Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

Urban growth copes with problems in sustainable development. In developing countries, particularly, sustainable development of urban growth copes with severe challenges with respect to sluggish economic and social growth, population boom, environmental deterioration, unemployment, slums and so on. Time series of remote sensing data provide critical support on sustainability assessment. However, the urban spatial extend cannot be accurately extracted from land cover data. Targeting the urban growth and its sustainability in Islamabad, the capital of Pakistan, this study extracts urban area from four periods of Landsat images between 1990 and 2018 using an innovative object-based backdating change detection method and two criteria for extracting urban land from impervious surface. We prove that impervious surface cover and urban area increased 273.10% and 426.21%, respectively, over the last 3 decades. We identify five factors playing important role in urban growth: population, transportation systems, master planning, industrial and real estate development, and neighbor urban effect. In this study, we assess the socioeconomic sustainability associated with slum growth and census data, and the environmental sustainability in relation to the variations of normalized difference vegetation index (NDVI) in forest areas. We found that slums increased with the corresponding growth of urban area and population, reflecting sluggish economic increase in Islamabad. We found that the area of woodland increased 9.29%, but its NDVI decreased from 0.668 to 0.551, implying a deteriorative trend of environmental condition. Keywords Land cover Á Impervious surface Á Change detection Á Urban growth Á Islamabad Á Sustainability Y. Liu (&) Á Shaker ul din