RESEARCH PROJECTS

  On going projects

1. HSI Sensor: Hyperspectral imaging system development for precision remote sensing applications

Funding agency: Department of Science and Technology, Government of India

Duration: July 2023 - July 2026.

Funding amount: 35.84 Lakh.

Co-PIs: Dr Dinesh Naik, Associate Professor, IIST, Dr Usha Rani Nelakuditi, Professor & Dean, Vignan University, Guntur.

2. Establishment: Regional Center for Geodesy  at IIST (part of the National Center for Geodesy t IIT Kanpur)

    Funding agency: Department of Science and Technolgoy, Government of India

     Duration: Jan 2023 - Jan. 2028

     Funding amount: Rs. 140.9 lakh

3.. DeepCloud: Deep learning based system for time series cloud detection using multi-sensor satellite Imagery

Funding agency: DOS - NRSC under the Advacned Apace Research Group (ASRG) initiative

                Funding amount: Rs. 39 lakh

               Duration: Jan 2022 – Mar. 2025

          Co-PI: Ms Sai Kalpana, Scientist/Engineer SF, NRSC-Hyderabad

4.. Structural and functional characterization of cropping systems using hyperspectral and 3D laser scanning data and big daIta analytics

               (Indo-German consortium research project; Phase-2)

                Funding agency: Department of Biotechnology, Govt. of India

                Funding amount: Rs. 83.15 lakh

               Duration: April 2021 – Mar. 2024

Completed  (2015 onwards)

 1. Indo-German consortium research project "the rural-urban interface of bangalore: a space of transitions in agriculture, economics, and society"

Taking forward the goal of the MOU signed in October 2012 between The Deutsche Forschungsgemeinschaft (DFG), Germany and the Department

of Biotechnology of India (DBT), Government of India for Scientific Cooperation, the following institutions have joined together to perform the theme

specific scientific research, knowledge sharing and technical cooperation.

Indian institutions

The University of Agricultural Sciences, Bengaluru (coordinating institution)

National Institute of Animal Nutrition and Physiology (NIANP), Bengaluru

Indian Institute of Space Science and Technology (IIST), Thiruvanthapuram

Institute for Social and Economic Change (ISEC), Bengaluru

Institute of Wood Science and Technology (IWST), Bengaluru

Ashoka Trust for Research in Ecology and Environment (ATREE Bengaluru and

AjimPremji University (APU), Bengaluru 

German institutions

University of Göttingen

University of Kassel

 As part of the scientific goals of these consortia, IIST and ISEC-Bengaluru have got funding for a joint research project

“Integrating air and space borne spectroscopy and laser scanning to assess structural and functional characteristics of crops and field margin vegetation”.

 Funding agency: Department of Biotechnology, Govt. of India

Funding amount: Rs. 200 lakh

Duration: Nov. 2016 – Sept. 2020

PI: Dr Rama Rao Nidamanuri

Co-PIs:

Prof. Sunil Nautiyal, (ISEC – Bengaluru)

Ms. Ramiya A M (IIST)

  2. Development of a stand-alone atmospheric correction module for hyperspectral data

 This project is part of the DST’s national initiative on hyperspectral remote sensing, creating for infrastructure (equipment) and research grants to academic institutions in India.  As part of this, IIST has taken up the responsibility of developing advanced algorithms based modules for atmospheric correction of hyperspectral data. Various scientific simulations, validations and extended remote sensing applications would be undertaken in this regard.

Funding agency:  Department of Science and Technology (DST), Government of India

Budget: Rs. 142.49 lakh

Duration: April 2016 - March 2021

PI: Dr Rama Rao Nidamanuri

  3. Spectral biochemical analysis of forest species using hyperspectral remote sensing – a case study from Eastern Ghats forest ecosystems

 Leaf chlorophyll and nitrogen are the basic indicators of vegetation health condition and are manifestations of the biogeochemical processes which provide

information on whether an ecosystem sustains or not. The specific objectives of this research are:  1. estimation of canopy level chlorophyll and nitrogen content

of various species using integrated field and satellite based methods, and  2.  correlating spectral variations with that of canopy biochemical patterns under stress conditions.

