Uzaktan Algılama Verileri ve Hücresel Otomata Yaklaşımı Kullanılarak 2000-2030 Dönemi Arazi Kullanımı ve Örtü Değişikliğinin İzlenmesi ve Tahmin Edilmesi

Abstract

Ormancılık, tarım, endüstriyel gelişim, şehir planlama, kırsal ve kentsel yönetim ve doğal kaynak yönetimi gibi çeşitli yönetim disiplinlerinde bilinçli karar alma için arazi kullanımı ve arazi örtüsü değişikliklerini anlamak ve karakterize etmek çok önemlidir. Bu çalışmada, hızlı bir sanayileşme süreci geçiren İzmit ili ve çevresindeki alanlardaki arazi kullanımı ve arazi örtüsü (AKAÖ) değişiklikleri, Uzaktan Algılama (UA) ve Yapay Sinir Ağı (YSA) metodolojileri kullanılarak 2000-2010 ve 2020 dönemleri için analiz edilmiştir. Ayrıca, 2030 yılı için bir AKAÖ projeksiyonu oluşturularak haritalanmıştır. Bu çalışma kapsamında, uydu görüntülerinden elde edilen yükseklik ve eğim değişkenleri kullanılarak dört kategorideki (orman, su, tarım ve yapılaşmış alanlar) arazi kullanım değişiklikleri simüle edilmiştir. Landsat 5 Tematik Haritalayıcı, Landsat 7 Geliştirilmiş Tematik Haritalayıcı Plus ve Landsat 8 Operasyonel Arazi Görüntüleyici uydu görüntüleri simülasyon için veri kaynağı olarak kullanılmıştır. Sınıflandırılmış görüntüler sonucunda Kappa değerleri 2000 yılı için %91, 2010 yılı için %87 ve 2020 yılı için %94 olarak hesaplanmıştır. 2030 simülasyonunun doğrulama değeri %89,2 olarak belirlenmiştir. 2030 simülasyonunun doğrulama değeri %89,2 olarak belirlenmiştir. Yapılan çalışma sonucunda sanayi kenti İzmit'te 2020-2030 yılları arasında orman alanlarının % 0,41, tarım alanlarının % 4,38, su alanlarının ise % 0,04 oranında azalacağı, yapılaşmış alanların ise % 37,06 oranında artacağı öngörülmektedir. Orman ve sucul ekosistemlerin kademeli olarak mekansal ve zamansal bir düşüş yaşadığı, tarım alanlarının ise daha hızlı bir azalma oranına maruz kaldığı ve bu eğilimin devam edeceği öngörülmektedir.

Keywords

• Uzaktan algılama
• Arazi örtüsü değişimi
• Yapay sinir ağları
• Landsat
• Modelleme

Project Number

Not applicable

Monitoring and Predicting of Land Use and Cover Change for the period 2000-2030 Using Remote Sensing Data and Cellular Automata Approach

Abstract

Understanding and characterize land use and land cover changes are crucial for informed decision-making in various management disciplines, including forestry, agriculture, industrial development, urban planning, rural and urban administration, and natural resource management. In this study, the land use and land cover (LULC) changes in İzmit province and its adjacent areas, undergoing rapid industrialization, were analyzed for the periods 2000-2010 and 2020 using Remote Sensing (RS) and Artificial Neural Network (ANN) methodologies. Additionally, a LULC projection for the year 2030 was generated and mapped. Within the scope of this study, land use changes across four categories (forest, water, agricultural, and built-up areas) were simulated utilizing elevation and slope variables derived from satellite imagery. Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager satellite imagery were employed as data sources for the simulation. As a result of classified images Kappa values were calculated as 91% for 2000, 87% for 2010 and 94% for 2020. The validation value of the 2030 simulation was determined as 89.2%. This study project that, forest areas will decrease by 0.41%, agricultural areas by 4.38%, and water areas by 0.04%, while built-up areas in the industrial city of İzmit are expected to increase by 37.06% from 2020 to 2030. It is projected that forest and aquatic ecosystems are experiencing gradual spatiotemporal decline, whereas agricultural lands are undergoing a more rapid rate of reduction, a trend anticipated to persist.

Keywords

• Remote sensing
• Land cover change
• Artificial neural network
• Landsat
• Modeling

Supporting Institution

No funding support was received for this study.

Project Number

Not applicable

Thanks

This research, titled “Modeling of Land Use and Land Cover Change with Remote Sensing Data and Artificial Neural Networks (İzmit Sample)” by Gülşen KEÇELİ, was carried out in the Department of Forest Engineering, Graduate School of Natural and Applied Sciences at Çankırı Karatekin University, is derived from master’s thesis completed in 2022.

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