Producing land use maps with Google Earth Engine

Yıl 2021, , 38 - 47, 15.01.2021

Majid Aghlmand , Kaan Kalkan , Mehmet İnanç Onur , Gürkan Öztürk , Ecem Ulutak

https://doi.org/10.28948/ngumuh.795977

Cited By: 8

Öz

Land use are changing due to negative factors occurring in the ecosystem such as continuously developing cities, population growth, and climatic conditions. Data produced by remote sensing satellites play an essential role in ground-based research. Land cover maps are prepared using this data. Land cover maps help us better understand environmental processes such as water and biogeochemical cycles, energy changes, or biodiversity changes. This study was carried out to test the producibility of land use maps on the Google Earth Engine cloud platform. All images acquired between 01/01/2019 and 01/01/2020 from Landsat 8, Sentinel 1, and Sentinel 2 were used in this study. Then 5 different indices NDVI, NDWI, NDBI, Ui, and EVI were calculated, and 19 different combinations of data were considered. Then, for each of these combinations, classification was performed by the LibSVM method in 5 classes: Urban Roads, Water, Forest-Grove, Non-agricultural Lands, and Agricultural Lands. Overall Accuracy and Kappa Coefficient were calculated for each classification, and results were compared. The best classification with Overall Accuracy 96.62 and Kappa Coefficient 95.76 belongs to the data combination of Landsat 8, Sentinel-1(VV), Sentinel-2, NDVI, NDBI, UI and NDWI from Sentinel-2 and NDVI from Landsat 8.

Anahtar Kelimeler

Land use maps, Eskişehir, Google Earth Engine, Supervised classification, Remote sensing

Google Earth Engine ile arazi kullanımı haritalarının üretimi

Öz

Sürekli gelişen şehirler, nüfus artışı ve iklimsel koşullar gibi ekosistem de meydana gelen olumsuz etkenler ile arazi kullanımı değişime uğramaktadır. Uzaktan algılama uyduları tarafından üretilen veriler, yeryüzü araştırmalarda önemli bir rol oynamaktadır. Arazi örtüsü/kullanımı haritaları bu veriler kullanılarak hazırlanmaktadır. Arazi örtüsü haritaları, su ve biyokimyasal döngüler, enerji değişimleri veya biyolojik çeşitlilik değişiklikleri gibi çevresel süreçleri daha iyi anlamamıza yardımcı olur. Bu çalışma, Google Earth Engine bulut platformunda arazi kullanım haritalarının üretilebilirliğini test etmek amacıyla gerçekleştirilmiştir. Bu amaçla 01/01/2019 ve 01/01/2020 tarihleri arasında Landsat 8, Sentinel 1 ve Sentinel 2 uyduları tarafından çekilen tüm görüntüler kullanılmıştır. Daha sonra 5 farklı endeks; NDVI (Normalleştirilmiş fark bitki örtüsü endeksi), EVI(Gelişmiş Bitki Örtüsü Endeksi), NDWI (Normalleştirilmiş fark su endeksi), NDBI (Normalleştirilmiş fark oluşturma indeksi) ve UI (Kentsel indeks) hesaplanmış ve 19 farklı veri kombinasyonu dikkate alınmıştır. Daha sonra bu kombinasyonların her biri Destek Vektör Makineleri yöntemi(LibSVM) kullanılarak 5 sınıfa (Şehir alanı-yollar, su, ormanlık-koruluk, tarım dışı araziler ve tarım arazileri) ayrılmıştır. Her sınıflandırma için genel doğruluk ve Kappa Katsayısı hesaplanmış ve sonuçlar karşılaştırılmıştır. En iyi sınıflandırma, Landsat8, Sentinel-2, Sentinel-1 (VV), Landsat 8'den NDVI, Sentinel-2'den NDVI, NDBI, UI ve NDWI veri kombinasyonuna aittir. Bu kombinasyonda toplam doğruluk 96.62 ve kappa katsayısı 95.76 olmuştur.

Anahtar Kelimeler

Arazi kullanım haritaları, Eskişehir, Google Earth Engine, kontrollü sınıflandırma, uzaktan algılama

Kaynakça

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