TIME SERIES ANALYSIS OF URBANISATION IMPACT ON THE TEMPERATURE VARIATIONS OFF MUMBAI COAST

This study explains the capabilities of C-band Synthetic Aperture Radar (SAR) system in detection of glacial deformation due to earthquakes. Due to the remote location of the Himalayan glaciers associated with harsh weather conditions and rugged topography, the method of differential interferometric SAR (DInSAR) can be very useful in studying the impact of earthquakes in the glaciated regions where field-based seismological study is extremely tough to execute.

Our analysis demonstrates the capability of machine learning models in estimating glacier mass balance in terms of performance metrics and dataset availability. Feature importance analysis suggests that ablation features are significant. This is in agreement with the predominantly negative mass balance observations. We show that ensemble tree models typically depict the best performance. However, neural network models are preferable for biased inputs and kernel-based models for smaller datasets.