Back to top

Areas of expertise

Environmental remote sensing and geomatics

Phone
418 654-2687

Email
saeid.homayouni@ete.inrs.ca

Eau Terre Environnement Research Centre

490 rue de la Couronne Street
Québec, Quebec  G1K 9A9
CANADA

See the research centre

Research interests

Professor Homayouni research and teaching interests include mainly geomatics, remote sensing, and the analysis of Earth observations, optical and synthetic aperture radar, through approaches using artificial intelligence and machine learning for urban and agro-environmental applications.

Saeid Homayouni is currently an associate professor in environmental remote sensing and geomatics at the Centre for Water, Earth and Environment, at the National Scientific Research Institute (INRS) in Quebec City, Canada .

He received the B.Sc. degree in surveying and geomatics engineering from the University of Isfahan, Isfahan, Iran, in 1996, the M.Sc. degree in remote sensing and geographic information systems from the Tarbiat Modaress University, Tehran, Iran, in 1999, and the Ph.D. degree in Signal and Image (Hyperspectral Remote Sensing) from the Télécom Paris Tech, Paris, France, in 2006.

He has worked as a post-doc fellow in Signal & Image Laboratory of the University of Bordeaux, France, from 2006 to 2007. From 2008 to 2011, he was with the Department of Geomatics and Surveying, College of Engineering, at the University of Tehran, Iran, as an assistant professor, and then worked as an NSERC research fellow at the Ottawa Center of  Research and Development Agriculture Canada. In 2013, he joined the Department of Geography, Environment, and Geomatics of the University of Ottawa, as an assistant professor in remote sensing and geographic information systems. He joind INRS in 2019.

 

Publications

Ahmadi, Salaman & Homayouni, Saeid (2020). A novel active contours model for environmental change detection from multitemporal synthetic aperture radar images. Remote Sens., 12 (11): Art. 1746.
DOI: 10.3390/rs12111746

Dufour-Beauséjour, Sophie; Bernier, Monique; Simon, Jérome; Homayouni, Saeid; Gilbert, Véronique; Gauthier, Yves; Tuniq, Juupi; Wendleder, Anna & Roth, Achim (2021). Tenuous correlation between snow depth or sea ice thickness and C- or X-Band backscattering in Nunavik Fjords of the Hudson Strait. Remote Sens., 13 (4): Art. 768.

Hosseini, Mehdi; McNairn, Heather; Mitchell, Scott; Robertson, Laura Dingle; Davidson, Andrew & Homayouni, Saeid (2020). Integration of synthetic aperture radar and optical satellite data for corn biomass estimation. MethodsX, 7: Art. 100857.
DOI: 10.1016/j.mex.2020.100857

Hosseini, Mehdi; McNairn, Heather; Mitchell, Scott; Robertson, Laura Dingle; Davidson, Andrew; Ahmadian, Nima; Bhattacharya, Avik; Borg, Erik; Conrad, Christopher; Dabrowska-Zielinska, Katarzyna; de Abelleyra, Diego; Gurdak, Radoslaw; Kumar, Vineet; Kussul, Natalia; Mandal, Dipankar; Rao, Y. S.; Saliendra, Nicarnor; Shelestov, Andrii; Spengler, Daniel; Verón, Santiago R.; Homayouni, Saeid & Becker-Reshef, Inbal (2021). A comparison between support vector machine and water cloud model for estimating crop leaf area index. Remote Sens., 13 (7): Art. 1348.
DOI: 10.3390/rs13071348

Mahdianpari, Masoud; Ghanbari, Hamid; Mohammadimanesh, Fariba & Homayouni, Saeid (2021). A meta-analysis of convolutional neural networks for remote sensing applications. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens., 14: 3602-3613.
DOI: 10.1109/JSTARS.2021.3065569

Shayeganpour, Samira; Tangestani, Majid H.; Homayouni, Saeid & Vincent, Robert K. (2021). Evaluating pixel-based vs. object-based image analysis approaches for lithological discrimination using VNIR data of WorldView-3. Front. Earth Sci., 15 (1): 38-53.

