B.Eng., M.Eng. (University of Tehran), PhD (Memorial University)

• Cross-appointed Professor

Contact Information

Ph: (709) 864-9791
Em: m.mahdianpari@mun.ca
Office: CF-3024

Expertise

• Machine Learning
• Remote Sensing

Research Interests

• PolSAR data processing, multi-sensor data fusion, satellite image classification, geo big data and deep learning.
• Application of remote sensing in wetland mapping, water quality monitoring, forest and agriculture.

Personal Profile

Masoud Mahdianpari is currently a Remote Sensing Technical Lead with C-CORE and a cross-appointed professor with the Department of Electrical and Computer Engineering, Memorial University of Newfoundland.

ResearchGate

Honours/Awards/Accreditation

1. T. David Collett Best Industry Paper award organized by IEEE NECEC conference for Big Data for Big Country presentation, local award, Organized by IEEE NECEC 2020.
2. The best cover paper award for Mid-season Crop Classification Using Dual-, Compact-, and Full-Polarization SAR data in Preparation for the RADARSAT Constellation Mission (RCM), international award, organized by Remote Sensing journal, 2020.
3. ESRI 2020 Map award for “Big Data for Big Country Map”, international award, organized by ESRI Canada, 2020.
4. PhD Exam: "Pass with Distinction", local award, Memorial University of Newfoundland, 2019.
5. Microsoft Artificial Intelligence for Earth grant (AI4Earth), international award, organized by Microsoft, 2018-2019.
6. Graduate Academic Excellence Award presented by Memorial University of Newfoundland, local award, 2018.
7. The ComAdv Devices Inc. Scholarship for Innovation, Creativity and Entrepreneurship, local award, organized by Memorial University of Newfoundland, 2018.
8. Outstanding reviewer award by Elsevier for contribution to the highly prestigious Remote Sensing of Environment Journal, international award, 2018.
9. RDC Ocean Industries Student Research Award, Newfoundland and Labrador, Canada, 2016-2019.
10. Teacher Assistance (TA) Award, local award, Memorial University of Newfoundland, 2017.
11. PhD Comprehensive Examination: "Pass with Distinction", local award, Memorial University of Newfoundland, 2017.
12. IEEE Student Travel Scholarship, International Geo-science and Remote Sensing Society (IGARSS), International, Texas, USA, international award, 2017.
13. T. David Collett Best Industry Paper award organized by IEEE, local award, 2016.
14. Student award, Canadian Institute of Geomatics - NL Graduate Award, provincial award, 2016.
15. IEEE Student Travel Scholarship, International Geo-science and Remote Sensing Society (IGARSS), International, Munich, Germany, international award, 2012.
16. The best student of year award, University of Tehran, local award, 2010-2013.

Research Highlights

Peer-reviewed journals:

