TY - JOUR T1 - Assessing Boundary Shifts at Gölcük Lake (Kütahya) with Google Earth Images TT - Google Earth Görüntüleri ile Gölcük Gölü (Kütahya) Sınır Değişimlerinin Değerlendirilmesi AU - Zengin, Enes AU - Acar, Recep Uğur AU - Öngen, Ali Samet PY - 2025 DA - August Y2 - 2025 DO - 10.35414/akufemubid.1579340 JF - Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi PB - Afyon Kocatepe Üniversitesi WT - DergiPark SN - 2149-3367 SP - 946 EP - 955 VL - 25 IS - 4 LA - en AB - Climate change is one of the most pressing issues facing the world today, with far-reaching impacts on ecosystems, human health, and global economies. It is characterized by significant alterations in temperature, precipitation patterns, and the frequency of extreme weather events, largely driven by human activities such as deforestation, industrial emissions, and the intense use of fossil fuels. United Nations has introduced a collective approach through the Sustainable Development Goals (SDGs), a set of 17 global goals adopted in 2015 as part of the 2030 Agenda for Sustainable Development. For this purpose, the boundary shifts of Gölcük lake in Simav, Kütahya, Türkiye, were examined using high-resolution Google Earth images from 2013 and 2023. Supervised classification techniques in ArcGIS Pro were applied to analyze changes in the lake's area over a decade marked by significant climate variability. The use of spatial data and geographic information system (GIS) methods allowed for precise measurement and visualization of these changes, proving highly useful for assessing the extent and impact of lake shrinkage. The findings reveal a 22.7% reduction in lake area, equating to approximately 32,279 m², indicating a notable shrinkage likely influenced by environmental factors. Temperature and precipitation data, obtained from the Ministry of Environment, Urbanization and Climate and the Turkish State Meteorological Service, were also assessed. The data showed an increase in average temperature from 11.5°C to 13°C and a slight decrease in precipitation over the period, suggesting potential contributions from climate change to the lake's shrinkage. These results underscore the importance of ongoing monitoring and sustainable management to mitigate the adverse impacts of climate change on freshwater resources. KW - Boundary shift KW - climate change KW - Gölcük lake KW - Kütahya KW - Geographic information system N2 - İklim değişikliği, bugün dünyanın karşı karşıya olduğu en acil sorunlardan biri olup, ekosistemler, insan sağlığı ve küresel ekonomiler üzerinde geniş kapsamlı etkiler yaratmaktadır. Bu durum, büyük ölçüde ormansızlaşma, sanayi kaynaklı emisyonlar ve fosil yakıtların yoğun kullanımı gibi insan faaliyetlerinin neden olduğu, sıcaklık, yağış düzenleri ve aşırı hava olaylarının sıklığında önemli değişimlerle tanımlanmaktadır. Birleşmiş Milletler, 2030 Sürdürülebilir Kalkınma Gündemi kapsamında 2015 yılında kabul edilen 17 küresel hedeften oluşan Sürdürülebilir Kalkınma Amaçları (SKA) ile kolektif bir yaklaşım sunmuştur. Bu amaç doğrultusunda, Türkiye'nin Kütahya iline bağlı Simav ilçesindeki Gölcük gölü’nün sınır değişimleri, 2013 ve 2023 yıllarına ait yüksek çözünürlüklü Google Earth görüntüleri kullanılarak incelenmiştir. Göl alanındaki değişimleri analiz etmek için ArcGIS Pro’da gözetimli sınıflandırma teknikleri uygulanmıştır. Mekansal veri