Monitoring and analyzing the seasonal wetland inundation dynamics in the Everglades from 2002 to 2021 using Google Earth Engine

Keywords: seasonal inundation, spatiotemporal dynamics, Everglades,GEE
Abstract Type: Paper Abstract

Abstract

Inundation dynamics coupled with seasonal information is critical to study the wetland envi-ronment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. This study has its first time deploying an automated thresholding method, to quantify and compare the annual inundation characteristics in dry and wet seasons in the Everglades, using Landsat imagery in Google Earth Engine (GEE). This re-search presents the long-term time series maps from 2002 to 2021, with a comprehensive spatio-temporal depiction of inundation. In this paper, we have abridged the research gap of space-time analysis for multi-season inundation dynamics, which is a timely need for the Everglades wet-land. With GIS-based framework, we integrated statistical models, such as Mann-Kendall and Sen’s Slope tests to track the evolutionary trend of seasonal inundation dynamics. The spatio-temporal analyses highlight the significant differences in wet and dry seasons through time and space. The stationary or permanent inundation is more likely to be distributed along the coastal regions (Gulf of Mexico and Florida Bay) of the Everglades, warning a concern of vulnerability to sea level rise.