1. Mahdianpari, M., Granger, J.E., Mohammadimanesh, F., Warren, S., Puestow, T., Salehi, B. and Brisco, B., 2020. Smart solutions for smart cities: Urban wetland mapping using very-high resolution satellite imagery and airborne LiDAR data in the City of St. John's, NL, Canada. Journal of Environmental Management, p.111676.
2. Mahdianpari, M., Jafarzadeh, H., Granger, J.E., Mohammadimanesh, F., Brisco, B., Salehi, B., Homayouni, S. and Weng, Q., 2020. A large-scale change monitoring of wetlands using time series Landsat imagery on Google Earth Engine: a case study in Newfoundland. GIScience & Remote Sensing, 57(8), pp.1102-1124.
3. Taghizadeh-Mehrjardi, R., Mahdianpari, M., Mohammadimanesh, F., Behrens, T., Toomanian, N., Scholten, T. and Schmidt, K., 2020. Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran. Geoderma, 376, p.114552.
4. Sheykhmousa, M., Mahdianpari, M., Ghanbari, H., Mohammadimanesh, F., Ghamisi, P. and Homayouni, S., 2020. Support Vector Machine vs. Random Forest for Remote Sensing Image Classification: A Meta-analysis and systematic review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
5. Mahdianpari, M., Brisco, B., Granger, J.E., Mohammadimanesh, F., Salehi, B., Banks, S., Homayouni, S., Bourgeau-Chavez, L. and Weng, Q., 2020. The Second Generation Canadian Wetland Inventory Map at 10 Meters Resolution Using Google Earth Engine. Canadian Journal of Remote Sensing, 46(3), pp.360-375.
6. Eskandari, R., Mahdianpari, M., Mohammadimanesh, F., Salehi, B., Brisco, B. and Homayouni, S., 2020. Meta-analysis of Unmanned Aerial Vehicle (UAV) Imagery for Agro-environmental Monitoring Using Machine Learning and Statistical Models. Remote Sensing, 12(21), p.3511.
7. Brisco, B., Mahdianpari, M., and Mohammadimanesh, F., 2020. Hybrid Compact Polarimetric SAR for Environmental Monitoring with the RADARSAT Constellation Mission. Remote Sensing, 12(20), p.3283.
8. Adeli, S., Salehi, B., Mahdianpari, M., Quackenbush, L.J., Brisco, B., Tamiminia, H. and Shaw, S., 2020. Wetland monitoring using SAR data: A meta-analysis and comprehensive review. Remote Sensing, 12(14), p.2190.
9. Mahdianpari, M., Granger, J.E., Mohammadimanesh, F., Salehi, B., Brisco, B., Homayouni, S., Gill, E., Huberty, B. and Lang, M., 2020. Meta-Analysis of Wetland Classification Using Remote Sensing: A Systematic Review of a 40-Year Trend in North America. Remote Sensing, 12(11), p.1882.
10. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., Brisco, B., Homayouni, S., Gill, E., DeLancey, E.R. and Bourgeau-Chavez, L., 2020. Big Data for a Big Country: The First Generation of Canadian Wetland Inventory Map at a Spatial Resolution of 10-m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform. Canadian Journal of Remote Sensing, pp.1-19.
11. Tamiminia, H., Salehi, B., Mahdianpari, M., Quackenbush, L., Adeli, S. and Brisco, B., 2020. Google Earth Engine for geo-big data applications: A meta-analysis and systematic review. ISPRS Journal of Photogrammetry and Remote Sensing, 164, pp.152-170.
12. DeLancey, E.R., Simms, J.F., Mahdianpari, M., Brisco, B., Mahoney, C. and Kariyeva, J., 2020. Comparing Deep Learning and Shallow Learning for Large-Scale Wetland Classification in Alberta, Canada. Remote Sensing, 12(1), p.2.
13. Mahdianpari, M., Mohammadimanesh, F., McNairn, H., Davidson, A., Rezaee, M., Salehi, B. and Homayouni, S., 2019. Mid-season Crop Classification Using Dual-, Compact-, and Full-Polarization in Preparation for the Radarsat Constellation Mission (RCM). Remote Sensing, 11(13), p.1582.
