Gopal Krishna, Ph. D.
Multispectral and Hyperspectral Image Processing for Remote Sensing of vegetation and LULC change.
Development of methodologies for data analysis and modeling for Natural Resources Management.
Cropping pattern identification using MODIS and Spot VGT products.
Inter-seasonal temperature variation analysis using MODIS (LST) and Landsat (Thermal bands) satellite data.
Hyperspectral Remote Sensing Expertise:
Hyperspectral Image Processing: Atmospheric Correction, MNF transformation, end members extraction and classifications (sub pixel and crop type discrimination).
Hyperspectral BRDF data generation and analysis to identify reflectance hotspot and crop biophysical parameters retrieval.
Correlation analysis between reflectance & its derivatives with crop parameters.
Spatial Analysis, DEM - DTM Modeling, Topology Building, Thematic Mapping, Geoprocessing, Image- vector alignment, Weather and temperature data analysis, etc.
GIS/Remote sensing for Urban Mapping, Land base creation and Change detection.
River analysis for Flood Inundation Mapping.
Hyperspectral reflectance analysis to develop hyperspectral indices/ model for disease identification.
Programming knowledge in Python, R and Matlab and basics of website designing using HTML.
The Vasai creek, the Manori creek and the Thane creek are estuarine creeks in the Arabian Sea near Mumbai.This area has the highest economic development rates in India. In this estuarine area, extensive land use change including embankments was observed and various constructions have taken place due to rapid urbanization and industrialization. Improper and unplanned sustainable coastal zone management may lead to severe environmental problems such as sea water intrusion, coastal erosion, siltation of river channels and land subsidence, etc. This study evaluates the utility of satellite remote sensing imageries by deploying multi-temporal Landsat series satellite data (MSS, TM5 and OLI) and high-resolution Google earth imagery including a topographic map of Mumbai also.
In recent past we have witnessed nature’s fury in Uttarakhand state of India. There were clearly two flood events in Mandakini valley on 16th and 17th June of 2013 and later was associated with the breach of Chorabari Tal. The present study was carried out to simulate flood plain and to map inundation area of Alaknanda, Mandakini and Bhagirathi rivers in the region of Rudraprayag and Uttarkashi of Uttarakhand respectively using hydraulic modeling on GIS based HEC-GeoRAS platform through detailed parameterization of river channels.
I am a researcher in Remote Sensing and GIS field, currently I am doing research using Hyperspectral remote sensing techniques for Natural Resources Management.
Areas of Interest include Satellite image processing, Hyperspectral BRDF, Multivariate Analysis of Reflectance Spectra, Floodplain simulation, Modelling using ArcSWAT, Spatiotemporal Analysis of LULC, GIS for LULC mapping, etc
The study was carried out for Indian capital city Delhi using Hyperion sensor onboard EO-1 satellite of NASA. After MODTRAN-4 based atmospheric correction, MNF, PPI and n-D visualizer were applied and endmembers of 11 LCLU classes were derived which were employed in classification of LULC. To incur better classification accuracy, a comparative study was also carried out to evaluate the potential of three classifier algorithms namely Random Forest (RF), Support Vector Machines (SVM) and Spectral Angle Mapper (SAM). The results of this study reemphasize the utility of satellite borne hyperspectral data to extract endmembers and also to delineate the potential of random forest as expert classifier to assess land cover with higher classification accuracy that outperformed the SVM by 19% and SAM by 27% in overall accuracy. This research work contributes positively to the issue of land cover classification through exploration of hyperspectral endmembers. The comparison of classification algorithms’ performance is valuable for decision-makers to choose better classifier for more accurate information extraction.
Ten different wheat genotypes were studied for understanding their differential behaviour to different water-deficit stress levels. Hyperspectral data (350-2500 nm) and relative water content (RWC) of plants were measured at different stress level for identifying optimal spectral bands, indices and multivariate models to develop non-invasive phenotyping protocols. Evaluation of water sensitive existing spectral indices, proposed indices and band depth analysis at selected wavelengths was done with respect to RWC and prediction
models were developed.
Presently pursuing Ph.D degree in Geoinformatics and Remote Sensing from Amity University, Noida. I studied Geoinformatics at the Indian Institute of Ecology and Environment, New Delhi in collaboration with Sikkim Manipal University of Health, Medical and Technological Sciences, (two years duration) where I obtained a Master’s degree (M.Sc.). After that I joined and successfully completed PG diploma in GIS and Remote sensing (6 months duration) from Center for development of advanced computing (CDAC), Noida, India.
I also enriched my knowledge with few expert training courses which deals with advanced level of Remote Sensing. So I have successfully gained certificates in ‘Hyperspectral Remote Sensing’ (50 days duration) and Microwave Remote Sensing for Natural Resources (3 months duration)from EDUSAT program of Indian Institute of Remote Sensing, Dehradun, India and ‘Introduction to ArcGIS Desktop 10’ certification (5 days duration) from ESRI, India .
After completion of my professional studies, I worked with privately held Remote sensing and GIS organizations for 2 and ½ years. In these organizations, I worked with the capacity of Remote sensing and GIS Executive and I learnt a lot about change detection analysis, topology creation for huge GIS data, Land use and Land cover layers extraction from high resolution imagery (Quick bird, IKONOS, Geoeye), Google Earth imagery as well as LISS III, LISS-IV and Landsat data, etc. I worked there for many of the projects of national repute.
Due to my deep interest in research activities in this field, I joined the prestigious Indian Agricultural Research Institute (IARI), New Delhi as a Senior Research Fellow in fall of year 2012. Here I learnt state-of-the-art techniques from highly qualified scientists and gained very precious professional research experience. Here I joined a research group and participated in different research projects under earth observation projects of Govt. of India.
About the Author
Natural Resources Management
Agriculture, Land, Water.
2015 - 2018
Amity University, Noida , Uttar Pradesh, India
Ph.D - Geoinformatics and Remote Sensing
Hyperspectral Remote Sensing
Satellite, Airborne and Spectroscopy
Crop Disease Monitoring
Using Satellite and Spectroscopic Remote Sensing
Retreival of Crop Biophysical Parameters
Hyperspectral BRDF, PROSAIL, Inversion
2006 - 2008
Indian Institute of Ecology & Environment, New Delhi in collaboration with SMU
M.Sc. - Geoinformatics
2008 - 2009
Center for Development of Advanced Computing (CDAC) Noida
PG Diploma in GIS and Remote Sensing
Best Paper Award at ESRI INDIA Conference, New Delhi-2015, for paper entitled"Flood Plain Modelling using River Hydraulic Modelling Approach"
Second Best Paper Award (Poster Presentation) at International Society of Photogrammetry and Remote Sensing (ISPRS), Hyderabad-2014 for paper entitled "Assessing Wheat Yellow Rust using Hyperspectral Remote Sensing".
Second Best Paper Award (Oral Presentation) at International Society of Photogrammetry and Remote Sensing (ISPRS), Hyderabad-2014 for paper entitled "Wheat Phenomics for Hyperspectral Remote Sensing for water Deficit Stress".
Advanced Course on Microwave Remote Sensing From EduSAT IIRS, Dehradun (3months).
Advanced Course on Hyperspectral Remote Sensing From EduSAT IIRS, Dehradun (50 Days).
Training attended on ArcGIS Desktop at ESRI INDIA (5 days).
Training attended on Remote Sensing and GIS technology at Indian Institute of Ecology & Environment, Delhi.
Training attended on ‘Advances of spectrometry in earth remote sensing’ in pre-symposium tutorial.
Introduction to Python Programming from Microsoft edx.