ve coğrafi bilgi sistemleri (GIS) yöntemlerinin kullanımı, bu değişikliklerin yüksek hassasiyetle ölçümünü ve görselleştirilmesini sağlamış ve göl küçülmesinin boyutunu ve etkisini değerlendirmede son derece yararlı olmuştur. Elde edilen sonuçlar, göl alanında %22,7'lik bir azalma olduğunu ve yaklaşık 32.279 m²'lik önemli bir küçülmeyi göstermektedir; bu küçülmenin çevresel faktörlerden etkilenmiş olabileceği düşünülmektedir. Çevre, Şehircilik ve İklim Değişikliği Bakanlığı ile Meteoroloji Genel Müdürlüğü’nden elde edilen sıcaklık ve yağış verileri de değerlendirilmiştir. Veriler, ortalama sıcaklığın 2013’te 11,5°C’den 2023’te 13°C’ye yükseldiğini ve aynı dönemde yağış miktarında hafif bir azalma olduğunu göstermektedir; bu durum, iklim değişikliğinin gölün küçülmesine potansiyel bir katkısı olabileceğini düşündürmektedir. Bu sonuçlar, tatlı su kaynakları üzerindeki iklim değişikliğinin olumsuz etkilerini azaltmak için sürekli izleme ve sürdürülebilir yönetimin önemini vurgulamaktadır. CR - Acar, R.U. and Özkul, C., 2020. Investigation of heavy metal pollution in roadside soils and road dusts along the Kütahya–Eskişehir Highway. Arabian Journal of Geosciences, 13, 216. https://doi.org/10.1007/s12517-020-5206-2 CR - Acar, R.U. and Zengi̇n, E., 2023. Performance Assessment of Landsat 8 and Sentinel-2 Satellite Images for the Production of Time Series Land Use/Land Cover (LULC) Maps. Journal of Scientific Reports-A, 53 1–15. https://doi.org/10.59313/jsr-a.1213548 CR - Amani, M., Ghorbanian, A., Ahmadi, S.A., Kakooei, M., Moghimi, A., Mirmazloumi, S.M., Moghaddam, S.H.A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q. and Brisco, B., 2020. Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5326–5350. https://doi.org/10.1109/JSTARS.2020.3021052 CR - Bastawesy, M.A., Khalaf, F.I. and Arafat, S.M., 2008. The use of remote sensing and GIS for the estimation of water loss from Tushka lakes, southwestern desert, Egypt. Journal of African Earth Sciences, 52, 73–80. https://doi.org/10.1016/j.jafrearsci.2008.03.006 CR - Beck, M.W., Vondracek, B., Hatch, L.K. and Vinje, J., 2013. Semi-automated analysis of high-resolution aerial images to quantify docks in glacial lakes. ISPRS Journal of Photogrammetry and Remote Sensing, 81,60–69. https://doi.org/10.1016/J.ISPRSJPRS.2013.04.006 CR - Brosch, T., 2021. Affect and emotions as drivers of climate change perception and action: a review. Current Opinion in Behavioral Sciences, 42, 15–21. https://doi.org/10.1016/J.COBEHA.2021.02.001 CR - Buchsteiner, C., Baur, P.A. and Glatzel, S., 2023. Spatial Analysis of Intra-Annual Reed Ecosystem Dynamics at Lake Neusiedl Using RGB Drone Imagery and Deep Learning. Remote Sensing, 15, Page 3961 15, 3961. https://doi.org/10.3390/RS15163961 CR - Chaaban, F., El Khattabi, J. and Darwishe, H., 2022. Accuracy Assessment of ESA WorldCover 2020 and ESRI 2020 Land Cover Maps for a Region in Syria. Journal of Geovisualization and Spatial Analysis, 6, 1–23. https://doi.org/10.1007/s41651-022-00126-w CR - Dietz, T., Shwom, R.L., Whitley, C.T., 2024. Climate Change and Society. Annual Review of Sociology, 46, 15. https://doi.org/10.1146/annurev-soc-121919 CR - Dong, S., Chen, Z., Gao, B., Guo, H., Sun, D. and Pan, Y., 2020. Stratified even sampling method for accuracy assessment of land use/land cover classification: a case study of Beijing, China. International