Langezijds

dr. M. Khodadadzadeh (Mahdi)

Universitair docent
ITC-SCI-TECH
Langezijds 1301
m.khodadadzadeh@utwente.nl
+31534893781
Visitekaartje

Expertises

  • Computer Science

    • Cross-Validation
    • Learning System
    • Machine Learning
    • Validation Method

  • Earth and Planetary Sciences

    • Desertification
    • Canopy (Vegetation)
    • Synthetic Aperture Radar
    • U-Net

Organisaties

Publicaties

2026

Twenty-one questions shaping the future of plant phenology research in the 21st century (2026)Functional Ecology, 40(9), 2777-2792. Templ, B., Kauffert, J., Oteros, J. A., Lehner, S., Luedeling, E., Prat, E., Van der Meersch, V., Vrieling, A., de Vries, J., Izquierdo-Verdiguier, E., García de Cortázar-Atauri, I., Duan, K., Vilhar, U., Garcia-Mozo, H., Rebaudo, F., Ye, H., Oblišar, G., Zurita-Milla, R., Khodadadzadeh, M. & Menzel, A.https://doi.org/10.1111/1365-2435.70403Benchmarking methods for identifying phenological regions (2026)Geomatica, 78(1). Article 100113. De Oto, L., Khodadadzadeh, M., Izquierdo-Verdiguier, E. & Zurita-Milla, R.https://doi.org/10.1016/j.geomat.2026.100113Replication data for "Benchmarking methods for identifying phenological regions" (2026)[Dataset Types › Dataset]. DANS Data Station Physical and Technical Sciences. De Oto, L., Khodadadzadeh, M., Izquierdo-Verdiguier, E. & Zurita-Milla, R.https://doi.org/10.17026/pt/y1zqaz

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., 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/10.3990/1.9789036563994Analysis of desertification trends in the Algerian steppe using multitemporal satellite imagery for the period 2002-2022 (2024)In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 10277-10280) (International Geoscience and Remote Sensing Symposium (IGARSS)). IEEE. Kaddour, M., De Oto, L., Tandjaoui, A. F., Guerid, H. & Khodadadzadeh, M.https://doi.org/10.1109/IGARSS53475.2024.10640857High 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/POJGN2

Onderzoeksprofielen

Adres

Universiteit Twente

Langezijds (gebouwnr. 19), kamer 1301
Hallenweg 8
7522 NH Enschede

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