Applying a normalized ratio scale technique to assess influences of urban expansion on land surface temperature of the semi-arid city of Erbil

• Published in: International Journal of Remote Sensing
• Main Authors: Rasul, Azad, Balzter, Heiko, Smith, Claire
• Format: Article in Journal/Newspaper
• Language: English
• Published: Taylor & Francis for Remote Sensing and Photogrammetry Society 2017
• Subjects: land surface temperature (LST); land use land cover change; normalized ratio scale (NRS); urban climate; surface urban cool island (SUCI); Landsat; Erbil; sami
• Online Access: http://www.tandfonline.com/doi/abs/10.1080/01431161.2017.1312030; http://hdl.handle.net/2381/39497; https://doi.org/10.1080/01431161.2017.1312030

The difference between surface and air temperature within a city and its surrounding area is a result of variations in surface cover, thermal capacity and 3-dimensional geometry. This research has examined and quantified the decreasing daytime land surface temperature (LST) in Erbil, Kurdistan region of Iraq, and the influence of rapid urban expansion on urban heat/cool island effect over a 20 year period. Land Use/Land Cover (LULC) change across this time period is also established using pixel samples. The current study proposes the application of the Normalized Ratio Scale (NRS) to adjust the temperature of images acquired at different date to the same range. Eleven satellite images acquired by Landsat 4, 5, 7 and 8 during the period 1992 to 2013 are used to retrieve LST. The results indicate that 55.3 km2 21 of city land cover changed from bare soil to urban, consequently the mean LST of the new urbanized area decreased by 2.28°C. The NDVI of Sami Abdul-Rahman (S.A.) Park increased from 0.09 ± 0.01 to 0.32 ± 0.11, resulting in a decrease of the mean LST by 7.29°C. This study shows that the NRS method is appropriate for detecting temperature trends from urbanization using remote sensing data. It also highlights that urban expansion may lead to a decrease in daytime LST in drylands. The authors would like to thank the HCDP Scholarship Programme and Soran University for their financial support of this research. Many thanks go to the USGS, for providing the research with Landsat images of the study area. We would also like to acknowledge the R Development Core Team for continuously improving and supporting this freely available software. H. Balzter was supported by the Royal Society Wolfson Research Merit Award, 2011/R3 and the NERC National Centre for Earth Observation. Peer-reviewed Publisher Version