Aria, Enayat Hosseini; Menenti, Massimo; Gorte, Ben G. H. & Homayouni, Saeid (2020). Unsupervised dimensionality reduction of hyperspectral images using representations of reflectance spectra. Int. J. Remote Sens., 41 (20): 7820-7845.
DOI: 10.1080/01431161.2020.1766146

Bahrami, Hazhir; Homayouni, Saeid; Shah-Hosseini, Reza; ZandKarimi, Arash & Safari, Abdolreza (2020). Efficient dust detection based on spectral and thermal observations of MODIS imagery. J. Appl. Remote Sens., 14 (3): Art. 034513.
DOI: 10.1117/1.JRS.14.034513

Eskandari, Roghieh; Mahdianpari, Masoud; Mohammadimanesh, Fariba; Salehi, Bahram; Brisco, Brian & Homayouni, Saeid (2020). Meta-analysis of unmanned aerial vehicle (UAV) imagery for agro-environmental monitoring using machine learning and statistical models. Remote Sens., 12 (21): Art. 3511.
DOI: 10.3390/rs12213511

Hamidi, Masoumeh; Safari, Abdolreza & Homayouni, Saeid (2020). An auto-encoder based classifier for crop mapping from multitemporal multispectral imagery. Int. J. Remote Sens., 42 (3): 986-1016.
DOI: 10.1080/01431161.2020.1820619

Hosseiny, Benyamin; Rastiveis, Heidar & Homayouni, Saeid (2020). An automated framework for plant detection based on deep simulated learning from drone imagery. Remote Sens., 12 (21): Art. 3521.
DOI: 10.3390/rs12213521

Jamshidpour, Nasehe; Safari, Abdolreza & Homayouni, Saeid (2020). A GA-based multi-view, multi-learner active learning framework for hyperspectral image classification. Remote Sens., 12 (2): Art. 297.
DOI: 10.3390/rs12020297

Jamshidpour, Nasehe; Safari, Abdolreza & Homayouni, Saeid (2020). Multiview active learning optimization based on genetic algorithm and gaussian mixture models for hyperspectral data. IEEE Geosci. Remote Sens. Letters, 17 (1): ONLINE.
DOI: 10.1109/LGRS.2019.2914858

Mahdianpari M, Brisco B, Granger JE, Mohammadimanesh F, Salehi B, Banks S, Homayouni S, Bourgeau-Chavez L & Weng Q (2020). The second generation Canadian Wetland inventory map at 10 meters resolution using Google Earth Engine / La deuxième génération de la carte de l’inventaire canadien des milieux humides à une résolution de 10 mètres en utilisant Google Earth Engine. Can. J. Remote Sens. / J. Can. Télédétection, 46 (3): 360-375.
DOI: 10.1080/07038992.2020.1802584

Mahdianpari, Masoud; Jafarzadeh, H.; Granger, Jean Elizabeth; Mohammadimanesh, Fariba; Brisco, Brian; Homayouni, Saeid & Weng, Qihao (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): 1102-1124.
DOI: 10.1080/15481603.2020.1846948

Mandianpari, Masoud; Granger, Jean Elizabeth; Mohammadimanesh, Fariba; Salehi, Bahram; Brisco, Brian; Homayouni, Saeid; Gill, Eric; Huberty, Brian & Lang, Megan (2020). Meta-analysis of wetland classification using remote sensing: A systematic review of a 40-year trend in North America. Remote Sens., 12 (11): Art. 1882.
DOI: 10.3390/rs12111882

Mahdianpari M, Salehi B, Mohammedimandesh F, Brisco B, Homayouni S, Gill E, DeLancey ER & 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  /  Mégadonnées pour un grand pays: La première carte d’inventaire des zones humides du Canada à une résolution de 10 m à l’aide des données Sentinel-1 et Sentinel-2 sur la plate-forme informatique en nuage de Google Earth Engine™. Can. J. Remote Sens. / J. Can. Télédétection, 46 (1): 15-33.
DOI: 10.1080/07038992.2019.1711366

