Scholarlink

<p>As wetlands of international importance, Ramsar sites are critical for preserving global biodiversity, mitigating climate change, and sustaining essential ecosystem services. The degradation and loss of these habitats pose a significant threat to local environments and global ecological stability. Monitoring these areas is critical to inform conservation efforts and ensure sustainable water resource management. This study evaluates the performance of water extraction indices (NDVI, NDWI, MNDWI<sub>1</sub>, MNDWI<sub>2</sub>, AWEI<sub>nsh</sub>, AWEI<sub>sh</sub>, and WRI) in three important Ramsar wetlands (Lake Burdur, Lake Uluabat, and Lake Akyatan) located in different geographical regions of Türkiye. Using optical satellite imagery and the Google Earth Engine platform, the analysis aims to determine the most reliable indices for water surface detection using different statistical methods. In the first part of the study, the overall accuracy, kappa, and F1 score values were calculated by comparing the index results with high-resolution satellite images (Maxar Technologies). Then, statistical analyses using ROC curves and AUC values revealed significant accuracy variations between the water extraction indices applied in Uluabat, Burdur, and Akyatan lakes. The NDWI provided the highest overall accuracy in all lakes and stood out as the most effective index with 99.3%, especially in Lake Burdur. The other indices also showed high performance, but differences were observed according to environmental factors. In addition, ANOVA and Kruskal–Wallis H tests were used to evaluate the statistical significance between the indices, and significant differences were observed between the NDVI and AWEI<sub>nsh</sub> indices in Lake Akyatan. Long-term surface change analyses (1984–2023) revealed a 42.5% water surface loss in Lake Burdur, 21.2% in Lake Uluabat, and 4.7% in Lake Akyatan. These findings show that Ramsar sites in Türkiye are under serious threat in terms of water resources and emphasize that urgent measures should be taken for sustainable water management.</p> Graphical abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Performance Analysis of Water Extraction Indices with Geospatial and Statistical Techniques Using Google Earth Engine Platform: A Case Study of Ramsar Wetlands in Türkiye

  • 期刊论文

  • 发表日期：

    2025年4月8日

查看全文
  • Münevver Gizem Gümüş

摘要

As wetlands of international importance, Ramsar sites are critical for preserving global biodiversity, mitigating climate change, and sustaining essential ecosystem services. The degradation and loss of these habitats pose a significant threat to local environments and global ecological stability. Monitoring these areas is critical to inform conservation efforts and ensure sustainable water resource management. This study evaluates the performance of water extraction indices (NDVI, NDWI, MNDWI1, MNDWI2, AWEInsh, AWEIsh, and WRI) in three important Ramsar wetlands (Lake Burdur, Lake Uluabat, and Lake Akyatan) located in different geographical regions of Türkiye. Using optical satellite imagery and the Google Earth Engine platform, the analysis aims to determine the most reliable indices for water surface detection using different statistical methods. In the first part of the study, the overall accuracy, kappa, and F1 score values were calculated by comparing the index results with high-resolution satellite images (Maxar Technologies). Then, statistical analyses using ROC curves and AUC values revealed significant accuracy variations between the water extraction indices applied in Uluabat, Burdur, and Akyatan lakes. The NDWI provided the highest overall accuracy in all lakes and stood out as the most effective index with 99.3%, especially in Lake Burdur. The other indices also showed high performance, but differences were observed according to environmental factors. In addition, ANOVA and Kruskal–Wallis H tests were used to evaluate the statistical significance between the indices, and significant differences were observed between the NDVI and AWEInsh indices in Lake Akyatan. Long-term surface change analyses (1984–2023) revealed a 42.5% water surface loss in Lake Burdur, 21.2% in Lake Uluabat, and 4.7% in Lake Akyatan. These findings show that Ramsar sites in Türkiye are under serious threat in terms of water resources and emphasize that urgent measures should be taken for sustainable water management.

Graphical abstract