EventsThe 7th International Electronic Conference on Water Sciences
Published
This submission belongs to the session C. Water Resources Policy, Governance and Socioeconomic Aspects of the event The 7th International Electronic Conference on Water Sciences
Published date
14 Mar, 2023
Academic Editor
author-avatarSlobodan Simonovic
Citation
Gordana Kaplan, Mervegul Aykanat Atay, Large-Scale Mapping of Inland Waters in Google Earth Engine using Remote Sensing, in Proceedings of The 7th International Electronic Conference on Water Sciences, 15 March–30 March 2023, MDPI: Basel, Switzerland, doi: 10.3390/ECWS-7-14171
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Large-Scale Mapping of Inland Waters in Google Earth Engine using Remote Sensing

Mervegul Aykanat Atay 1
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1. Eskisehir Technical University, Institute of Higher Education
2. Eskisehir Technical University, Institute of Earth and Space Sciences
Abstract

Water resources are becoming scarce due to climate change and anthropogenic activity, necessitating immediate action. The first step in conserving our water supplies is to manage them mindfully and sustainably. To achieve this, water sources must be monitored, mapped, and evaluated regularly. Updating national water maps using conventional methods can be a challenging task. Most of the obstacles have been addressed due to recent breakthroughs in the remote sensing field. In this study, we benefit from the remote sensing data integrated into Google Earth Engine (GEE) for developing an application for mapping Turkey's national inland water bodies. To achieve this, we explored the recently developed Multi-Band Water Index (MBWI) in GEE using Sentinel-2 satellite imagery and then applied it over the research area. The results showed that GEE is a promising application for dealing with large amounts of satellite data and can accurately extract water bodies on a national scale. The results might be helpful for various administrative applications that require up-to-date water information. The developed application can be used over different study areas and for spatiotemporal analysis.

Keywords
Remote sensing
water
google earth engine
sentinel-2
Manuscript
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