Google Earth Engine and Sentinel 1/2 data-based forest degradation monitoring of Sundarban Biosphere Reserve

Abstract

Tropical cyclone was effect through biodiversity, environment-nature circumstances, mangrove deforestation; flood inundation and high salinity at worldwide landscape and regularly in coastal ecosystem. Indian coastal areas recorded numerous tropical cyclones were impact through nature-environment effects, like Titli, Fani, Amphan, Bulbul, and Yass. This analysis was to recognize flood inundation and LULC alteration regions because of tropical cyclones. The cloud computing-based Google Earth Engine (GEE) stage is applied for growth of the flood inundation regions assessment in the affected Indian coastal area. The Random Forest (RF) approach is applied for vegetation change monitoring and Sentinel-1 Synthetic Aperture Rader (SAR) of the pre- and post-cyclone is applied for the monitoring and mapping of cyclonic result on landforms. In the outcome, vegetation loss is 238.34 km² (2015/2016), 181.79 km²(2016/2017), 443.00 km²(2017/2018), 22.64 km²(2018/2019), 34.39 km²(2019/2020), 118.51 km² (2020/2021) and 134.24 km² (2021/2022) because of those years happens numerous cyclones Fani (2019), Bulbul (2019), Amphan (2022) and Yass (2021). The NDVI of the examining years are 2016, 2017, 2018, 2019, 2020, 2021, 2022 highest values were 0.172, 0.726, 0.593, 0.831, 0.634, 0.568 and 0.387 respectively. South most parts of Ganga-delta were recording enormous alteration in certain periods; similarly, dynamics of mangrove forests are recorded. This analysis indicates that novel adaptation strategies, future disaster management and planning can help to reduce the mangrove deforestation. Mangrove plantation, river bank management and coastal planning is necessary to reducing the climate change effects. Those analyses can help to the future disaster management team, stakeholders and for awareness purpose.