Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 1012-2354 Erciyes Üniversitesi 10.65520/erciyesfen.1773264 Environmental Management (Other) Astronomical Sciences (Other) Çevre Yönetimi (Diğer) Astronomik Bilimler (Diğer) Projection of Light Pollution and Environmental Impact Estimation Based on Population and GDP: The Case of Türkiye Nüfus ve GSYİH'ye Dayalı Işık Kirliliğinin Projeksiyonu ve Çevresel Etki Tahmini: Türkiye Örneği https://orcid.org/0000-0002-0494-0310 Yılmaz Abdulvahap Erzincan Binali Yıldırım Üniversitesi, Sağlık Hizmetleri Meslek Yüksekokulu, Erzincan, Türkiye https://orcid.org/0000-0002-6110-8088 Elveren Müjgan ERZINCAN UNIVERSITY 03 27 2026 42 1 08 28 2025 01 11 2026 Copyright © 1985, Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 1985 Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi

Artificial Light at Night (ALAN) prediction can inform the development of strategies to minimise future light pollution and mitigate its adverse health, ecological, and environmental impacts. Population growth and GDP expansion significantly influence ALAN dynamics. This study quantifies changes in light pollution across Türkiye for 2012, 2017, and 2022, and predicts and maps potential changes in ALAN for 2027 and 2037 using the MOLUSCE plugin (MLP-ANN) in QGIS version 2.18, incorporating population and GDP as driving variables. The predicted and observed ALAN maps for 2022 show a satisfactory level of agreement, with an overall kappa coefficient of 0.63 and a general accuracy of 73.16%. The predicted and observed ALAN maps for 2022 exhibit an overall kappa coefficient of 0.63 and a general accuracy of 73.16%. Based on this validation, potential changes in ALAN according to Bortle classes were projected for 2027 and 2037. From 2022 onwards, ALAN intensity in the light suburban zone (20.1–19.1 mag/arcsec²) is projected to increase by 34,792.87 km², while the suburban–urban transition zone (19.1–18 mag/arcsec²) is expected to expand by 2,979.80 km² by 2037. The predicted spatial patterns provide critical insights into future urbanisation trends and light pollution dynamics. The contraction of rural areas and expansion of suburban zones pose notable risks to environmental sustainability. Gains and losses among Bortle classes indicate that ALAN dynamics can be managed through spatial planning and that ALAN projections can serve as early-warning and scenario-based decision-support tools. Integrating ALAN maps into Environmental Impact Assessment (EIA) processes and spatial planning policies can help preserve dark-sky areas and mitigate the impacts of light pollution.

ALAN (Gece Yapay Işık) tahmini, gelecekte ışık kirliliğini en aza indirmeye ve ışık kirliliğinin sağlık, ekolojik ve çevresel zararlarını azaltmaya yönelik stratejilerin geliştirilmesine katkıda bulunabilir. Nüfus ve GSYİH büyümesi, ALAN dinamikleri üzerinde önemli bir etkiye sahiptir. Bu çalışma, Türkiye’de ışık kirliliğindeki değişimleri 2012, 2017 ve 2022 yılları için ortaya koymayı; QGIS 2.18 yazılımında yer alan MOLUSCE eklentisi (MLP-ANN) ile nüfus ve GSYİH değişkenlerini kullanarak 2027 ve 2037 yıllarına yönelik olası ışık kirliliği değişimlerini tahmin etmeyi ve haritalamayı amaçlamaktadır. 2022 yılına ait tahmini ve gerçek ALAN haritaları, 0.63’lük toplam kappa katsayısı ve %73.16’lık genel doğruluk değerine sahiptir. Bu doğrulama sonuçlarının ardından, 2027 ve 2037 yılları için Bortle sınıflarına göre ALAN’daki olası değişimler tahmin edilmiştir. 2022'den itibaren, hafif banliyö bölgesindeki (20.1-19.1) ALAN yükü 34792.87 km² artacak ve banliyö/kentsel geçiş bölgesindeki (19.1-18) ALAN yükü 2037 yılına kadar 2979.80 km² artacaktır. Tahmin edilen mekânsal değişimler, kentleşme ve ışık kirliliği dinamiklerinin gelecekteki eğilimlerine ilişkin önemli ipuçları sunmaktadır. Kırsal alanların daralması ve banliyölerin genişlemesi, çevresel sürdürülebilirlik açısından dikkat çekici riskler oluşturmaktadır. Borthle sınıfları arasındaki kayıp ve kazanımlar, ALAN dinamiklerinin planlama yoluyla yönlendirilebilir olduğunu ve ALAN projeksiyonlarının erken uyarı ve senaryo temelli bir karar destek aracı olarak kullanılabileceğini göstermektedir. Bu kapsamda, ALAN haritalarının ÇED süreçleri ve mekânsal planlama politikalarına entegre edilmesi, karanlık gökyüzü alanlarının korunmasına ve ışık kirliliğinin olumsuz etkilerinin azaltılmasına katkı sağlayacaktır.

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