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Item Historical water body changes using spatio temporal indices - a case study of Dakshina Kannada(Elsevier Ltd, 2023) Shetty, S.T.; Kushwaha, A.; Shetty, A.The spatiotemporal shift of surface water affects the structure, performance, and development of the ecosystem in Dakshina Kannada as well as its agricultural, economic, and social development. In order to better recognize the long-standing variations in the surface water area in Dakshina Kannada, the study used all available Landsat images, the modified Normalized Difference Water Index (MNDWI), the Enhanced Vegetation Index (EVI), and the Normalized Difference Water Index (NDWI) to map the open-surface water from 2014 to 2020 in the Google Earth Engine (GEE) cloud platform. The study looked at precipitation, temperature, and irrigated land to see how weather variation and anthropological actions affect long-standing surface water changes. The following are the outcomes. (1) The Dakshina Kannada, the extreme, periodic, and yearly average water body area values have all decreased during the last 8 years. In the meantime, the number of extreme, periodic, and lasting waterbodies has been steadily increasing. (2) The maximum water body area influences the variance of surface water area in the Dakshina Kannada, whereas the number of minimum water bodies influences the variation of water body number. (3) The area and number of water bodies are statistically significantly improved by rainfall, which also significantly improves water body area and number. The city's water surface area has changed significantly during the last 8 years, according to this study. © 2023Item Mapping of Flood-Inundated Urban Regions Using Sentinel-1 SAR Imagery for the 2018 and 2019 Kerala Floods(Springer Science and Business Media Deutschland GmbH, 2023) Kulithalai Shiyam Sundar, K.S.S.; Kundapura, S.Floods are a common natural calamity causing an immense impact on the natural and human ecosystems around the world. A combination of unfavorable meteorological, hydrological, and physical conditions causes it. The study area is the Vembanad Lake System in Kerala, India comprising six watersheds: Periyar, Muvattupuzha, Meenachil, Manimala, Pamba, and Achenkovil that drains into the lake. The state faced severe flooding in 2018 and 2019 due to torrential rainfall. Thus, this study focuses on assessing flood inundation mapping utilizing Sentinel-1 SAR imagery in Google Earth Engine (GEE) for 2018 and 2019 since it simplifies and streamlines the complicated and time-consuming pre-processing of Sentinel-1 SAR images. These images are pre-processed, and the flooded areas are delineated. Change detection by image ratio method is utilized to identify the flood inundated and the most frequently flooded areas. The results show that 4% and 3.21% of the entire region were flooded in 2018 and 2019, respectively. In addition, 14.7 Km2 of the urban area flooded in 2018, whereas 7.26 Km2 of urban land flooded in the 2019 floods. Hence, these inundation maps can be utilized for risk assessment and primary preventive measures. It also serves as a tool to warn the residents in that region about the hazards and the possibility of inundations at the time of heavy downpours in the future. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.