Urban Change Detection in Jeddah City, Saudi Arabia - Eman Rafi Al Amri, Aljazia Khamis Ali Alkendi (مجلة العلوم الهندسية و تكنولوجيا المعلومات, 2018)
This paper investigates the capabilities and robustness of different remote sensing data for the area between the years1990 and 2000; using Landsat TM images in particular, to extract the urban and vegetation land covers in the city of Jeddah in Saudi Arabia. Locating the land cover changes in Jeddah; from 1990 to 2000 determines the relationship between urban growth and vegetation. Supervised classifications were carried out to extract four urban land covers, namely: urban, vegetation, barren lands and water. Results show that the most remarkable change is witnessed in the expansion of urban lands over the agricultural lands and bare lands through the whole study period of ten years. This paper demonstrates that remote sensing is capable of extracting urban land cover through supervised classifications method using minimum distance classifier algorithm with highly acceptable results. This gives an indication that the agricultural lands are likely to decrease in the future in the city of Jeddah. This paper also discusses that urban land covers information have a tremendous capability for improving urban planning processes in Jeddah.