Atefe Choopani

Geologist/PhD student
Hydrogeology & Geohazards



Atefe Choopani is a Ph.D. student in the ArGEnCo Department at ULiège and at the same time she is employed  at the Geological Survey of Belgium (inside the RBINS), to play a role as a Research Assistant in the LASUGEO project.

She holds a Master’s degree in Radar Remote Sensing from the Dept. of CEE, Shiraz University (Iran). She has worked on some RS fields, especially InSAR. Integration of Hydrogeology with InSAR and working on natural hazards are a couple of her major interesting topics. Moreover, she has hands-on experiences of groundwater modelling and AI-based modelling.


Radar Interferometry, Hydrogeology

Research group

Research interests

  • Radar Interferometry (PSInSAR, SBAS)
  • Groundwater Modelling
  • Natural Hazards

Key publications

IF – peer-reviewed papers

Choopani, A., Declercq, P. Y., Dassargues, A., & Devleeschouwer, X. (2021, July). Land Subsidence Observed in the Merchtem Area (Flanders)–30 Years of SAR Data Associated to Groundwater Withdrawal?. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 8392-8395). IEEE.

Choopani, A., Dehghani, M. & Reza Nikoo, M., 2020. Determining hydrogeological parameters of an aquifer in Sirjan Basin using Envisat ASAR interferometry and groundwater modelling, International Journal of Remote Sensing 41:2, 655-682

Conference abstracts

Devleeschouwer X., Choopani A., Moreau A., Walraevens K., Van Camp M., Van Camp M., Gobron M., Dassargues A., Oorban P., Declercq P.Y. (2021). The LASUGEO project:monitoring LAnd SUbsidence caused by Groundwater exploitation through gEOdetic measurements. 7th International Geologica Belgica Meeting 2021, Brussels, Belgium, 15-17 September 2021, accepted, poster.

Choopani A., Declercq P.-Y., Dassargues A., Devleeschouwer X. (2021). Land subsidence observed in the Merchtem Area (Flanders) – 30 years of SAR data associated to groundwater withdrawal? International Geoscience and Remote Sensing Symposium – IGARSS 2021 Brussels, Belgium, 12-16 July 2021, accepted, oral presentation.

Declercq P.-Y., Choopani A., Dassargues A., Devleeschouwer X. (2021). Areas prone to land subsidence and their evolutions in Belgium during the last 30 years. International Geoscience and Remote Sensing Symposium – IGARSS 2021 Brussels, Belgium, 12-16 July 2021, accepted, oral presentation.

Choopani, A., Declercq, P. Y., Orban, P., Devleeschouwer, X., & Dassargues, A. (2021). “Land subsidence as revealed by PS-InSAR observations in the Antwerp area (Belgium): first steps towards the understanding and modelling.” IAH2021 48th IAH Congress ‘Inspiring Groundwater’, Brussels, Belgium.

Choopani, A., M. Dehghani, and M. R. Nikoo. 2019, “Time Series Analysis of InSAR Data to Monitor Quantitative Changes in Land Subsidence Rate.” 11th National Congress on Civil Engineering, Shiraz, Iran.

Choopani, A., M. Dehghani, M. R. Nikoo, and S. Zeinali. 2017, “Time Series Analysis of InSAR Data to Study Land Subsidence Induced by Groundwater Level in Sirjan Plain.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 42.4/W4 (2017): 265-271.


monitoring LAnd SUbsidence caused by Groundwater exploitation through gEOdetic measurements

Belspo BRAIN project: Long term time series of deformation in Antwerp area will be calculated by applying PS-InSAR algorithm on different high and mid spatial resolution radar data. Furthermore, the consolidation of the saturated geological layers during the corresponded temporal period will be simulated in a 1-D geomechanical model. Moreover, long-term time series of gravimetric data will be compared also to the time evolution of the deformations. All simulated results and observed measurements will be compared. In the last step, GPS/GNSS campaign measurements, at the position of artificial Corner Reflectors (CR) installed in various sites over each ROI will allow me to calibrate Sentinel-1A PS-InSAR results during at least three future years and will ensure that the detected land surface deformations are in a good agreement with measured observations.