Sürdürülebilir Kalkınma Amaçları
Yazarlar
Yayınlar
- MakaleYalnız künye2026Scopus SJRQ2Multi-scale greening dynamics in Türkiye’s Ecoregions (2001–2024): the effects of elevation and land cover on NDVI change tendencies
Işık, Fatih; Eraslan, Selim
Understanding vegetation dynamics in terrestrial ecosystems is critical under the pressures of global climate change and anthropogenic activities. This study analyzes vegetation dynamics from 2001 to 2024 in Türkiye’s 13 biodiverse terrestrial ecoregions using a multi-scale approach, focusing not only on the main drivers, but also on the interactive and context-specific role of these factors. Using the Google Earth Engine (GEE) platform and MODIS Normalized Difference Vegetation Index (NDVI) data, integrated through a structured multi-scale framework, we applied statistical methods including the Mann–Kendall test, Kruskal–Wallis test, and LOESS curves optimized with leave-one-out cross-validation (LOOCV) to objectively model non-linear dynamics. The results revealed statistically significant positive NDVI change tendencies in all 13 terrestrial ecoregions (Mann–Kendall test, p < 0.05). Forest-dominated ecoregions exhibited the strongest greening, with Sen’s slope values reaching +0.0032 NDVI year⁻1 in the Euxine–Colchic Broadleaf Forests, whereas steppe ecosystems showed more moderate increases (e.g., Central Anatolian Steppe: + 0.0019 NDVI year⁻1). Across elevation gradients, the most consistent and strongest greening occurred at mid-elevations (500–1500 m; τ ≈ 0.40–0.65), while change tendencies weakened and became more heterogeneous at higher elevations. Land-cover-based analysis further showed that natural vegetation types exhibited the strongest nationwide tendencies (“Trees”: τ = 0.71; “Shrubland”: τ = 0.66), whereas anthropogenically influenced classes displayed weaker or regionally variable responses. Beyond documenting general greening patterns, the original contribution of this study lies in introducing a structured multi-scale framework that integrates long-term MODIS NDVI time series (2001–2024) with ecoregion, elevation, and land cover contexts. This approach enables the objective identification of ecosystem-specific and scale-dependent vegetation dynamics that cannot be captured by conventional single-scale or linear trend-based analyses commonly applied in previous studies in Türkiye.
AtıfWoS1OpenAlex1
İncele - MakaleAçık Erişim2020OPPORTUNITIES PROVIDED BY REMOTE SENSING DATA FOR WATERSHED MANAGEMENT: EXAMPLE OF KONYA CLOSED BASIN
Yagmur, Nur; Tanik, Aysegul; Tuzcu, Aylin; Musaoglu, Nebiye; Erten, Esra; Bilgilioglu, Baha
Remote sensing data provides great opportunities in various steps of watershed management like characterization of watersheds that bear dynamic structure with large land, monitoring the physical variations within the basin, and conducting various scenario analyses to detect the response of the basin. The high resolution capacity of today’s satellite images enables the production of land use/cover data of a basin in shorter period of time. In this study, it is aimed to demonstrate various aspects of remote sensing technology to be used in watershed management studies. For that purpose, MODIS, Landsat and Sentinel satellite data with different spatial resolutions were used to monitor the surface water bodies in Konya Closed Basin (KCB) of Turkey. In addition, high spatial Worldview-3 satellite data were used to extract detailed information about Akgol Wetland located in KCB. A methodology was developed on the utilization of remote sensing technology consisting of 3 main groups; field surveys, satellite images and ancillary data. In the study, 5 different spectral indices were applied to Sentinel 2 data to determine the areas of surface water bodies. Moreover, Support Vector Machine (SVM) method was applied to Worldview-3 satellite image to classify Akgol Wetland and its vicinity. The importance of establishing watershed information system together with a database reflecting the characteristics of watersheds was underlined. Various examples were given from KCB that is known as the largest closed basin of the country with a surface area of 5.426.480 ha. The basin owns 17 water bodies out of which 2 of them are RAMSAR sites. Within the scope of the study, information obtained from optical and synthetic aperture radar (SAR) satellite images in the basin were discussed. More accurate results were achieved by Sentinel 2 than MODIS and Landsat data. In addition, detailed information about the wetland were extracted by means of Worldview-3 data and water bodies were monitored in all weather conditions via Sentinel 1 SAR data.
AtıfScopus20WoS23OpenAlex22İncele