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Journals / International Advanced Researches and Engineering Journal / 2026 / Volume: 10 Issue: 1

Monitoring spatio‑temporal changes in Arslanköy Pond in Google Earth Engine

Aydın Alptekin(Mersin University)0000-0002-5605-0758
Pages
—
Publication Date
2026-04-20
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The development of a water management plan is recommended to ensure the future sustainability of the pond.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the effects of land surface temperature (LST) and precipitation variations on the surface area of the Arslanköy Pond in Mersin were analyzed using the Google Earth Engine (GEE) platform between 2022 and 2025.
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Key Findings & Data:Variations in the pond’s surface area were analyzed via Sentinel-2 images; concurrently, changes in LST around the pond were assessed through the combined use of Landsat-8 and Landsat-9 imagery.
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Conclusion & Impact:The development of a water management plan is recommended to ensure the future sustainability of the pond.
🔬Design:Modeling & Simulation
📍Scope:2022 Verileri
⚙️Variables:GEE · LST · NDWI

Abstract

In this study, the effects of land surface temperature (LST) and precipitation variations on the surface area of the Arslanköy Pond in Mersin were analyzed using the Google Earth Engine (GEE) platform between 2022 and 2025. Variations in the pond’s surface area were analyzed via Sentinel-2 images; concurrently, changes in LST around the pond were assessed through the combined use of Landsat-8 and Landsat-9 imagery. Monthly precipitation data were determined using the “Global Precipitation Measurement (GPM) Release 07” dataset. In the last two years, the pond area exhibited an upward trend during January-June, whereas it remained constant at 63765 m2 during the July–December period. The highest LST was observed in August (38.1°C), while the lowest was recorded in January (4.3°C). The maximum and minimum average precipitation rates were observed in December (183.7 mm/hour) and August (9.0 mm/hour), respectively. The growth of the pond's surface area results from the melting of mountain snow and the efficient use of water resources for agricultural purposes by the local residents. The LST has been increasing annually, and a significant decline in annual precipitation was recorded in 2025. This situation poses a threat to the local ecosystem. The use of the GEE cloud computing platform facilitated the rapid modeling of the pond due to its practical computational capabilities. The pond is influenced by the effects of climate change. The development of a water management plan is recommended to ensure the future sustainability of the pond.

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Cite This Article

Alptekin, A. (2026). Monitoring spatio‑temporal changes in Arslanköy Pond in Google Earth Engine. International Advanced Researches and Engineering Journal, Volume: 10 Issue: 1. https://doi.org/10.35860/iarej.1855888

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