Abstract
Sri Lanka is an important hub connecting Asia-Africa-Europe maritime routes. It receives abundant but uneven spatiotemporal distribution of rainfall and has evident seasonal water shortages. Monitoring water area changes in inland lakes and reservoirs plays an important role in guiding the development and utilisation of water resources. In this study, a rapid surface water extraction model based on the Google Earth Engine remote sensing cloud computing platform was constructed. By evaluating the optimal spectral water index method, the spatiotemporal variations of reservoirs and inland lakes in Sri Lanka were analysed. The results showed that Automated Water Extraction Index (AWEIsh) could accurately identify the water boundary with an overall accuracy of 99.14%, which was suitable for surface water extraction in Sri Lanka. The area of the Maduru Oya Reservoir showed an overall increasing trend based on small fluctuations from 1988 to 2018, and the monthly area of the reservoir fluctuated significantly in 2017. Thus, water resource management in the dry zone should focus more on seasonal regulation and control. From 1995 to 2015, the number and area of lakes and reservoirs in Sri Lanka increased to different degrees, mainly concentrated in arid provinces including Northern, North Central, and Western Provinces. Overall, the amount of surface water resources have increased.
Highlights
Sri Lanka is an important hub connecting Asia-Africa-Europe maritime routes
It is of great significance to study the spatiotemporal variation of inland lakes and reservoirs in Sri Lanka, which can provide a scientific basis for the protection, management, and planning of water resources
We analysed the spatiotemporal variation of inland water in Sri Lanka, which has not been studied extensively based on a remote sensing cloud computing platform and Landsat-5/8 images; a rapid extraction model of surface water was constructed, and the optimal spectral water index method was determined by a water extraction accuracy test, for obtaining the spatiotemporal variation analysis of typical reservoirs and inland lakes and reservoirs in Sri Lanka
Summary
Sri Lanka is an important hub connecting Asia-Africa-Europe maritime routes. It receives abundant but uneven spatiotemporal distribution of rainfall and has evident seasonal water shortages. A rapid surface water extraction model based on the Google Earth Engine remote sensing cloud computing platform was constructed. There are relatively few studies that have performed the complete process of water extraction utilizing remote sensing cloud computing, and the research on the spatiotemporal variation of inland water in Sri Lanka is still in the blank. We analysed the spatiotemporal variation of inland water in Sri Lanka, which has not been studied extensively based on a remote sensing cloud computing platform and Landsat-5/8 images; a rapid extraction model of surface water was constructed, and the optimal spectral water index method was determined by a water extraction accuracy test, for obtaining the spatiotemporal variation analysis of typical reservoirs and inland lakes and reservoirs in Sri Lanka
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