Journal of Remote Sensing, 41, 6427–6443. https://doi.org/10.1080/01431161.2020.1739349 CR - Emami, H. and, Zarei, A., 2021. Modelling lake water’s surface changes using environmental and remote sensing data: A case study of lake Urmia. Remote Sensing Applications, 23, 100594. https://doi.org/10.1016/J.RSASE.2021.100594 CR - Jeffry, L., Ong, M.Y., Nomanbhay, S., Mofijur, M., Mubashir, M. and Show, P.L., 2021. Greenhouse gases utilization: A review. Fuel, 301. https://doi.org/10.1016/j.fuel.2021.121017 CR - Jumaah, H.J., Ameen, M.H., Mohamed, G.H. and Ajaj, Q.M., 2022. Monitoring and evaluation Al-Razzaza lake changes in Iraq using GIS and remote sensing technology. The Egyptian Journal of Remote Sensing and Space Science, 25, 313–321. https://doi.org/10.1016/J.EJRS.2022.01.013 CR - Keshta, A.E., Riter, J.C.A., Shaltout, K.H., Baldwin, A.H., Kearney, M., El-Din, A.S. and Eid, E.M., 2022. Loss of Coastal Wetlands in Lake Burullus, Egypt: A GIS and Remote-Sensing Study. Sustainability (Switzerland) 14,4980. https://doi.org/10.3390/SU14094980/S1 CR - Kiage, L.M. and Douglas, P., 2020. Linkages between land cover change, lake shrinkage, and sublacustrine influence determined from remote sensing of select Rift Valley Lakes in Kenya. Science of the Total Environment, 709. https://doi.org/10.1016/j.scitotenv.2019.136022 CR - Kimijima, S., Sakakibara, M., Amin, A.K.M.A., Nagai, M. And Arifin, Y.I., 2020. Mechanism of the rapid shrinkage of limboto lake in Gorontalo, Indonesia. Sustainability (Switzerland), 12, 1–14. https://doi.org/10.3390/su12229598 CR - Li, K., Wang, J., Cheng, W., Wang, Y., Zhou, Y., Altansukh, O., 2022. Deep learning empowers the Google Earth Engine for automated water extraction in the Lake Baikal Basin. International Journal of Applied Earth Observation and Geoinformation,112, 102928. https://doi.org/10.1016/J.JAG.2022.102928 CR - Marsooli, R. and Lin, N., 2020. Impacts of climate change on hurricane flood hazards in Jamaica Bay, New York. Climate Change, 163, 2153–2171. https://doi.org/10.1007/s10584-020-02932-x CR - Noble, W.S., 2006. What is a support vector machine? Nature Biotechnology, 24, 1565–1567. https://doi.org/10.1038/nbt1206-1565 CR - Ocakoğlu, F., Kuzucuoğlu, C., Akbulut, A. and, Çilingiroğlu, Ç., 2022. Lake level changes and paleo-precipitation estimations based on colluvial stratigraphy of Holocene sediments in West Anatolia (Simav Graben). Palaeogeography, Palaeoclimatology, Palaeoecology, 597. https://doi.org/10.1016/j.palaeo.2022.111001 CR - Öngen, A.S. and Ergüler, Z.A., 2020. The effect of urban heat island on groundwater located in shallow aquifers of Kutahya city center and shallow geothermal energy potential of the region. Bulletin Of The Mineral Research and Exploration, 165, 1–24. https://doi.org/10.19111/bulletinofmre.820395 CR - Öngen, A.S. and Zengin, E., 2025. Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 14, 122–131. https://doi.org/10.28948/NGUMUH.1527341 CR - Pachauri, R.K., Meyer, L., Hallegatte France, S., Bank, W., Hegerl, G., Brinkman, S., van Kesteren, L., Leprince-Ringuet, N. and van Boxmeer, F., 2014. Climate Change 2014 Synthesis Report, Kristin Seyboth (USA). Gian-Kasper Plattner. Pang, Y., Yu, J., Xi, L., Ge, D., Zhou, P., Hou, C., He, P. and Zhao, L., 2024. Remote Sensing Extraction of Lakes on the Tibetan Plateau Based on the Google Earth Engine and Deep Learning. Remote Sensing, 16, 583. https://doi.org/10.3390/RS16030583 CR - Perrier, F., Le Mouël, J.