Mustafa Hamoodi

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Research@Locate Presentation:
Diurnal and seasonal surface temperature variations: a case study in Baghdad city

Mustafa Hamoodi, PhD student at Curtin University


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5 Things You Will Learn

  1. Urban classification
  2. Extraction built-up area by ISA techniques
  3. Producing LST maps
  4. Comparison diurnal and seasonal LST
  5. Using daytime and nighttime Landsat images

Target Audience

People who interest in field of remote sensing including urban heat islands, image classification, calculate LST, NDVI and MNDWI. As well as comparison diurnal and seasonal surface temperature.

Presentation Overview

Urban land use and land cover (LULC) classification is an important technique to study a variety of applications in remote sensing, especially in urban climate and environment. In this study, a new approach was applied to classify urban LULC area into four main categories using Landsat TM. This approach used the impervious surface area (ISA) technique by fusing the night thermal band with day multispectral bands of Landsat data. In addition, masks of water and vegetation cover were applied to extract their categories. In the second part, diurnal and seasonal variations in surface temperature were analysed using LST maps. Landsat TM images during daytime and nighttime for Summer and Winter in 1990 have been utilised to estimate surface temperature and spectral indices (MNDWI and NDVI).