14. Mahdianpari, M., Salehi, M., Mohammadimanesh, F., Homayouni, Saeid, 2019. The First Wetland Inventory Map of Newfoundland at a Spatial Resolution of 10 m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform. Remote Sensing, 11(1), p.43.
15. Mohammadimanesh, F., Salehi, B., Mahdianpari, M., Gill, E. and Molinier, M., 2019. A new fully convolutional neural network for semantic segmentation of polarimetric SAR imagery in complex land cover ecosystem. ISPRS Journal of Photogrammetry and Remote Sensing, 151, pp.223-236.
16. Mohammadimanesh, F.; Salehi, B.; Mahdianpari, M.; Brisco, B.; Gill, E. Full and Simulated Compact Polarimetry SAR Responses to Canadian Wetlands: Separability Analysis and Classification. Remote Sens.2019, 11, 516.
17. Mahdianpari, M., Motagh, M., Akbari, V., Mohammadimanesh, F. and Salehi, B., 2019. A Gaussian Random Field Model for De-speckling of Multi-polarized Synthetic Aperture Radar Data. Advances in Space Research.
18. Mahdianpari, M., Salehi, B., Rezaee, M., Mohammadimanesh, F., and Zhang, Y., 2018. Very deep convolutional neural networks for complex land cover mapping using multispectral remote sensing imagery. Remote Sensing, 10(7), p.1119.
19. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., Brisco, B., Mahdavi, S., Amani, M. and Granger, J.E., 2018. Fisher Linear Discriminant Analysis of coherency matrix for wetland classification using PolSAR imagery. Remote Sensing of Environment, 206, pp.300-317.
20. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., Larsen, G. and Peddle, D.R., 2018. Mapping land-based oil spills using high spatial resolution unmanned aerial vehicle imagery and electromagnetic induction survey data. Journal of Applied Remote Sensing, 12(3), p.036015.
21. Rezayee, M., Mahdianpari, M., Zhang, Y., Salehi, 2018, Deep Convolutional Neural Network for Complex Wetland Classification Using Optical Remote Sensing Imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS.2018.2846178.
22. Mohammadimanesh, F., Salehi, B., Mahdianpari, M., Motagh, M. and Brisco, B., 2018. An efficient feature optimization for wetland mapping by synergistic use of SAR intensity, interferometry, and polarimetry data. International Journal of Applied Earth Observation and Geoinformation, 73, pp.450-462.
23. Mohammadimanesh, F., Salehi, B., Mahdianpari, M., English, J., Chamberland, J. and Alasset, P.J., 2018. Monitoring surface changes in discontinuous permafrost terrain using small baseline SAR interferometry, object-based classification, and geological features: a case study from Mayo, Yukon Territory, Canada. GIScience & Remote Sensing, pp.1-26.
24. Mohammadimanesh, F., Salehi, B., Mahdianpari, M., Brisco, B. and Motagh, M., 2018. Multi-temporal, multi-frequency, and multi-polarization coherence and SAR backscatter analysis of wetlands. ISPRS Journal of Photogrammetry and Remote Sensing, 142, pp.78-93.
25. Mohammadimanesh, F., Salehi, B., Mahdianpari, M., Brisco, B. and Motagh, M., 2018. Wetland Water Level Monitoring Using Interferometric Synthetic Aperture Radar (InSAR): A Review, Canadian Journal of Remote Sensing, pp. 1-16.
26. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., and Brisco, B., 2017. An Assessment of Simulated Compact Polarimetric SAR Data for Wetland Classification Using Random Forest Algorithm. Canadian Journal of Remote Sensing, 43(5), pp.468-484.
27. Mahdianpari, M., Salehi, B. and Mohammadimanesh, F., 2017. The Effect of PolSAR Image De-speckling on Wetland Classification: Introducing a New Adaptive Method. Canadian Journal of Remote Sensing, 43(5), pp.485-503.
28. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., and Motagh, M., 2017. Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 130, pp.13-31.

