893 Rate this article:

Student Spotlight Summer 2021

Andrew Fore

Prateek Tripathi, our first L3Harris Geospatial Student Spotlight, is a Ph.D. candidate in the Geomatics Engineering Group, Department of Civil Engineering at Indian Institute of Technology Roorkee, Uttarakhand, India. His research interests include hyperspectral remote sensing image analysis, Earth, Lunar and Mars geology, spectroscopy and its applications, UAV applications, and machine learning applications. “It has always been my dream to study planetary science,” says Tripathi.

Under the direction of Dr. Rahul Dev Garg, Tripathi is working on the identification and characterizations of analogs for planetary surfaces by integrating the Raman, VNIR-SIR, thermal range spectra from the field with hyperspectral imagery of the Earth and Moon. “I have worked on the surface composition and future scope to explore different extra-terrestrial surfaces like the Moon, Mars, and Jupiter,” explains Tripathi. The focal point of his research is to look for Earth-like features or processes on other planetary surfaces to search for signs of life. Recently one of his research papers on the first results of PRISMA hyperspectral data was published in a peer-reviewed science journal.

“ENVI® plays a crucial role in my research. I use ENVI to process every type of remote sensing dataset (Earth and planetary), including panchromatic imagery, visible and infrared imagery, hyperspectral imagery, and microwave (ENVI SARscape), and ultraviolet imagery,” says Tripathi.


The following methods and results were Tripathi’s entry for L3Harris Geospatial and also part of his Ph.D. project:

Integration of Raman, VNIRSWIR, FTIR and hyperspectral imaging for mineral identification: Implications for future lunar missions



Remote sensing has increasingly taken on a vital role in monitoring and maintaining various natural resources. Hyperspectral data can provide detailed information about any object or feature of interest. However, until the recent launches of PRISMA and DESIS, there was a shortage of timely global hyperspectral imagery available. The following methods use ENVI to analyze PRISMA and DESIS imagery to obtain results.


1. We processed and analyzed the newly released PRISMA and DESIS hyperspectral dataset with a few non-traditional image and signal processing methods such as derivative spectroscopy. This work was done for few areas of geological importance in India. The ".he5" data of PRISMA was successfully processed with ENVI in the first week of the dataset’s launch. We published the first work on PRISMA hyperspectral datasets for the Indian region (https://wwwops.currentscience.ac.in/Volumes/119/08/1267.pdf).

In this work, a few overlapped absorption features were enhanced after using derivative spectroscopy in ENVI spectral profile tool. The derivative spectroscopy plays an essential role in identifying and characterizing the hidden and overlapped absorption features of important minerals. Derivative spectroscopy also helped in mitigating the noise present in spectra.

Figure 1. 2nd order derivative for a spectra obtained from PRISMA data

2. We have also used the same technique on airborne earth observation data (AVIRIS) and lunar hyperspectral datasets such as Moon Mineralogy Mapper, VNIS from Chang'e 4. Spectral absorption features other than pyroxenes, iron is seen. Also, we found the similarity between spectral features obtained from M3 and VNIS data and PRISMA 2nd derivative spectra from the Tamil Nadu state of India. It shows the presence of lunar analogs.

3. We also analyzed the similarity between Raman spectra of a few terrestrial and Apollo returned samples using ENVI, and the results supported the presence of analogs for lunar breccia. This work is presented at 52nd Lunar and Planetary Science Conference 2021 (https://www.hou.usra.edu/meetings/lpsc2021/pdf/1602.pdf).

Figure 2. 2nd order derivative for a spectra obtained from PRISMA data

4. We also fused the results obtained from various data dimensionalities reduction techniques like PCA, MNF, and ICA and classified them using the unsupervised methods available in ENVI. This work is done for DESIS and PRISMA hyperspectral data from Rajasthan and Tamil Nadu, India. We got some exciting geological results. This work is currently under review.

Figure 3. Unsupervised classification of PCA-MNF-ICA fused images from DESIS AND PRISMA hyperspectral data of Rajasthan, India. These classes represent the mineral classes.


1. The study (derivative spectroscopy of newly launched hyperspectral datasets) is focused on the characteristics and compatibilities of the PRISMA hyperspectral sensor. It will be beneficial to the scientific and user community. The enhanced mineral mapping and identification will be handy to geoscientists, geologists and researchers in geology. The derivative spectroscopy can enhance our knowledge about an already mapped geological area. Various scholars in our group came to know about derivative spectroscopy and are also using ENVI in their work. Geology (derivative spectroscopy), implemented in ENVI and IDL, can also enhance the spectral features of urban remote sensing, water resources, agriculture, soil, etc.

2. The spectral profile tool in ENVI can be used in visualizing Raman, XRD, and other quantitative spectra, giving the user an upper hand by analyzing all of the spectral ranges in a single software.


You could be the next L3Harris Geospatial Student Spotlight!
Learn more by visiting l3harrisgeospatial.com/Industry-Solutions/Academic/Student-Spotlight


Students, Researchers and Instructors


Using ENVI and IDL for research and to prepare students for successful careers.


ENVI Software


Process and analyze all types of imagery resources, and data



Extract meaningful visulizations from complex numerical data.