## 2 Materials and Methods
### Satellite Data and Processing
#### 2.3.1 Available Dataset  
We used combinations of satellite imagery from four satellites constellations available and science-ready in the GEE platform, i.e., Landsat 7 (L7), Landsat 8 (L8), Sentinel 1 (S1), and Sentinel 2 (S2). S1 and S2 are satellite constellations developed by ESA (European Space Agency) along with other constellations such as Sentinel 3 and 5. S1 and S2 satellites hold the sensors that are suitable for the mangrove classification study. S1 satellite carries a dual-polarisation C-band Synthetic Aperture Radar (SAR) instrument [66; 67]. Each S1 scene in GEE has been pre-processed with the Sentinel-1 Toolbox and is science ready [68]. We employed Sentinel-1 SAR Ground Range Detected (GRD) products with 10 m spatial resolution with available dataset in GEE ('COPERNICUS/S1_GRD') from October 2014. The S2 satellite carries a Multispectral Instrument (MSI) with 13 spectral bands: 10 m resolution RGB and NIR, 20 m red edge and SWIR, and 60 m atmospheric band [69; 70]. The S2 MultiSpectral Instrument (MSI) Level-1C products were used with available dataset in GEE ('COPERNICUS/S2') from June 2015. L7 and L8 are satellite constellations developed by a joint program of the USGS and the NASA. Within the GEE platform, L7 scenes have been atmospherically corrected using LEDAPS [71; 72] and L8 using LasRC [73; 74] (USGS Landsat Surface Reflectance Tier 1). Clouds, shadow, water, and snow were masked with the CFMASK algorithm [71; 73; 75]. The L8 Surface Reflectance Tier 1 ('LANDSAT/LC08/C01/T1_SR') which is available from April 2013 onwards and Landsat 7 Surface Reflectance Tier 1 ('LANDSAT/LE07/C01/T1_SR') dataset available from January 1999 onward were employed in this study.  
Seasonal varying precipitation, flood control measures, and diversion operations are likely to influence the sediment yield. Mangrove flowering and seedling dispersal periods are also influenced by the season. By considering those conditions and dynamics on the delta, we proposed to map mangrove extent on a seasonal time scale. We mapped the mangrove extent that represents dry season (May and August) and wet season (November and February). A composite from one-month scenes of the particular month was created with the median value of the selected bands and indices for mangrove classification for optical sensor (S2, L7, L8). A mean function was applied for the satellite with SAR instrument (S1) [76; 77]. The median value was chosen because it is less affected by outlier values that arise, for instance, from pixels affected by clouds or snow during the masking procedures [75]. To optimise the dataset availability and account for mangrove-mudflat dynamics, we employed the combination of S1 and S2 during the period of November 2015 to November 2019. The combination of optical S1 and S2 SAR was reported to improve the classification accuracy [12; 76; 78; 79]. L8-based classification was for the period of August 2013 to August 2015, and L7-based classification was from dry season 2009 to dry season 2012. An exception has been made for L7-based classification. The L7 series of scenes has gaps due to Scan-Line Connector (SLC) failure or stripping problem [80]. Therefore, instead of using the one-month scenes we applied median values of full seasons (six months for each) during 2009-2012. Since in that period the diversion operation had just begun and the LUSI Island reclamation project had been conducted, we observed less mangrove succession in the delta. A presentation of the seasonal classification with a single map for the period of 2009-2012 is considered sufficient. All available datasets in a particular classification period were used to generate a cloud-free composite and improve the classification accuracy [76; 78].