Spatial Evaluation of Urban Green Space-Population Relationship Using Sentinel-2 Satellite Data and Object-Based Image Analysis: A Case Study Antalya

Abstract

The relationship between urban green space (UGS) and population is essential for the quality of life in cities. In this study, a method is proposed to determine the relationship between UGS and population in Antalya, Türkiye, and to reveal the change in the short-term, using Sentinel-2 satellite data and object-based image analysis (OBIA). In the study, two different dated Sentinel-2 satellite data were used as the basic data set to analyze the vegetation. The Normalized Difference Vegetation Index (NDVI) was calculated for the threshold value and UGSs were analyzed according to different categories. Then, the Urban Green Space Index (UGSI) was calculated to determine the amount of green space and Per Capita Green Space (PCGS) was also calculated for this purpose. The OBIA general accuracy values of the proposed method are 93% and 94% for 2017 and 2023, respectively. The results showed that PCGS across the study area decreased by 7.33 m² in a short time. It is evaluated that the method proposed in this study, which reveals the short-term change in UGS and PCGS more quickly and at lower cost, can be used effectively in sustainable city management.

Keywords

• Landscape
• NDVI
• OBIA
• PCGS
• Planning
• Remote sensing and GIS

Sentinel-2 Uydu Verileri ve Nesne Tabanlı Görüntü Analizi Kullanarak Kentsel Yeşil Alan-Nüfus İlişkisinin Mekansal Değerlendirilmesi: Antalya Örneği

Abstract

Kentsel yeşil alan (KYA) ile nüfus arasındaki ilişki, kentlerdeki yaşam kalitesi için önemlidir. Bu çalışmada, Türkiye, Antalya'da KYA ile nüfus arasındaki ilişkiyi belirlemek ve kısa dönemdeki değişimi ortaya koymak için Sentinel-2 uydu verileri ve nesne tabanlı görüntü analizi (OBIA) kullanılarak bir yöntem önerilmiştir. Çalışmada bitki örtüsünü analiz etmek için iki farklı tarihli Sentinel-2 uydu görüntüsü temel veri seti olarak kullanılmıştır. Eşik değeri için Normalize Edilmiş Fark Bitki Örtüsü İndeksi (NDVI) hesaplanmış ve KYA’lar farklı kategorilere göre analiz edilmiştir. Ardından, yeşil alan miktarını belirlemek için Kentsel Yeşil Alan İndeksi (KYAI) ve yeşil alanı belirlemek için Kişi Başına Yeşil Alan (KBYA) hesaplanmıştır. Önerilen yöntemin OBIA genel doğruluk değerleri 2017 ve 2023 yılları için sırasıyla %93 ve %94'tür. Sonuçlar, çalışma alanı genelinde PCGS’nin kısa vadede 7.33 m² azaldığını göstermiştir. KYA ve KBYA’da kısa vadeli değişimi daha hızlı ve daha düşük maliyetle ortaya koyan bu çalışmada önerilen yöntemin sürdürülebilir kent yönetiminde etkin bir şekilde kullanılabileceği değerlendirilmektedir.

Keywords

• Peyzaj
• NDVI
• OBIA
• KBYA
• Planlama
• Uzaktan algılama ve CBS

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