The aim of satellite remote sensing of the earth is to efficiently reproduce surface and sub-surface properties to achieve an end application. Field investigations are often needed to ensure validity of the remote measurements. However, in an era when pandemics can usurp everyday life, field investigations can be halted without any warning. Moreover, glaciers and glacial systems are excellent indicators of climate change, but field investigations in regions such as the Himalayas and the High Arctic are expensive and difficult. Therefore, the necessity for improving reliability of satellite observations of glaciers is rising. My research is focused on enhancing the quality of extractable information from satellite images. In this effort, I have tried to answer some questions: Can the effects of the atmosphere that induce changes in satellite images be reduced? If so, which method is applicable and how does it compare to others? Enhancing the sharpness of an image may appear to improve visibility, however, does this translate to improving the final data products generated? What algorithm can be used to make such enhancements? Are there any other methods? And most importantly, what is the best method for extracting surface information of glaciers from satellite images? How would machine learning and automated methods work? What results would innovative methods produce? Are they comparable to field observations? Are they reliable enough to ensure other researchers can use my results and determine the direction of their own work? If you wish to know the answers, check out my publications below and reach out to me if you are interested in this research.
1. Jawak, S.D., Wankhede, S.F., Luis, A.J., Balakrishna, K. (2022). Effect of Image-Processing Routines on Geographic Object-Based Image Analysis for Mapping Glacier Surface Facies from Svalbard and the Himalayas. Remote Sensing, 14, 4403. https://doi.org/10.3390/rs14174403 (Impact Factor = 5.349)
2. Jawak, S.D., Wankhede, S.F., Luis, A.J., and Balakrishna, K. (2022). Impact of Image-Processing Routines on Mapping Glacier Surface Facies from Svalbard, and the Himalayas Using Pixel-Based Methods, Remote Sensing, 14, 1414, doi: https://doi.org/10.3390/rs14061414 (Impact Factor = 5.349)