Farklı Kaynaklı Uydu Görüntüleri Kullanarak Bakü (Azerbaycan) Kıyılarındaki Petrol Kirliliğinin Gözlenmesi

u çalışmada farklı kaynaklı (Sentinel-1, Sentinel-2 ve Landsat-8) uydu görüntüleri kullanılarak Azerbaycan’ın Bakü kıyılarındaki tabii ve insan kaynaklı sızıntılar incelenmiştir. Sentinel-1 Yapay Açıklıklı Radar (SAR) görüntüleri açık kaynaklı Sentinel Uygulama Platformu’nun SNAP 6.0 yazılımı kullanılarak işlenmiş ve değişik tarihli petrol kirliliği olan alanlar tespit edilmiştir. Bu sızıntılardan en büyüğü 465 kilometrekare alan kaplayan 19 Ocak 2018 tarihli görüntüdür. Sentinel-2 görüntüsü de SNAP yazılımı kullanılarak işlenmiş, obje temelli analiz (OBIA) uygulanarak kirli alanlar tespit edilmiştir. Landsat-8 uydusu ACOLITE yazılımı kullanılarak işlenmiş ancak istenen sonuçlara ulaşılamamıştır. Çalışma sonucunda farklı kanallı uydu temelli izlemenin, denizel ortamdaki petrol kirliliği ile ilgili bilginin toplanması, görüntülenmesi ve analizi için etkili bir yöntem olduğu ortaya çıkmıştır.

Anahtar Kelimeler:

Petrol Kirliliği, Uydu Görüntüsü, Zaman Serisi

Monitoring Oil Pollution of Caspian Sea Coastline of Bakü, Azerbaican by Using Multi-Sensor Based Approach

In this study Multi-Sensor (Sentinel-1, Sentinel-2 and Landsat-8) based approach is used to investigate natural seepage and manmade oil pollution in the Caspian Sea along the coast of Bakü, Azerbaijan. The processing of the satellite images was carried out using the sentinel application platform (SNAP, 6.0), which is an open source common architecture and oil pollution for different dates was determined. The largest oil seepage was detected on January 19, 2018 that covered almost 465 square km. Sentinel-2 image was also processed by SNAP 6.0 and by using object-based image analysis (OBIA) the polluted areas were determined. ACOLITE software was used for processing however did not provide expected output. As a result of this study, it was determined that multi-sensor based satellite monitoring is an efficient approach for the collection, visualization and analysis of information on oil pollution in the marine environment.

Keywords:

Oil Pollution, Satellite Image, Time-series,

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[1] Kostianoy, A.G., Lavrova, O. (2014) Conclusions. In: Oil pollution in the Baltic Sea. (Eds.) A.G. Kostianoy and O.Yu. Lavrova, Springer-Verlag, Berlin, Heidelberg, New York, V27, 249-263.
[2] Kostianoy, A., Litovchenko, K., Lavrova, O., Mityagina, M., Bocharova, T., Lebedev, S., Stanichny, S., Soloviev, D., Sirota, A., Pichuzhkina, O. (2006). Operational satellite monitoring of oil spill pollution in the Southeastern Baltic Sea: 18 months experience. Environmental Research, Engineering and Management, 4(38): 70-77.
[3] EMADI, S. Y., NEZHAD, H. (2011). Energy market for Caspian Sea oil and its supply. Scientific Journal of International Black Sea University. 5(2): 21-34, ISSN:1512-3731.
[4] Mityagina, M., Lavrova, O. (2016). Satellite survey of inner seas: Oil pollution in the Black and Caspian Seas. Remote Sensing, 8: 875-899.
[5] Jafari, N. (2010). Review of pollution sources and controls in Caspian Sea region. Journal of Ecology and the Natural Environment Vol. 2(2), pp.025-029.
[6] Espedal, H. A., 1998, Detection of oil spill and natural film in the marine environment by spaceborne synthetic aperture radar. PhD thesis, Department of Physics University of Bergen and Nansen Environment and Remote Sensing Center, Norway.
[7] EAS (2017) Copernicus Open Access Hub. https://scihub.copernicus.eu/dhus/#/home
[8] ESA SNAP (2017) Scientific Toolbox Exploitation Platform http://step.esa.int/ main/ download/
[9] Jun Zhao, Marouane Temimi, Hosni Ghedira, Chuanmin Hu. (2014). Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf. Optical Society of America Vol. 22, No. 11 | DOI:10.1364/OE.22.013755
[10] USGS (2017) EarthExplorer – Distributable Code https://earthexplorer.usgs.gov/distribution/download
[11] Kolokoussis, P., Karathanassi, V. (2018) Oil Spill Detection and Mapping Using Sentinel 2 Imagery. J. Mar. Sci. Eng. 2018, 6, 4;
[12] ACOLITE (2014) atmospheric correction software for Landsat-8 publicly released in 2014.http://odnature.naturalsciences.be/remsem/software-and-data/acolite
[13] Vanhellemont, Q., Ruddick, K. ACOLITE processing for Sentinel-2 and Landsat-8: atmospheric correction andaquatic applications. Extended abstract submitted for the 2016 Ocean Optics Conference, held in Victoria, BC, Canada
[14] Misra, A., Balaji, R. Simple. (2017). Approaches to Oil Spill Detection Using Sentinel Application Platform (SNAP)-Ocean Application Tools and Texture Analysis: A Comparative Study. J Indian Soc Remote Sens (December 2017) 45(6):1065–1075.
[15] Qianguo Xing, Lin Li, Mingjing Lou, Lei Bing, Ruxiang Zhao Zhenbo Li. (2015). Observation of Oil Spills through Landsat Thermal Infrared Imagery: A Case of Deepwater Horizon. Aquatic Procedia 3 (2015) 151 – 156. doi: 10.1016/ j.aqpro.2015.02.205
[16] Pak, A., Farajzadeh, M. (2007). Iran’s Integrated Coastal Management Plan: Persian Gulf, Oman Sea, amd southern Caspian coastlines. Ocean and Coastal Management, 50: 754-773.