Intensity Estimation of Tropical Cyclones from Satellite Imagery Over North Indian Ocean

Tropical cyclones (TC) harm both people and property over coastal regions, so early estimation of the TC intensity can help reduce the damage. Intensity estimation of a tropical cyclone (TC) has always been challenging for meteorologists. Several studies regarding the estimation of TCs have been made in the past few decades. Still, developing a mechanism to identify more reliable methods to find TC intensity is a difficult task. It is also seen that most of the research works related to TC intensity estimation have been conducted over the Atlantic and Pacific Oceans, and very few have been done on the North Indian Ocean (NIO). Hence, the TC intensity estimation over NIO becomes challenging due to the need for more references. This paper will demonstrate the research done in the past few decades and ongoing progress in the same field, including many remaining problems. TC intensity estimation using feature extraction of satellite images and machine learning algorithms is specially addressed in this study. Many researchers have confirmed that artificial intelligence has the potential to offer a fresh approach to the problems associated with estimating the intensity of tropical cyclones, whether through the use of purely data-driven models or models based on image processing. This review introduces the progress in TC intensity estimation by providing brief description of the challenges in TC intensity assessment and development in recent years.