İZMİR’İN YÜZEY SICAKLIĞININ HESAPLANMASI

Year 2019, Volume: 1 Issue: 2, 36 - 46, 30.12.2019

Hakan Oğuz , Neslihan Doygun , Şule Kısakürek , Mahire Özçalık

Abstract

Bilindiği gibi, Yer Yüzey Sıcaklığı (YYS) evapotranspirasyon tahmini, kentsel iklim, bitki örtüsü izleme ve iklim değişikliğinde rol oynayan temel parametrelerden biridir. Bu çalışmanın ana amacı, 23 Ağustos 2019 tarihli Landsat 8 uydu görüntüsünü kullanarak Türkiye’nin İzmir ili için YYS’nin konumsal dağılımının hesaplanmasıdır. Yeni nesil Landsat 8’in termal kızılötesi sensörü (TIRS) iki bant halinde dünya yüzey sıcaklığını ölçmektedir. Bu özel çalışmada, İzmir ili için YYS hesaplanması amacıyla en popüler yöntemlerden biri olan Radyasyon Transferi Denklemi (RTD) yöntemi kullanılmıştır. Bu çalışmanın sonucunda en yüksek sıcaklık 34 °C civarında ve çıplak alanlarda tespit edilmiş, en düşük sıcaklık ise 10 °C civarında İzmir Kuş Cenneti ve Tahtalı Barajı’nda bulunmuştur. Ayrıca ormanlık alanların sıcaklığının ise 17 °C ile 25 °C arasında ağaç yoğunluğuna göre değiştiği tespit edilmiştir.

Keywords

ArcGIS, Yayınırlık, CBS, Landsat 8, YYS, Model Builder

CALCULATING SURFACE TEMPERATURE OF IZMIR, TURKEY

Abstract

As well known, Land Surface Temperature (LST) is one of the essential parameters in evapotranspiration estimation, urban climate, vegetation monitoring and climate change. The main objective of this study was to retrieve spatial distribution of LST for the province of İzmir, Turkey using Landsat 8 satellite imagery which was acquired on August 23, 2019. The new generation of Landsat 8 has a new instrument called Thermal Infrared Sensor (TIRS) that captures the temperature of the earth's surface in two bands. In this particular study, one of the most popular methods, Radiative Transfer Equation (RTE) method, was employed. According to the results, the low temperatures were retrieved in İzmir Bird Paradise and Tahtali Dam around 10 °C while high temperatures were found in bare land with temperatures around 34 °C. It was also determined that temperatures in forest areas were ranging from 17 °C to 25 °C according to tree density.

Keywords

ArcGIS, Emissivity, GIS, LST, Model Builder, Landsat 8

References

• Barsi, J.A., Schott, J.R., Palluconi, F.D., Helder, D.L., Hook, S.J., Markham, B.L., Chander, G., & O’Donnell E.M. (2003). Landsat TM and ETM+ thermal band calibration. Canadian Journal of Remote Sensing, 29(2), 141–153.
• Cristóbal, J., Jiménez-Muñoz, J.C., Sobrino, J.A., Ninyerola, M., & Pons, X. (2009). Improvements in land surface temperature retrieval from the Landsat series thermal band using water vapor and air temperature. Journal of Geophysical Research, 114(D8), D08103.
• EOS (2019). Earth Observing System. Retrieved from https://eos.com/blog/band-combinations-for-landsat-8/
• Jiménez-Muñoz, J.C., & Sobrino J.A. (2008). Split-window coefficients for land surface temperature retrieval from low-resolution thermal infrared sensors, IEEE Geoscience and Remote Sensing Letters, 5(4), 806–809.
• Jiménez-Muñoz, J.C., Cristóbal, J., Sobrino, J.A., Sòria, G., Ninyerola, M., & Pons, X. (2009). Revision of the single-channel algorithm for land surface temperature retrieval from Landsat thermal-infrared data, IEEE Transactions on Geoscience and Remote Sensing, 47(1). 339–349.
• Li, Z.L., Tang, B.H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I.F., & Sobrino J.A. (2013). Satellite-derived land surface temperature: Current status and perspectives, Remote Sensing of Environment, 131, 14-37.
• LST Portal (2019). LST for climate change applications. Retrieved from http://lst.nilu.no/language/en-US/ApplicationsofLST.aspx
• Oguz H. (2013). LST calculator: A program for retrieving Land Surface Temperature from Landsat TM/ETM+ imagery Environmental Engineering and Management Journal 12(3):549-555
• Oguz, H. (2015). A Software Tool for Retrieving Land Surface Temperature from ASTER Imagery, Journal of Agricultural Sciences. 21, 471-482
• Oguz, H. (2016). LST Calculator: A Python Tool for Retrieving Land Surface Temperature from Landsat 8 Imagery. In: Recep Efe, İsa Cürebal, Abdalla Gad, Brigitta Toth (Eds.) Environmental Sustainability and Landscape Management, Chapter: 36, p. 560-572, St. Kliment Ohridski University Press, Sofia.
• USGS (2019). US Geological Survey. Retrieved from http://landsat.usgs.gov /landsat8.php
• Yu, X., Guo, X., & Wu, Z. (2014). Land Surface Temperature Retrieval from Landsat 8 TIRS—Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method. Remote Sensing, 6, 9829-9852.