speaker

Dr. Rama Rao

Associate Professor

Department of Earth and Space Sciences

Indian Institute of Space and Technology

Thiruvananthapuram

email: rao@iist.ac.in

Brief Introduction

Dr. Rama Rao is an associate professor in the department of Earth and Space Sciences, Indian Institute of Space Science and Technology (IIST), Department of Space, Thiruvananthapuram. Dr. Rao obtained M.Tech (Remote Sensing) from Birla Institute of Technology, Mesra, Ranchi in 2001 and PhD from Indian Institute of Technology, Roorkee on hyperspectral image processing in November 2006. After a brief stint at RMSI Pvt. Ltd, Noida as a project leader leading few projects involving remotes sensing applications in agriculture, Dr. Rao moved on to continue academic pursuits in RMIT University, Australia, and Leibniz-Center for Agricultural Landscape Research, Germany, postdoctoral research scientist securing Endeavour Research Fellowship -Australia and Alexandervon Humboldt Fellowship - Germany. During this period, he performed extensive research studies on hyperspectral image processing and analysis methods and developed several new hyperspectral data analysis algorithms. Results of these studies are published in several journals published by IEEE / Elsevier, Springer/ Taylor & Francis etc. He has been an active member of several professional societies including Senior Member of IEEE. Dr. Rao has been actively working on the classification/automation/target detection /using high and ultra-high spatial /spectral resolution remote sensing data (terrestrial, drone, airborne and satellite based), LiDAR point cloud and 3D modelling of natural and built environment. Currently Dr. Rao has been handling multiple funded research projects on developing algorithms and methodologies for processing of integrating / fusing hyperspectral and LiDAR remote sensing data for procession agriculture, forestry, water quality monitoring, industrial material inspection etc.

Abstract

The advancements in the classification, data fusion of high spatial resolution active (LiDAR) and passive remote sensing data: Data acquisition in remote sensing has been going through a silent revolution with the evolution of field / industry ready compact imaging systems (e.g. indoor spectral imager) and platforms (e.g. drones). Even at modest operation level, the current pace of remote sending data acquisition is several orders of magnitude of the current level of human and processing systemsâĂŹ availability. The fast and voluminous remote sensing data rate needs adaptive and knowledge inspired algorithms and methodologies for automation and replication of remote sensing applications. Among the possible remote sensing techniques, hyperspectral and LiDAR data have been found to be promising in terms of their potential readiness for developing precision applications from both in door and landscape perspectives. These two technologies complement each other for balancing the limitations and together can offer a range of applications in various domains of applications. Amongst the possible ways of analyses, classification has been one of the best approaches of fused data exploitation. In this talk, with a brief on advanced remote sensing techniques, I will present the advancements in the classification, data fusion of high spatial resolution active (LiDAR) and passive remote sensing data (hyperspectral) acquired from ground and drone platforms (with example works at IIST). Classification Algorithms for industrial level applications of hyperspectral imagery would be discussed with example works from IIST.