Mohammedi, Ayub; Karimzadeh, Sadra; jalal, Shazad Jamal; Kamran, Khalil Valizadeh; Shahabi, Himan; Homayouni, Saeid & Al-Ansari, Hadhir (2020). A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models. Sensors, 20 (24): Art. 7214.
DOI: 10.3390/s20247214

Parto, Fatemeh; Saradjian, Mohammadreza & Homayouni, Saeid (2020). MODIS brightness temperature change-based forest fire monitoring. J. Indian Soc. Remote Sens., 48 (1): 163-169.
DOI: 10.1007/s12524-019-01071-w

Sheykhmousa, Mohammadreza; Mahdianpari, Masoud; Ghanbari, Hamid; Mohammadimanesh, Fariba; Ghamisi, Pedram & Homayouni, Saeid (2020). Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens., 13: 6308-6325.
DOI: 10.1109/JSTARS.2020.3026724

Yavari, Adel; Homayouni, Saeid; Oubennaceur, Khalid & Chokmani, Karem (2020). Flood inundation modeling in ungauged basins using Unmanned Aerial Vehicles imagery. Earth Obs. Geomat. Eng., 4 (1): 44-45.
DOI: 10.22059/eoge.2020.297824.1075

Gahrouei, Omid Reisi; McNairn, Heather; Hosseini, Mehdi & Homayouni, Saeid (2020). Estimation of crop Biomass and leaf area index from multitemporal and multispectral imagery using machine learning approaches / Estimation de la biomasse & de l’indice de surface foliaire de cultures à partir d’images multi-temporelles & multi-spectrales à l’aide d’approches d’apprentissage automatique. Can. J. Remote Sens. / J. Can. Télédétection, 46 (1): 84-99.
DOI: 10.1080/07038992.2020.1740584

Farhadiani, Ramin; Homayouni, Saeid & Safari, Abdolreza (2019). Hybrid SAR speckle reduction using complex wavelet shrinkage and non-local PCA-Based filtering. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens., 12 (5): 1489-1496.
DOI: 10.1109/JSTARS.2019.2907655

Hadavand, Ahmad; Saadat Seresht, Mohammad & Homayouni, Saeid (2019). A novel density-based super-pixel aggregation for automatic segmentation of remote sensing images in urban areas. Earth Obs. Geomat. Eng., 3 (21): 84-91.
DOI: 10.22059/EOGE.2019.282354.1048

Hosseini, Mehdi; McNairn, Heather; Mitchell, Scott; Dingle Robertson, Laura; Davidson, Andrew & Homayouni, Saeid (2019). Synthetic aperture radar and optical satellite data for estimating the biomass of corn. Int. J. Appl. Earth Observ. Geoinfo., 83): Art. 101933.
DOI: 10.1016/j.jag.2019.101933

Mahdianpari, Masoud; Mohammedimandesh, Fariba; McNairn, Heather; Davison, Andrew; Rezaee, Mohammad; Salehi, Bahram & Homayouni, Saeid (2019). Mid-season crop classification using dual-, compact-, and full-polarization in preparation for the radarsat constellation mission (RCM). Remote Sens., 11 (13): Art. 1582.
DOI: 10.3390/rs11131582

Niazmardi, Saeid; Homayouni, Saeid & Safari, Abdolreza (2019). A computationally efficient multi-domain active learning method for crop mapping using satellite image time-series. Int. J. Remote Sens., 40 (16): 6383-6394.
DOI: 10.1080/01431161.2019.1591648

Reisi-Gahrouei, Omid; Homayouni, Saeid; McNairn, Heather; Hosseini, Mehdi & Safari, Abdolreza (2019). Crop biomass estimation using multi regression analysis and neural networks from multitemporal L-band polarimetric synthetic aperture radar data. Int. J. Remote Sens., 40 (17): 6822-6840.
DOI: 10.1080/01431161.2019.1594436

See previous publications on ResearchGate