Lightning detection sensor installed at University in Vadodara after MoU with ISRO

Vadodara: A lightning detection sensor (LDS) installed at the Navrachana University in Vadodara can detect lightning incidences in 300 km radius with over 98% accuracy. This helps in study the vulnerable locations and takes remedial steps to minimize the damage. These are the words of Dr. Pallavi Ghalsasi a faculty of School of Engineering and Technology from the university and under her mentorship the students made a predictive model to anticipate the incidence of lightening.

Navrachana University has an MoU with National Remote Sensing Center (NRSC), ISRO Hyderabad. Through the MoU, the lightning detection sensor (LDS) is installed at the Navrachana University to detect lightning incidences in 300 km radius with over 98% accuracy.

Dr Pallavi said, NRSC has a wide network of such sensors in India and uses time of arrival algorithm (TOA) to confirm the geographical coordinates of the lightning occurrences. The present study has been carried out as part of KHOJ Winter School 2022 where students from different disciplines such as Data Science, Computer Science and Engineering and Mechanical Engineering became part of the project. The objective of the project was to locate vulnerable locations and study the possible parameters responsible for lightning in those locations. If any trend is found, the results can be communicated to the concerned authorities to undertake necessary steps to mitigate similar situation in future.

Gujarat has a history of lightening incidents and according to Dr. Pallavi such lightning occurrences data across Gujarat, the students have been able to map the vulnerable locations and their shift within Gujarat State with time. The mapping helped to understand role of possible parameters like elevation, land cover, wind and temperature behind lightning. From the visualizations of the maps, built area was also seen to become prone to attract lightning which requires further study.

She also added that the students have further worked out a predictive model that does classify 83% of the total lightning instances correctly with a limitation based on data availability for short time duration. To refine the model even further, we would require lightning data for a longer duration along with accurate weather and geographical data for the same. It would be also interesting to see correlation with soil composition, long wavelength radiation, aerosol concentration, population and carbon monoxide emissions.

Dr Pallavi mentioned, in our research we found that 33% of the damage is due to lightening. The vulnerable locations will help in taking remedial steps like putting lightening arresters, early warning to minimize the damage. The surprise in the study was lightening on built up area which spread the area of study. She will be studying on generating renewable energy from lightening and learn about the patterns. Also the Fulgurite tubular structure soil formation on the area of lightening is her area of research.