-L., Poirier, J.-P. and Shnirman, M.G., 2005. Long-term climate change and surface versus underground temperature measurements in Paris. International Journal of Climatology, 25, 1619–1631. https://doi.org/10.1002/joc.1211 CR - Pisner, D.A. and Schnyer, D.M., 2020. Support vector machine. Machine Learning: Methods and Applications to Brain Disorders, 2020, 101–121. https://doi.org/10.1016/B978-0-12-815739-8.00006-7 CR - Pollack, H.N., Huang, S., Shen, P.-Y., 1998. Climate Change Record in Subsurface Temperatures: A Global Perspective. Science, 282, 279–281. https://doi.org/10.1126/science.282.5387.279 CR - Rwanga, S.S., Ndambuki, J.M., Rwanga, S.S., Ndambuki, J.M., 2017. Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS. International Journal of Geosciences, 8, 611–622. https://doi.org/10.4236/IJG.2017.84033 CR - Schölkopf, B., 1998. SVMs - A practical consequence of learning theory. IEEE Intelligent Systems and Their Applications, 13, 18–21. https://doi.org/10.1109/5254.708428 CR - Taconet, N., Méjean, A., Guivarch, C., 2020. Influence of climate change impacts and mitigation costs on inequality between countries. Climatic Change, 160, 15–34. https://doi.org/10.1007/s10584-019-02637-w CR - Yan, Y., Zhuang, Q., Zan, C., Ren, J., Yang, L., Wen, Y., Zeng, S., Zhang, Q., Kong, L., 2021. Using the Google Earth Engine to rapidly monitor impacts of geohazards on ecological quality in highly susceptible areas. Ecological Indicators ,132, 108258. https://doi.org/10.1016/J.ECOLIND.2021.108258 CR - Yang, M., Chen, L., Wang, J., Msigwa, G., Osman, A.I., Fawzy, S., Rooney, D.W., Yap, P.S., 2022. Circular economy strategies for combating climate change and other environmental issues. Environmental Chemistry Letters, 21, 55–80. https://doi.org/10.1007/S10311-022-01499-6 CR - Yang, X., Jiang, G.M., Luo, X., Zheng, Z., 2012. Preliminary mapping of high-resolution rural population distribution based on imagery from Google Earth: A case study in the Lake Tai basin, eastern China. Applied Geography, 32, 221–227. https://doi.org/10.1016/J.APGEOG.2011.05.008 CR - Zengin, E., 2023a. Inundation risk assessment of Eastern Mediterranean Coastal archaeological and historical sites of Türkiye and Greece. Environmental Monitoring Assessment, 195. https://doi.org/10.1007/s10661-023-11549-3 CR - Zengin, E., 2023b. A Combined Assessment of Sea Level Rise (SLR) Effect on Antalya Gulf (Türkiye) and Future Predictions on Land Loss. Journal of the Indian Society of Remote Sensing, 51, 1121-1133. https://doi.org/10.1007/s12524-023-01694-0 CR - Zengin, E., Erguler, Z.A., 2022. Experimental investigation of pore-fracture relationship on failure behaviour of porous rock materials. Bulletin of Engineering Geology and the Environment, 81, 351. https://doi.org/10.1007/s10064-022-02857-y CR - Zhao, Z., Islam, F., Waseem, L.A., Tariq, A., Nawaz, M., Islam, I.U., Bibi, T., Rehman, N.U., Ahmad, W., Aslam, R.W., Raza, D., Hatamleh, W.A., 2024. Comparison of Three Machine Learning Algorithms Using Google Earth Engine for Land Use Land Cover Classification. Rangeland Ecology & Management, 92, 129–137. https://doi.org/10.1016/J.RAMA.2023.10.007 UR - https://doi.org/10.35414/akufemubid.1579340 L1 - https://dergipark.org.tr/tr/download/article-file/4339814 ER -