Funding agency:  Department of Science and Technology (DST), Government of India

 Budget: Rs. 39.5 lakh  

Duration: three years (April 2016 - March 2019)

 PIs: Dr. Ramachandra Prasad, IIIT-Hyderabad, Dr Rama Rao Nidamanuri (IIST).

 4.  Above ground volume/biomass estimation and validation using airborne S- and L-band NISAR data and radiative transfer modeling

          Funding agency: SAC-Ahmedabad

          Budget: Rs. 19 lakh
 

          Role: co-PI      PI: Dr. Smitha Ashok, All Saints College, Trivandrum.

          Duration: Nov. 217 - Nov. 2020

5. City GML based 3D models for smart cities in India using LiDAR point cloud

                 Funding agency: Department of Science and Technology (DST), Government of India

                   Budget: Rs. 33 lakh

                   Role: co-PI

                  PI: Dr Ramiya A M

             Duration:  two years (Oct. 2020 - Sept. 2022)

Doctoral Research Mentor

1.       Mr. Bharath Bhushan, 2014: Multiple classifier system for hyperspectral image classification

2.       Ms. Dhanya S Pankaj, 2016: Improved algorithms for automatic registration of 3D point clouds

3.       Ms. Ramiya A.M., 2016 (jointly with Dr R Krishnan, former Dean R&D, IIST): 3D Semantic labelling of urban LiDAR point cloud and multispectral data 

4.       Ms. Indu I (jointly with Prof. Jai Shanker, IIITM-K), 2019. Estimation of biophysical parameters of tropical forest using optical and LiDAR remote sensing techniques: a case study from Western Ghats of India

5.        Ms. Salghuna, N.N., 2019 (Jointly with Dr R.C. Prasad, IIIT Hyderabad): Approaches for spectral characterization of tree species of Araku forest, Eastern Ghats, using CHRIS-PROBA imagery and canopy   upscaling models by assimilating leaf biophysical-chemical parameters

6.        Mr. Dubacharla Gyaneshwar, 2021: Robust image classification algorithms for multispectral and hyperspectral data in real-time environments

7.       Mr. Sudhanshu Shekhar Jha (2021): Multi-platform hyperspectral target detection and modelling in dynamic atmospheric conditions

8.     Ms. Reji, J. (2021). 3D LiDAR point cloud processing using statistical and machine learning methods for precision agriculture

9.       Mr. Manohar Kumar (2023): Benchmark studies on spectral unmixing of multi-sensor hyperspectral imagery

10.   Mr. Suraj Reddy (2024): (jointly with Dr V K Dadhwal former Director, IIST and Dr C S Jha NRSC Hyderabad): Studies on multi-source remote sensing data integration for modelling and estimation of forest biomass

11.   Mr. Abhijeeth Kumar (2025) (jointly with Dr T Narayana Rao, NARL, Tirupati): A study on structure, dynamics and microphysics of precipitation using X-band dual-polarization radar                            

12.   Mr. Deepak Singh Bisht (2025) (jointly with Dr T Narayana Rao, NARL, Tirupati): Studies on dynamics of integrated water vapor (IWV) and precipitation measurements from a GNSS receiver network     

 13.   Ms. Harsha Chandra (2025): Transferable methods for within-field/patch-level crop identification using drone-based hyperspectral imagery

14.   Ms. Anagha S Sarma (2025): Evolutionary computing and knowledge transfer approaches for hyperspectral image analysis in precision agriculture

15.  Mr Vamsi Krishna (2025) (jointly with Prof. Usha Rani, Vignan University): Development and assessment of knowledge transfer-based approaches for hyperspectral image classification for land use / land cover mapping

Ongoing: 

1.   Mr. Jayasimha  (jointly with Dr P Murugan, URSC Bengaluru): Deep learning approaches for anomaly and target detection in hyperspectral imagery                                                                   

2.   Mr. Ashwin Gujarati  (jointly with Dr R P Singh, SAC Ahmedabad): Remote sensing of eutrophication in inland water bodies of India 

3.   Ms. Punya P: Studies on the long-term dynamics of algal blooms & climate change impacts using statistical and machine learning approach

