Publications

Jishad, M; Agarwal, N (2022). Thermal Front Detection Using Satellite-Derived Sea Surface Temperature in the Northern Indian Ocean: Evaluation of Gradient-Based and Histogram-Based Methods. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 50(7), 1291-1299.

Abstract
Two different methods of detecting oceanic thermal fronts using satellite-derived high-resolution sea surface temperature (SST) data are evaluated in this study. High-resolution SST observations from INSAT, MODIS and the group of high-resolution SST (GHRSST) have been used to identify thermal fronts in the Northern Indian Ocean. The thermal fronts are identified using gradient-based and histogram-based techniques. Several sensitivity studies were conducted to determine various thresholds required to identify thermal fronts from both methods. It is found that the detected fronts using gradient-based method are noisy and more in number as compared to histogram-based edge detection technique. The edge detection method can detect prominent fronts with fewer false alarms. Front detection techniques were also applied on sub-daily SST images obtained from geostationary satellite, INSAT-3D. Winter time fronts were realistically detected by using both algorithms. Buoy observations confirmed the presence of detected fronts in the satellite images. Application of the two techniques of front detection on SST images during cyclone shows that the histogram-based method successfully detects thermal fronts associated with cooling. The gradient-based method missed most of the thermal fronts during the cyclone, mainly due to diffused gradients captured in the satellite based merged SST under cloudy conditions.

DOI:
10.1007/s12524-022-01527-6

ISSN:
0974-3006