evaluating geospatial machine learning predictions with clustered samples (2025)Ecological informatics, 90. Article 103287. Wang, Y., Khodadadzadeh, M. & Zurita-Milla, R.https://doi.org/10.1016/j.ecoinf.2025.103287Deep learning-based vegetation canopy height mapping with polarimetric SAR: Application of a Polarization Fusion U-Net in Gabon’s tropical forests (2025)Science of Remote Sensing, 12, 1-16. Article 100327. Bhuiyan, R., Paris, C., Wang, T., Khodadadzadeh, M. & Schlund, M.https://doi.org/10.1016/j.srs.2025.100327Mapping and monitoring spatiotemporal desertification patterns in the arid transition zone of Algeria over the period 2002–2022 (2025)International Journal of Applied Earth Observation and Geoinformation (JAG), 143. Article 104799. Tandjaoui, A. F., Kaddour, M., de Oto, L. H., Guerid, H. & Khodadadzadeh, M.https://doi.org/10.1016/j.jag.2025.104799On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction (2025)GIScience & remote sensing, 62(1). Article 2460513. Wang, Y., Khodadadzadeh, M. & Zurita-Milla, R.https://doi.org/10.1080/15481603.2025.2460513
2024
Evaluating geospatial machine learning predictions: a data-driven perspective on cross-validation (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Wang, Y.https://doi.org/10.3990/1.9789036563994High Resolution Remote Sensing Images from the Algerian steppic zone (2024)[Dataset Types › Dataset]. DANS Data Station Physical and Technical Sciences. de Oto, L. H., Khodadadzadeh, M., Tandjaoui, A. F., Kaddour, M. & Guerid, H.https://doi.org/10.17026/PT/POJGN2Remote sensing-based driving factors of desertification in the Algerian steppic zone (2024)[Dataset Types › Dataset]. DANS Data Station Physical and Technical Sciences. de Oto, L. H., Khodadadzadeh, M., Tandjaoui, A. F., Guerid, H. & Kaddour, M.https://doi.org/10.17026/PT/0DNFS0
2023
Spatial+: A new cross-validation method to evaluate geospatial machine learning models (2023)International Journal of Applied Earth Observation and Geoinformation (JAG), 121. Article 103364. Wang, Y., Khodadadzadeh, M. & Zurita-Milla, R.https://doi.org/10.1016/j.jag.2023.103364Springtime (2023)[Dataset Types › Dataset]. Zenodo. Kalverla, P., Alidoost, F., Verhoeven, S. & Khodadadzadeh, M.https://doi.org/10.5281/zenodo.7835300Spatial Plus Cross-Validation experiments datasets and codes (new) (2023)[Dataset Types › Dataset]. Zenodo. Wang, Y., Khodadadzadeh, M. & Zurita-Milla, R.https://doi.org/10.17026/dans-zwj-zauq
Onderzoeksprofielen
Vakken collegejaar 2025/2026
Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.
- 201900002 - Internship
- 202300415 - IIRS Internship
- 202500041 - Fund.Progr. for Geospatial Data Analysis
- 202500051 - Big Geodata Processing
- 202500300 - Data Science
- 202500301 - Data Science - Additional Topics
- 202500322 - Data Science for GZW / pre-masters HS
- 202500323 - Data Science for ATLAS - Topics
- 202500324 - Data Science for ATLAS - Project
Vakken collegejaar 2024/2025
Adres

Universiteit Twente
Langezijds (gebouwnr. 19), kamer 1340
Hallenweg 8
7522 NH Enschede
Universiteit Twente
Langezijds 1340
Postbus 217
7500 AE Enschede