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Journals / Peyzaj Araştırmaları ve Uygulamaları Dergisi / 2026 / Cilt: 8 Sayı: 1

DETERMINATION OF URBAN GREEN SPACES USING NDVI-BASED REMOTE SENSING: THE CASE OF SERIK CITY CENTER

NDVI TABANLI UZAKTAN ALGILAMA İLE KENTSEL YEŞİL ALANLARIN BELİRLENMESİ: SERİK KENT MERKEZİ ÖRNEĞİ

Emine Kahraman(AKDENİZ ÜNİVERSİTESİ)0000-0001-8738-8017
Nihat Karakuş(AKDENİZ ÜNİVERSİTESİ)0000-0002-6924-1879
Pages
76–89
Publication Date
2026-06-30
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AI Summary & Key Takeaways

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

The findings revealed that green spaces in Serik city center increase from the urban core towards the periphery, while central neighborhoods exhibit lower levels of green space compared to other areas.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aimed to identify and classify urban green spaces in the city center of Serik through the use of satellite imagery.
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Key Findings & Data:For this purpose, an open-access Sentinel-2 satellite image dated June 24, 2025, was obtained.
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Conclusion & Impact:The findings revealed that green spaces in Serik city center increase from the urban core towards the periphery, while central neighborhoods exhibit lower levels of green space compared to other areas.
🔬Design:Araştırma Makalesi
📍Scope:2025 Verileri
⚙️Variables:Kentsel peyzaj · Yeşil alanlar · Sentinel-2

Abstract

This study aimed to identify and classify urban green spaces in the city center of Serik through the use of satellite imagery. For this purpose, an open-access Sentinel-2 satellite image dated June 24, 2025, was obtained. The presence of urban green spaces was determined using the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 data. NDVI data was classified based on threshold values established in the literature, and urban green spaces were evaluated according to vegetation density levels. The findings revealed that green spaces in Serik city center increase from the urban core towards the periphery, while central neighborhoods exhibit lower levels of green space compared to other areas. In addition, it was determined that green areas with dense vegetation are limited and fragmented, whereas areas with low vegetation density are more widespread and exhibit a more continuous structure. Consequently, the study demonstrates that NDVI-based remote sensing methods constitute a reliable, applicable, and reproducible tool for the identification and monitoring of urban green spaces. The spatial resolution provided by Sentinel-2 data offers data-driven contributions to landscape planning and management processes at the neighborhood scale.

Özet

Çalışmada, Serik kent merkezinde kentsel yeşil alanların uydu görüntüleri aracılığıyla belirlenmesi ve sınıflandırılması amaçlanmıştır. Bu amaç doğrultusunda, açık erişimli 24 Haziran 2025 tarihli Sentinel-2 uydu görüntüsü temin edilmiştir. Sentinel-2 uydu verilerinden türetilen Normalize Edilmiş Fark Bitki Örtüsü İndeksi (NDVI) ile kentsel yeşil alan varlığı ortaya konulmuştur. Literatüre dayalı eşik değerleri kullanılarak NDVI verileri sınıflandırılmış ve kentsel yeşil alanlar bitki örtüsü yoğunluklarına göre değerlendirilmiştir. Bulgular, Serik kent merkezinde yeşil alanların merkezden çeperlere doğru arttığını, merkezi mahallelerde ise yeşil alanların diğer mahallere kıyasla daha düşük düzeyde olduğunu ortaya koymuştur. Ayrıca, yoğun bitki örtüsüne sahip yeşil alanların sınırlı ve parçalı olduğu, buna karşılık düşük yoğunluklu bitki örtüsünün daha yaygın ve süreklilik gösteren bir yapıda olduğu belirlenmiştir. Sonuç olarak, çalışma NDVI temelli uzaktan algılama yöntemlerinin kentsel yeşil alanların belirlenmesi ve izlenmesinde güvenilir, uygulanabilir ve tekrarlanabilir bir araç olduğunu ortaya koymaktadır. Sentinel-2 verilerinin sunduğu mekânsal çözünürlük, mahalle ölçeğinde peyzaj planlama ve yönetim süreçlerine veri temelli katkı sağlamaktadır.

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Cite This Article

Kahraman, E., Karakuş, N. (2026). DETERMINATION OF URBAN GREEN SPACES USING NDVI-BASED REMOTE SENSING: THE CASE OF SERIK CITY CENTER. Peyzaj Araştırmaları ve Uygulamaları Dergisi, Cilt: 8 Sayı: 1, 76–89. https://doi.org/10.56629/paud.1946094

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