Spatial temporal analysis of the mangrove forest using the google earth engine cloud computing platform for Pichavaram, South East Coast of India

Abstract

Abstract Coastal mangrove wetlands are constantly under pressure from increasing populations, rising sea levels, and other climate change impacts. Globally, mangrove cover has decreased by about 5,245 sq. km since 1996. However, quantifying mangroves is challenging due to the difficult terrain, and it can be time-consuming and costly. Fortunately, recent advances in remote sensing technology and machine learning algorithms enable managers to quickly and accurately quantify mangroves.The objective of this study is to use the Google Earth Engine (GEE) cloud computing facility and five decades of Landsat images to quantify mangroves. This study utilized the extensive Landsat archive images available through cloud computing facilities. The random forest classifier was used to classify satellite images for better accuracy. The study reveals that mangroves in Pichavaram Reserve Forest have increased by 104% from 1977 to 2021. It demonstrates that the massive dataset was processed quickly, efficiently, and cost-effectively on the GEE cloud platform without the need for sophisticated software or hardware