Hosseini, Mehdi

Bio

Dr. Hosseini is an Associate Research Professor of the NASA Harvest Hub at the Department of Geographical Sciences, University of Maryland, College Park. His research related to optical and SAR applications to crop monitoring and production forecasting for both large scale agricultural systems and smallholder systems at the field to national scales. This is involved developing and refining models for yield forecasting, cropland and crop type mapping, and crop condition assessments. Dr. Hosseini has expertise in model development for agricultural and environmental applications using radar and optical remote sensing data. His interests include using physical, statistical and machine learning approaches for modeling of agricultural and environmental parameters. During 2017-2019, Dr. Hosseini was a co-lead of an international project involving 18 countries for studying the best practices for crop biomass and leaf area index (LAI) estimations and crop type classification using Synthetic Aperture Radar (SAR). 

Degrees

  • Remote Sensing - Ph.D.

  • Remote Sensing - MS.c.

  • Geomatics Engineering - Bachelor

Areas of Interest

  • Polarimetric SAR
  • InSAR
  • Machine Learning

                        

                                                                                                                                      
  • Kerner, H. R., Sahajpal, R., Pai, D. B., Skakun, S., Puricelli, E., Hosseini, M., ... & Becker-Reshef, I. (2022). Phenological normalization can improve in-season classification of maize and soybean: A case study in the central US Corn Belt.

  • Ranjbar S., Akhoondzadeh M., Brisco B., Amani M., Hosseini M., 2021, Soil Moisture Change Monitoring from C and L-band SAR Interferometric Phase Observations, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.110

  • Hosseini, M., McNairn, H., Mitchell, S., Robertson, L. D., Davidson, A., Ahmadian, N., Bhattacharya, A., et al. (2021). A Comparison between Support Vector Machine and Water Cloud Model for Estimating Crop Leaf Area Index. Remote Sensing, 13(7), 1348. MDP


                                                                              

                      

                      

                        
                        1 of 1.3333333333333
                        
                      

                      
                      

                                            
                    

                    
                                      

                

              

            

          


                    

            

            
 

            

                              

                  
Personal Website(s)

                  
                

              
                          

          

                  



        

  
                              

            
  
        Mehdi Hosseini



  



          

                    
                              

            Mehdi Hosseini

            Associate Research Professor
          

                      
                    	  

          

             | 4600 River Road, Suite 310 (send mail to 2181 LeFrak)
          

                      
                              

             | mhoseini@umd.edu