Conference papers and presentations:
1. Mahdianpari, M, 2020, Big Data for Big Country: Producing the Canadian Wetland Inventory Map Using Satellite Imagery, In IEEE NECEC2017 Conference, St Johns, NL, Canada, November, 2020.
2. Salehi, B., Mahdianpari, M., Mohammadimanesh, F. and Brisco, B., 2019, December. Wetland Inventory of Canada using Satellite Earth Observation Data and Google Earth Engine Cloud. In AGU Fall Meeting 2019. AGU.
3. Mahdianpari, M., Recent Developments in Wetland Mapping and Monitoring Using Remote Sensing Data and Tools From the Avalon Peninsula to Canada, . Newleef2019, St John’s, NL, Canada, 2019.
4. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., Rezayee, M., 2018. Wetland classification using deep convolutional neural network. In 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE.
5. Mohammadimanesh, F., Salehi, B., Mahdianpari, M., Motagh, M., 2018. A new hierarchical object-based classification algorithm for wetland mapping in Newfoundland, Canada. In 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Valencia, Spain.
6. Mohammadimanesh, F., Salehi, B. and Mahdianpari, M., 2017. Moving to RADARSAT constellation mission (RCM) for wetland classification. Geomatics Atlantic2017, November 2017.
7. Mahdianpari, M., Salehi, B., Mohammadimanesh, F. and Motagh, M., 2017. A novel hierarchical framework for wetland classification based on a multi-frequency and multi-polarization SAR data. In IEEE NECEC2017 Conference, St Johns, NL, Canada, November, 2017.
8. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., 2017. Terrestrial oil spill detection using UAV imagery. Geomatics Atlantic2017, November 2017.
9. Mohammadimanesh, F., Salehi, B. and Mahdianpari, M., 2017. Moving to the RCM: A compact Polarimetric feature selection analysis for monitoring of Canadian wetlands. In IEEE NECEC2017 Conference, St Johns, NL, Canada, November, 2017.
10. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., 2017. Novel contextual speckle reduction method of PolSAR images: evaluation of speckle reduction effects on sea ice classification. IGTF2017, ASPRS Annual Conference, At Baltimore, Maryland, March, 2017.
11. Mahdianpari, M., Salehi, B. and Mohammadimanesh, F., 2017, July. A new speckle reduction algorithm of PolSAR images based on a combined Gaussian random field model and wavelet edge detection approach. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 2349-2352). IEEE.
12. Mohammadimanesh, F., Salehi, B., Mahdianpari, M. and Motagh, M., 2017, July. X-band interferometric SAR observations for wetland water level monitoring in newfoundland and labrador. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 3159-3162). IEEE.
13. Mohammadimanesh, F., Salehi, B., Brisco, B., and Mahdianpari, M., 2017. Monitoring of wetland water levels in Newfoundland and Labrador using InSAR technique. IGTF2017, ASPRS Annual Conference, At Baltimore, Maryland, March, 2017.
14. Mohammadimanesh, F., Salehi, B., Brisco, B. and Mahdianpari, M., 2016. Water level monitoring of wetland areas in Newfoundland and Labrador: Results from C-Band Interferometric Synthetic Aperture Radar (InSAR) analysis. In IEEE NECEC2016 Conference, St Johns, NL, Canada, Nov, 2016.
15. Mahdianpari, M., Salehi, B., Mohammadimanesh, F., 2016. Sea ice segmentation of PolSAR data: A case study in Baffin Bay. Newleef2016, St John’s, NL, Canada, 2016.
16. Mahdianpari, M., Salehi, B., 2016. The Investigation of Oil Spill Detection in Terrestrial Area Using Proximal and UAV Data. In IEEE NECEC2016 Conference, St Johns, NL, Canada, Nov, 2016.
17. Mahdianpari, M., Motagh, M. and Akbari, V., 2013. Image enhancement and speckle reduction of full polarimetric SAR data by Gaussian Markov random field. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W3, 2013, SMPR 2013.
18. Mahdianpari, M., Homayouni, S., Fazel, M.A. and Mohammadimanesh, F., 2013. Agricultural land classification based on statistical analysis of full polarimetric SAR data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 1, p.W3.
19. Mahdianpari, M., Motagh, M. and Akbari, V., 2013, September. Urban Land Cover Classification of Polarimetry Images Using Adaptive Contextual SEM Approach. In living planet symposium ESA2013.
20. Fazel, M.A., Homayouni, S., Akbari, V. and Mahdianpari, M., 2012, July. Speckle reduction of SAR images using curvelet and wavelet transforms based on spatial features characteristics. In Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International (pp. 2148-2151). IEEE.
21. Mahdianpari, M., Motagh, M. and Akbari, V., 2012, July. Speckle reduction and restoration of synthetic aperture radar data with an adoptive Markov random field model. In Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International (pp. 276-279). IEEE.

Book chapters:
1. Salehi, B., Mahdianpari, M., Amani, M., Manesh, F.M., Granger, J., Mahdavi, S. and Briscoe, B., 2018. A Collection of Novel Algorithms for Wetland Classification with SAR and Optical Data. In Wetland Classification with SAR and Optical Data. In Wetlands Management-Assessing Risk and Sustainable Solutions. IntechOpen.
2. M. Mahdianpari, A. Tajik, “Caculus2”, 2014, Published Book, Serie Omran and Ghalame Davar Publication, Edition 3, 2019.
3. M. Mahdianpari, M. Forghani, “Caculus1”,2013, Published Book, Serie Omran and Ghalame Davar Publication, Edition 5, 2019.
4. M. Mahdianpari, “Differential Equations”, 2012, Published Book, Mahyar Publication, Edition 6, 2019.

Other Contacts

https://www.researchgate.net/profile/Masoud_Mahdianpari