Hi, I'm Bharath Reddy K.
A
An ambitious, self-motivated and passionate Remote Sensing Data Engineer with a curious mind who enjoys solving complex and challenging real-world problems using Remote Sensing and Geo-spatial technologies.
About
I am a Remote Sensing Data Engineer at the National Remote Sensing Centre, Indian Space Research Organization.
Skilled in Digital Image Processing, Data analytics, ML algorithms, open source ML, DP and DIP libraries, ESRI/Hexagonal/PCI Products, Statistical Data Analysis and Remote Sensing.
Experience
- Remote Sensing and GIS-based solutions for operational hydrological drought assessment
- Multi-sensor based temporal surface "Water Bodies Information System" (WBIS)
- Orthorectified imagery generation of entire India for Bhuvan - a geoportal of Indian Space Research Organization
- Development of GIS solutions, tools and maps for irrigation and command area development of Telangana for efficient water resources planning (TWRIS)
- Applications of UAV data in capacity estimation of minor irrigation tanks
- Mapping of river course changes of Yamuna near Mathura and Vrindavan
- Catchment delineation for irrigation tanks
- Extraction of paddy grown regions from Synthetic Aperture Radar (SAR) imagery using machine learning
- Pan-sharpening using HPF & Brovey Fusion
- Optimal satellite image pair selector for minimal gap in pan-sharpened product
Worked on geo-spatial data production, devopment of geo-spatial tools and techniques for processing Remote Sensing and GIS data. Following are the major projects/activities I'm involved in:
Developed GIS applications (using opensource tools), such as:
- As a project trainee, I worked towards the application of object-based classification techniques for the identification of citrus orchards using Remote Sensing and GIS tools. Published and presented the same in a conference
Projects
Multi satellite and sensor based water bodies surface water spread information system for India.
- Tools: GDAL, PostgreSQL, PostGIS, Python
- Developed and integrated algorithms for extraction of water spread area derived from new satellite sensors and built a robust Geospatial database of inland waterbodies.
- Advanced image processing techniques such as machinelearning, object-based techniques, etc., are employed to extract water spread area in near real-time from Optical and Synthetic Aperture Radar data derived from Copernicus missions such as Sentinel-1,2 & Indian satellites such as Resourcesat-1, 2, 2A, RISAT-1 etc.
- This database is currently being used for water assessment, inland fisheries potential, hydrological drought, etc. and is made available to the public
Hydrological Drought Assessment is a National Project with the objectives to characterize spatiotemporal variability of hydrological drought, provide hydrological drought indices based on geospatial data, hydrological model outputs and observational/field data.
A 2.5m resolution seamless ortho rectified image tiles generation using Indian Remote Sensing satellites data.
A comprehensive geo-database of water related data for Telangana State in India.
Capacity estimation of minor irrigation tanks using UAV and satellite based remote sensing.
- A novel approach was proposed and published to use images acquired from the Unmanned Aerial Vehicle (UAV) platform instead of stereo images from other sources/platforms for generating Elevation Area Capacity (EAC) relationship curves
- These EAC curves in combination with the near real-time water spread area obtained from satellite remote sensing were used to estimate the volume of water available in a tank
Orthorectified data geometric accuracy evaluator developed for quick QC.
- Fourier phase correlation with Log - Polar Transform along with Template matching using normalized cross-correlation is used in the process
Check details for other short term projects.
- Developed a classification algorithm using machine learning methods such as Quadratic Discriminant Analysis for the extraction of paddy grown regions from the Synthetic Aperture Radar data.
- Developed optimal image pair (Pan chromatic-Pan & Multispectral-MS) identification tool from a lot of Pan and MS imagery which has criteria of minimizing the number of gaps that are likely to occur in the final pan-sharpened images.
Skills
Languages and Databases
Python
PostgreSQL
PostGIS
C
Matlab
Libraries
NumPy
OpenCV
scikit-learn
matplotlib
scipy
numba
GDAL & OGR
Geospatial Softwares
QGIS
ArcGIS
ERDAS
PCI Geomatica
Ecognition
Orfeo Toolbox
Other
Latex & Beamer
Education
Birla Institute of Technology And Science, Pilani (BITS Pilani)
Hyderabad, India
Degree: Master of Technology in Data Science & Engineering
- Machine Learning
- Natural Language Processing
- Deep Learning
- Big Data Systems
Relevant Courseworks:
Indian Institute of Space Science and Technology
Trivandrum, Kerala, India
Degree: Bachelor of Technology in Physical Sciences
- Remote Sensing
- Geographic Information Systems
- Digital Image Processing
- Atmospheric Sciences
Relevant Courseworks:
Publications
Achievements
Awarded scholarship for 8 consecutive semesters by Department of Space, Government of India. 120 out of 150,000 meritorious applicants received this grant.
Telangana Water Resources Information System (TWRIS), a project in was I was involved directly as a GIS data analyst was awarded with 2nd Prize under the category “Comprehensive Water Data Base in Public Domain”.
Rated as Brilliant (Grade: 10/10) for my contributions to the organization for the years 2024, 22, 21 & 20
Rated as Outstanding (Grade: 9/10) for my contributions to the organization for the year 2023, 19, 18, 17 & 16