Monitoring urban greenness evolution using multitemporal Landsat imagery in the city of Erbil (Iraq)

Most cities in the world have experienced major developments in the past 20–25 years. However, research has showed that the development aspect of these cities has led to a decrease in green areas. This paper aims to assess the spatiotemporal variations of urban green areas during the period 1990–2015 with special regard to city of Erbil. The study uses a mix of fuzzy functions, linear spectral mixture analysis, and maximum likelihood classification for the classification of Landsat imagery from 1990 to 2015 to extract the four main classes of land use, namely agricultural land, vacant land, built-up land, and green vegetation. Both the classification approaches used in this research produced excellent and reliable results, as an overall accuracy of more than 80% was able to be obtained. The spatiotemporal analysis of land use within the city of Erbil shows a series of major changes between 1990 and 2015. Therefore, the results of the spatiotemporal evolution of urban greenness assessment in the Erbil region can be used both for spatial planning purposes and as an urban greenness assessment method in dry climate areas.