Abstract

Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially green space, have become a great challenge for sustainable urban development. Detection of such changes may help decision makers and planners to understand the factors in land use and land cover changes in order to take effective and useful measures. Change detection is a technique used in remote sensing for detecting the changes which may have occurred in the existing over two or more periods of time in a particular area. In this paper, Saqqez, a city in Kurdistan province has witnessed a rapid growth in construction which has caused destruction of green spaces areas. It is fragmented and dispersed, causing impairment and dysfunction of these important urban elements. The objective of this study was to detect changes in extent and pattern of green areas of Saqqez city and to analyze the results in terms of landscape ecology principles and functioning of the green spaces. Three remote sensing techniques, including normalized difference vegetation index (NDVI) comparison, principal component analysis (PCA) and the post classification were employed to detect the green space changes. To carry out these techniques, Thematic Mapper (TM) andEnhanced Thematic Mapper Plus (ETM+) LANDSAT data within the year 1989 to 2009 were used to recognize land use changes, especially the physical development of the area and its devastating effects on the green space. The result showed that green space has been reduced from 530 ha in 1989 to 198.3 ha in 2009. In this research, the capabilities of LANDSAT data which is oriented towards determining land use changes, via the standard methods is examined. The result showed that NDVI and post classification analysis methods are better than principal component analysis in detecting the devastating effects of unplanned constructions and forming projects on Saqqez’s green space.

Key words: Multi-temporal images, change detection, destruction of green space, urban development, Saqqez.