Iranian Wetland Hydroperiod Change Detection Using an Unsupervised Method on 20 Years of Landsat Data Within the Google Earth Engine

Wetlands provide different environmental services and contribute to global biodiversity and climate mitigation. However, these priceless environments have been damaged by direct and indirect interference of human activities. Monitoring wetland's hydroperiod over large study areas became feasible only by recent advances in cloud computing platforms and free archive of Landsat time-series. We used the Dynamic Surface Water Extent algorithm for the unsupervised classification of time-series images. This unsupervised algorithm showed 86.7% overall accuracy for 2020 results. Then hydroperiod maps were produced based on the water occurrence of each pixel, and a differencing change detection method was used to produce change maps.