4.   Ms. Latha Johnson  (jointly with Dr S Muralikrishnan, NRSC Hyderabad): Deep learning-based simulation and generation of high-resolution remote sensing imagery 

5.   Mr. Manoj Kaushik: Machine learning-based discrimination, mapping, and prediction of crop and soil parameters using multi-source hyperspectral imagery

6.   Mr. Ammaji Rao: Crop growth modelling, radiative transfer and machine-machine approaches for precision agriculture

A.  DST Sponsored Central Facility for Hyperspectral Remote Sensing for Southern Region

  A central lab facility with all the advanced equipment for researching on hyperspectral remote sensing/image processing

    has been set up in the Department of Earth and Space Sciences, Indian Institute of Space Science and Technology. The following instruments available.

  1. Hyperspectral spectroradiometer (400 - 2500nm)

 2. Hyperspectral imaging spectroradiometer (400 - 1000nm)

 3. Plant canopy analyser

 4. Chlorophyll concentration meter

 5. Quantum sensor

 6. Laser distance meter (Leica Disto S-910) 

 Researchers and students from Andhra Pradesh, Karnataka, Kerala, Pondicherry, Tamil Nadu, and Telangana can access the facilities. 

     Contact: Dr. Rama Rao Nidamanuri 

          email: rao@iist.ac.in

B. Data Resources 

   As part of the research and teaching activities of the faculty, IIST has acquired/generated several remote sensing data of multispectral,

microwave and LiDAR remote sensing nature.

 Recently IIST acquired good quality terrestrial laser scanner data on trees, crops, and buildings. We will be happy to share some

of the data for students’ projects. Interested may please contact (email: rao@iist.ac.in) explaining the purpose.

 Apart, we can acquire ground / lab / outdoor 3D laser point cloud and hyperspectral images for a variety of applications.

Interested researchers / students may contact with the idea of joint works / usage / collaboration.
 C. Benchmark Dataset for Target Detection Experiments
 Advanced remote sensing techniques have been gaining popularity for decision level strategic applications such as military security and surveillance, and law enforcement.

 Target detection in imagery is the simplest yet powerful general approach suitable for addressing surface object identification and monitoring

requirements in military, mineral recognizance, environmental monitoring and enforcement etc. Noticing the vast potential of target detection

using hyperspectral imagery and the lack of a reference dataset for researchers, we have brought out an exemplary dataset – multi-platform

(ground, airborne and space-borne) remote sensing imagery (hyperspectral) for target detection / engineered material detection studies.

 This dataset is described in our recent article “Jha S.S. and Nidamanuri R.R. (2020). Gudalur Spectral Target Detection (GST-D): A new

benchmark dataset and engineered material target detection in multi-platform remote sensing data, Remote Sensing (Accepted)”

We will be happy to share the datasets with those interested and assist in the appropriate processing and analyses of imagery for various other perspectives.

 Interested researchers may contact me.
 Thank you!

NIR: Networking of Independent Researchers

 A seamless association of researchers across the disciplines-age-position -institution is the evolving approach of research collaboration.

In the NIR, every member is aware and assured of a set of resources without out explicit costs associated with it.

 Often, the research starts with a member proposing a topic for research - can come simply out of nowhere research proposal/PhD/masters

thesis etc., no limit.

 The problem will be put for discussion and will be further guided for a team formation. The members in the team contribute to the

execution of the plans and put in skills, tools, expert suggestion, blessing supervision. The outcome will be credited based on the

level and specifics of member involvement.

 The key aspects of NIR is to (i) optimize the utility, reachability and value creation of tools/techniques/equipment available across

different institutions, and (ii) to help anyone requiring technical guidance, handholding, research mentoring irrespective of the

existence or level of a formal relationship.

 Proposing this approach, we will be pleased to interact and share our resources for research in a truly cross-discipline nature

and is independent of the level of researcher (anyone can approach with a relevant requirement/idea).

 Topics of research are plenty – urban, water resources, water quality (marine/inland), forestry, agriculture,

soils, environmental monitoring and management, air, soil, and water pollution etc.