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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.

Over the last four decades, the loss of agricultural land has been observed in Egypt at high rates. However, the highest rates of losses have occurred since the January 25th revolution in 2011. Greater Cairo (GC), which is the largest metropolitan in Egypt, has witnessed a massive loss of agricultural land since the 2011 revolution. However, until now, no study or official report has revealed the volume of agricultural land losses in this region. This study quantifies agricultural land losses around the GC using Landsat satellite images from 2010 and 2018. Supervised classification was performed using the maximum likelihood algorithm in QGIS software. A post-classification comparison method was applied to detect the land use/land cover changes between the classified images; then, the loss of agricultural land was quantified using Arc GIS software. Visualizations of the gains and losses in agricultural land and the spatial trends of agricultural land losses were created using TerrSet software. The results show that 9600 ha of agricultural land were converted to urban use during 2010–2018, which means that the annual rate of agricultural land loss has tripled and now reaches approximately 1200 ha per year. Decay of executive authority, rapid population growth, real estate market speculation and fragmentation of agricultural land were the main driving factors of agricultural land losses during this period. The results of this research may help decision makers understand the current high rate of agricultural land loss. Hence, appropriate strategies may be adopted to prevent future losses of this valuable land.

The increasing threat of transportation energy insecurity, environmental issues and public health issues have led to a growing body of research that looks at the potential contribution of urban planning in reducing travel energy consumption. The sustainable planning strategies aimed at reducing travel energy consumption need to understand the relationships between urban form, travel behavior and energy consumption. This study provided additional insights into the relationships between urban form, travel mode choice and energy consumption via mode-wise (non-motorized, motorcycle, car, bus and rail) stratified models and travel energy consumption model by applying the multiple linear regression model based on 108 zones of Fukuoka city, Japan. This study suggests that urban form makes a major contribution towards conserving travel energy in cities. This study shows that the provision of bus stops and rail stations are essential alongside an increase in road connectivity, otherwise increasing only road connectivity encourages people to use private modes of transport, which is not good for travel energy conservation. The findings suggest that better transit accessibility promotes public mode use, and reduces private mode use and travel energy consumption even where travel distance is longer. Higher density with greater land use mix and better transit accessibility has a more profound influence on increasing use of the non-motorized mode.