Investigation of Long and Short-Term Water Surface Area Changes in Coastal Ramsar Sites in Turkey with Google Earth Engine

Abstract

Deltas and lagoons, which contain many flora and fauna, have rich coastal ecological and biological environments, and are wetlands of vital importance for humans. In this study, the current problems in all coastal Ramsar sites in Turkey are summarized, and changes in water surface areas are investigated using Landsat and Sentinel 1/2 satellite images on the Google Earth Engine (GEE) cloud computing platform. Landsat TM and OLI images were used in the long-term analysis, and time series were created by taking annual and July to September averages between 1985 and 2020. In the short-term analysis, monthly averages were determined using Sentinel 2 images between 2016 and 2020. Sentinel-1 Synthetic Aperture Radar (SAR) images were used in the months when optical data were not suitable for use in monthly analysis. The Normalized Difference Water Index (NDWI) was used to extract water surface areas from the optical images. Afterwards, a thresholding process was used for both optical and radar images to determine the changes. The changes were analyzed together with the meteorological data and the information obtained from the management plans and related studies in the literature. Changes in the water surface areas of all coastal Ramsar sites in Turkey were determined from 1985 to 2020 at different rates. There was a decreasing trend in the Goksu and Kızılırmak Deltas, which also have inland wetlands. The decreasing rates from 1985 to 2020 were −24.52% and −2.86%, for annual average water surfaces for the Goksu and Kızılırmak Deltas, respectively, and −21.64% and −6.34% for the dry season averages, respectively. However, Akyatan Lagoon, which also has inland wetlands, showed an increasing trend. Observing the annual average surface area from 1985 to 2020, an increase of 438 ha was seen, corresponding to 7.65%. Every year, there was an increasing trend in the Gediz Delta and Yumurtalık Lagoons, that do not have inland wetlands. The increasing rates from 1985 to 2020 were 46.01% and 17.31% for the annual average surface area, for the Gediz Delta and Yumurtalık Lagoons, respectively, and 38.34% and 21.04% for the dry season average, respectively. The obtained results reveal the importance of using remote sensing methods in formulating strategies for the sustainable management of wetlands.

Spatio-Temporal Assessment of the Shrinking Lake Burdur, Turkey

“…In another study again from Asia, the surface water dynamics were estimated from February 2017 to November 2019 with Sentinel-2 and Landsat 8 images in the Yangtze River which is the longest river in Asia and the third in the world by Yang et al (2020). NDWI was most recently applied to Landsat and Sentinel images using the GEE platform to determine the water surface change between 1985 and 2020 at the 14 Ramsar Sites in Turkey (Dervisoglu, 2021;Dervisoglu, 2022). Moreover, Firatli et al (2022) investigated the changes over a 35-year period in Turkey's natural lakes with a surface area greater than 20 km 2 using NDWI in the GEE.…”

A Novel and Extensible Remote Sensing Collaboration Platform: Architecture Design and Prototype Implementation

“…Among them, in the field of Earth science, Li et al [5] used RS images and digital elevation models to discover the ancient lake and reconstruct the ancient climate in the Gobi. Dervisoglu [6] investigated the changes in the long-and short-term water surface area in Turkey. Wang et al [7] utilized satellite images to study the geological features and evolution of yardangs.…”

Mapping Dongting Lake Wetland Utilizing Time Series Similarity, Statistical Texture, and Superpixels With Sentinel-1 SAR Data

“…Temporal information is valuable to wetland classification because of the dynamic variability of wetlands. SAR time series data have proved to be an ideal data set for capturing wetland dynamics [15,27,28]. Calculating the maximum, minimum or standard deviation as temporal characteristics is a common strategy for multi-temporal SAR data processing [29][30][31].…”