Change (1990-2022) and modelling (2038-2054) of land use in Silivri

Emre Tunalı; Hamza Akengin

Makale detayları

Change (1990-2022) and modelling (2038-2054) of land use in Silivri

Yazarlar:

Emre Tunalı | Hamza Akengin

Yayıncı:

Marmara University

Ana Başlıklar:

Beşeri Coğrafya (Diğer) | Uzaktan Algılama

Dergi:

International Journal of Geography and Geography Education Issue 52, pp.71-95

Belge Tipi:

Makale

Yayın Tarihi:

5/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001318049

pISSN:

2630-6336

Anahtar kelimeler:

Özet:

 In this study, it was aimed to the detect the land use changes that occured in Silivri between 1990-2022 and to predict the directions and effects of the changes that may occur in the land by creating future models in the light of existing data. To identify the mentioned change, satellite images obtained from Landsat satellites were intially used, and the images were subjected to analysis through the ArcMap 10.5 program. The data obtained from the thematic maps as a result of the analysis were interpreted through tables and graphs. In the final phase of the study, model maps were created for the years 2038 and 2054 using Artificial Neural Networks ANN and Cellular Automata CA Markov Chain methods. The result obtained from the study indicate that the land classes have undergone important changes. While residental and industrial areas, which are considered as artificial surfaces, increased significantly between 1990 and 2022, there was a decrease in agricultural and pasture areas and forest areas. The findings acquired from models shows that the change will continue in the future. Accordingly, the area of artificial surfaces is expected to increase. However, it is foreseen that the area covered by agricultural, pasture lands and forest lands will continue to decrease.

 In this study, it was aimed to the detect the land use changes that occured in Silivri between 1990-2022 and to predict the directions and effects of the changes that may occur in the land by creating future models in the light of existing data. To identify the mentioned change, satellite images obtained from Landsat satellites were intially used, and the images were subjected to analysis through the ArcMap 10.5 program. The data obtained from the thematic maps as a result of the analysis were interpreted through tables and graphs. In the final phase of the study, model maps were created for the years 2038 and 2054 using Artificial Neural Networks ANN and Cellular Automata CA Markov Chain methods. The result obtained from the study indicate that the land classes have undergone important changes. While residental and industrial areas, which are considered as artificial surfaces, increased significantly between 1990 and 2022, there was a decrease in agricultural and pasture areas and forest areas. The findings acquired from models shows that the change will continue in the future. Accordingly, the area of artificial surfaces is expected to increase. However, it is foreseen that the area covered by agricultural, pasture lands and forest lands will continue to decrease.

 In this study, it was aimed to the detect the land use changes that occured in Silivri between 1990-2022 and to predict the directions and effects of the changes that may occur in the land by creating future models in the light of existing data. To identify the mentioned change, satellite images obtained from Landsat satellites were intially used, and the images were subjected to analysis through the ArcMap 10.5 program. The data obtained from the thematic maps as a result of the analysis were interpreted through tables and graphs. In the final phase of the study, model maps were created for the years 2038 and 2054 using Artificial Neural Networks ANN and Cellular Automata CA Markov Chain methods. The result obtained from the study indicate that the land classes have undergone important changes. While residental and industrial areas, which are considered as artificial surfaces, increased significantly between 1990 and 2022, there was a decrease in agricultural and pasture areas and forest areas. The findings acquired from models shows that the change will continue in the future. Accordingly, the area of artificial surfaces is expected to increase. However, it is foreseen that the area covered by agricultural, pasture lands and forest lands will continue to decrease.

 Bu çalışmada, Silivride 1990-2022 yılları arasında meydana gelen arazi kullanımı değişimlerini tespit etmek ve mevcut veriler ışığında geleceğe yönelik modeller oluşturarak arazide meydana gelebilecek değişimin yönlerini ve etkilerini öngörmek amaçlanmıştır. Söz konusu değişimi tespit etmek amacıyla öncelikle Landsat uydularından elde edilen uydu görüntüleri kullanılmış, görüntüler ArcMap 10.5 programı aracılığıyla analize tabi tutulmuştur. Analiz sonucu tematik haritalar üzerinden elde edilen veriler, tablo ve grafikler vasıtasıyla yorumlanmıştır. Çalışmanın son aşamasında, Yapay Sinir Ağları YSA ve Hücresel Otomat HO Markov Zincirleri yöntemleri kullanılarak 2038 ve 2054 yılları için model haritaları oluşturulmuştur. Çalışmadan elde edilen sonuçlar arazi sınıflarının büyük ölçüde değiştiğini göstermektedir. 1990-2022 yılları arasında yapay yüzeyler sınıfı içinde değerlendirilen konut ve sanayi alanları önemli ölçüde artış gösterirken, tarım ve mera alanları ile orman alanlarında azalış gerçekleşmiştir. Modelden elde edilen bulgular gelecekte de değişimin süreceğini göstermektedir. Buna göre yapay yüzeylerin alanının artması beklenmektedir. Ancak, tarım ve mera alanları ile orman arazilerinin kapladığı alanın azalmaya devam edeceği öngörülmektedir.

Makale detayları

Change (1990-2022) and modelling (2038-2054) of land use in Silivri

Yazarlar:

Emre Tunalı | Hamza Akengin

Yayıncı:

Marmara University

Ana Başlıklar:

Beşeri Coğrafya (Diğer) | Uzaktan Algılama

Dergi:

International Journal of Geography and Geography Education Issue 52, pp.71-95

Belge Tipi:

Makale

Yayın Tarihi:

5/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001318049

pISSN:

2630-6336

Silivri

Land Use

Land Use Modelling

Artificial Neural Network (ANN)

CA-MarkovSilivri

Arazi Kullanımı

Arazi Kullanımı Modellemesi

Yapay Sinir Ağları

HO-Markov

Sayı

Makale detayları

Yazarlar: Emre Tunalı | Hamza Akengin

Yayıncı: Marmara University

Ana Başlıklar: Beşeri Coğrafya (Diğer) | Uzaktan Algılama

Dergi: International Journal of Geography and Geography Education Issue 52, pp.71-95

Belge Tipi: Makale

Yayın Tarihi: 5/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001318049

pISSN: 2630-6336

Sayı

Yazarlar:

Emre Tunalı | Hamza Akengin

Yayıncı:

Marmara University

Ana Başlıklar:

Beşeri Coğrafya (Diğer) | Uzaktan Algılama

Dergi:

International Journal of Geography and Geography Education Issue 52, pp.71-95

Belge Tipi:

Makale

Yayın Tarihi:

5/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001318049

pISSN:

2630-6336