Estimation of Water Spread Area in Selected Tanks of Cuddalore District of Tamil Nadu Using Sentinel-1A SAR Data
Dharun Vembadi Manivannan, Jagadeeswaran R., S. Pazhanivelan, R. Kumaraperumal, M. Raju, R. Pangayar Selvi
International Journal of Environment and Climate Change · pp. 3130–3136 · Published 7 Aug 2023
10.9734/ijecc/2023/v13i92555Abstract
The most important aspect of water resource planning and management is mapping and regular monitoring of surface water bodies. Remote sensing has become most widely used method for measuring and monitoring of water body dynamics due its temporal and spatial availability of high-resolution data. A study was conducted to map and estimate the water spread area in the tanks of Kattumannarkoil block of Cuddalore district of Tamil Nadu using Sentinel-1A SAR satellite data. European Space Agency’s Sentinel-1A data provides high quality SAR data which is used widely for monitoring of crop and water resources. The acquisition and preprocessing of satellite data was done using Google Earth Engine. The obtained satellite image from Google Engine was processed using ArcGIS. The water spread area was derived from the processed data using thresholding approach. The back-scattering values generated through pre-processing ranges from -18.00 db to -28.12 db for August 2022 (Pre-rainy season), -15.85 to -26.96 for December 2022 (Post-rainy season) and -15.55 to -24.82 for April 2023(Summer time). The estimated water spread area in selected 12 Tanks were 37.191 ha, 58.34 ha and 59.971 ha on 19th August 2022, 17th December 2022 and 16th April 2023 respectively.
References (18)
- 1 The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features [DOI]
- 2 High-resolution mapping of global surface water and its long-term changes [DOI]
- 3 A survey of image classification methods and techniques for improving classification performance [DOI]
- 4 A fully automated TerraSAR-X based flood service [DOI]
- 5 An Automated Method for Extracting Rivers and Lakes from Landsat Imagery [DOI]
- 6 An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic [DOI]
- 7 Sen1Floods11: a georeferenced dataset to train and test deep learning flood algorithms for Sentinel-1 [DOI]
- 8 Automated Extraction of Surface Water Extent from Sentinel-1 Data [DOI]
- 9 High-Resolution 3-D Flood Information From Radar Imagery for Flood Hazard Management [DOI]
- 10 Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations [DOI]
- 11 Satellite-supported flood forecasting in river networks: A real case study [DOI]
- 12 Modified Grasshopper Algorithm-Based Multilevel Thresholding for Color Image Segmentation [DOI]
- 13 Multi-sensoral and automated derivation of inundated areas using TerraSAR-X and ENVISAT ASAR data [DOI]
- 14 Data Analytics for Rapid Mapping: Case Study of a Flooding Event in Germany and the Tsunami in Japan Using Very High Resolution SAR Images [DOI]
- 15 Water Balance in Irrigation Reservoirs Considering Flood Control and Irrigation Efficiency Variation [DOI]
- 16 Application of a Decision Tree Method with a Spatiotemporal Object Database for Pavement Maintenance and Management [DOI]
- 17 Radar Satellite Imagery and Automatic Detection of Water Bodies [DOI]
- 18 Assessing the Increase in Background Oil–Contamination Levels Along Alabama's Beaches Resulting From the Deepwater Horizon Oil Spill [DOI]
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