The peri-urban area (PUA) of the Greater Cairo Region (GCR) in Egypt has witnessed a rapid urban expansion during the last few years. This urban expansion has led to the loss of wide, areas of agriculture lands and the annexation of many peripheral villages into the boundary of the GCR. This study analyzed the driving factors causing the urban expansion in the GCR during the period 2007–2017 using the logistic regression model (LRM). Eight independent variables were applied in this model: distance to the nearest urban center, distance to the nearest center of regional services, distance to water streams, distance to the main agglomeration, distance to industrial areas, distance to nearest road, number of urban cells within a 3 × 3 cell window and population density. The analysis was conducted using LOGISTICREG module in Terrset software. This research showed that the population density and distance to the nearest road have the highest regression coefficients, 0.540 and 0.114, respectively, and were the most significant driving factors of urban expansion during the last 10 years (2007–2017). Moreover, based on the results of the LRM, a probability map of urban expansion in the PUA was created, which shows that most urban expansion would be around the existing urban areas and near roads. The relative operating characteristic (ROC) value of 0.93 indicates that the probability map of urban expansion is valid.

No abstract

No abstract

During the last few decades, sustainable development (SD) has increasingly received attention globally. Therefore, international organizations and researchers sought to assess progress towards SD at different territorial levels. However, most of the studies were conducted at the city level and a very small number of studies has conducted at the urban periphery territory. This study aims to fill the current research gap through assessing the progress towards SD in the urban periphery of Greater Cairo (GC) in Egypt between 1996-2017. Eight composite indicators have been employed to assess the progress towards SD in this territory. These composite indicators were constructed based on the 14 individual indicators associated with sustainable development goals. The results showed meaningful progress achieved in the peripheral municipalities of GC, particularly in infrastructure and education indicators, while the economic and environmental indicators have deteriorated, particularly after the civic revolution of 2011. In addition, the study found a development gap between the urban periphery and the main urban agglomeration in GC, particularly in the infrastructure aspect. These results highlight the deficiencies that exist in the urban periphery of GC which help decision-makers to prepare appropriate policies to improve SD in such territory.

During the last three decades, Delhi has witnessed extensive and rapid urban expansion in all directions, especially in the East South East zone. The total built-up area has risen dramatically, from 195.3 sq. km to 435.1 sq. km, during 1989–2020, which has led to habitat fragmentation, deforestation, and difficulties in running urban utility services effectively in the new extensions. This research aimed to simulate urban expansion in Delhi based on various driving factors using a logistic regression model. The recent urban expansion of Delhi was mapped using LANDSAT images of 1989, 2000, 2010, and 2020. The urban expansion was analyzed using concentric rings to show the urban expansion intensity in each direction. Nine driving factors were analyzed to detect the influence of each factor on the urban expansion process. The results revealed that the proximity to urban areas, proximity to main roads, and proximity to medical facilities were the most significant factors in Delhi during 1989–2020, where they had the highest regression coefficients: −0.884, −0.475, and −0.377, respectively. In addition, the predicted pattern of urban expansion was chaotic, scattered, and dense on the peripheries. This pattern of urban expansion might lead to further losses of natural resources. The relative operating characteristic method was utilized to assess the accuracy of the simulation, and the resulting value of 0.96 proved the validity of the simulation. The results of this research will aid local authorities in recognizing the patterns of future expansion, thus facilitating the implementation of effective policies to achieve sustainable urban development in Delhi.