Sorry, you need to enable JavaScript to visit this website.

  • 8:10 PM, Tuesday, 22 Sep 2020

Department of Earth and Space Sciences
     
Ramiya A.M., Ph.D.
Assistant Professor
 
Office
Tel:+91-471-2568527
Fax:+91-471-2568462
Email:ramiya@iist.ac.in













Education
  • PhD  in Remote Sensing , IIST, Thiruvananthapuram (Dissertation: 3D Semantic Labelling of urban LiDAR point cloud and multispectral data)
  • M.S. in Remote Sensing and Spatial Analysis, University of Southampton, UK (Dissertation : Effect of Atmosphere on object oriented segmentation for land cover classification)
  • B.E. in Geoinformatics, CEG, Anna University, Chennai (Dissertation : Estimating the Area of Vaigai Reservoir – A Sub Pixel Approach)

 

For more details:

Personal Webpage:

https://sites.google.com/view/ramiya-iist


Course Offered

 • LiDAR Remote Sensing

• Digital Image Processing of Remotely Sensed Data

• Remote Sensing and Application

• Geographic Information System

• Satellite based Navigation and Positioning

• Introduction to Data Structures, Algorithms and Database Management

• Scientific Computing for Geospatial Data Analysis

 


Experience
  • Assistant Professor, Indian Institute of Space Science and Technology, Thiruvananthapuram (Dec 2017 – present)
  • Reader, Indian Institute of Space Science and Technology, Thiruvananthapuram (July 2009 – Dec 2017)
  • Junior Research Fellow, Centre for Earth Science Studies, Akkulam, Thiruvananthapuram (March 2009 – July 2009)
  • Software Engineer, Infosys Technologies Ltd, Bangalore (May 2006- July 2007)

Research Work / Area
  • LiDAR Point Cloud Processing : Development of Algorithms and techniques, 3D processing/visualization/VR

    • Primary Application areas: Urban., agriculture, forest, disaster management, cultural heritage mapping, archaeological studies, industrial application , etc

  • Development of processing, analyzing, high spatial/spectral remote sensing images : Hyperspectral/Multispectral/Microwave

    • Developing geo-spatial solutions for real world applications related to Urban., agriculture, forest, disaster management etc

  • Geospatial analysis using open source programming and machine learning techniques,Spatial database, spatial data structures