Urban sprawl has become a very complex process, because it has many factors affecting its directions and values. The study of relative research shows that the driving forces that lead and redirect future urban sprawl require the application of a statistical method. In our study, logistic regressions were used to analyze and class the driving forces for urban sprawl. Identifying the driving forces, which is the most important step in predicting the future of urban sprawl in 2037, was performed using the cellular automata models. This study takes the Aswan area as a case study in the period from 2001 to 2013 by analyzing the official detailed plan and Google Earth historical imagery. Almost all data was prepared for logistic regression analysis using ArcGIS software and IDRISI^® Selva. In our study, a hybrid model of the Markov chain and logistic regression models was applied to identify future urban sprawl in 2037. The findings of this paper simulate the increase in urban area over 24 years from 1.85 to 2.59 km². These findings highlight the growing risks of urban sprawl and the difficulties opposing the sustainable urban development plans officially proposed for this area.

The primary healthcare facilities are among the most basic needs of the residents, huge in quantity and widespread. Their distributions are directly related to people’s health, which affects the sustainable development of cities. The accessibility calculation of primary level healthcare facilities and the equity evaluation of accessibility from the perspective of medical service category and urban population is very important for the decision-making of layout and configuration but has been ignored for a long time. This study took the primary healthcare facilities of Fukuoka city in Japan as research objects; it first used the variable two-step floating catchment area (V2SFCA) method to calculate the healthcare catchment areas (HCAs) of medical service providers and the population catchment area (PCAs) of medical demand locations, and then obtained the accessibility to primary healthcare facilities. Finally, the spatial disparities of accessibility were evaluated from three aspects: overall space distribution by using Global and Local Moran’s I, service quality, and the population to be served. The results showed that HCAs were from 500 m to 6400 m, PCAs ranged from 500 m to 3000 m, the use of variable catchments can improve the accuracy of accessibility assessment results; the accessibility of primary healthcare facilities was clustered and had significant spatial differences, which were high in urban center and low in suburban area; the obvious differences in the accessibility distribution characteristics of clinics in differential diagnosis and treatment departments led to different degrees of unsaturation in the types of medical services obtained by residents; although the elderly’s demand for basic medical care was many times higher than that of other age groups, the accessibility in high-demand areas was generally low, and the situation in severely high-demand areas was more serious. This work puts forward a multi-dimensional realistic evaluation system for equality accessibility of primary healthcare facilities, providing the data support for the medical resources and facilities’ allocation and the intensive land use.

Abouelreesh is one of the most at risk areas in Aswan, Egypt, which suffers from storms, poor drainage, and flash flooding. These phenomena affect the urban areas and cause a lot of damage to buildings and infrastructure. Moreover, the potential for the further realization of dangerous situations increased when the urban areas of Abouelreesh extended towards the risk areas. In an effort to ameliorate the danger, two key issues for urban growth management were studied, namely: (i) estimations regarding the pace of urban sprawl, and (ii) the identification of urban areas located in regions that would be affected by flash floods. Analyzing these phenomena require a lot of data in order to obtain good results, but in our case, the official data or field data was limited so we tried to obtain it by accessing two kinds of free sources of satellite data. First, we used Arc GIS tools to analyze (digital elevation model (DEM)) files in order to study the watershed and better identify the risk area. Second, we studied historical imagery in Google Earth to determine the age of each urban block. The urban growth rate in the risk areas had risen to 63.31% in 2001. Urban growth in the case study area had been influenced by house sizes, because most people were looking to live in bigger houses. The aforementioned problem can be observed by considering the increasing average house sizes from 2001 until 2013, where, especially in risky areas, the average of house sizes had grown from 223 m² in 2001 to 318 m² in 2013. The findings from this study would be useful to urban planners and government officials in helping them to make informed decisions on urban development to benefit the community, especially those living in areas at risk from flash flooding from heavy rain events.

At present, Japan is facing the problem of increasing medical demands caused by an aging society. The imbalance between supply and demand makes the efficiency of medical services particularly important. In this context, a new medical facility, medical malls, has emerged in recent years. Different from independent clinics, the medical mall is a facility that integrates multiple medical functions and provides multi-disciplinary treatments for patients. In order to verify the effectiveness of this new medical facility and explore its relationship with the urban environment, this paper first identifies the medical malls in Fukuoka City and studies their characteristics, then the SBM model was used to calculate the medical efficiency of the clinics in the 75 medical malls, compared with the independent clinics. Finally, the research analysed the spatial distribution of the medical mall efficiency and the spatial regression with the surrounding urban environment. The results show that the medical mall is a more efficient facility, and population density of the young and the working-aged, the number of main roads, total construction area, the proportion of residence and commerce, and the number of the other medical facilities have significant impacts on the medical efficiency. This research proposes a method to evaluate the effectiveness of utilization of medical resources. Through the evaluation of medical efficiency and the analysis of the urban environment affecting efficiency, this paper provides data support for the site selection of medical malls and the rational layout of urban medical facilities.

Timely access to essential primary healthcare services is critical for achieving health equity, particularly in geographically constrained mountainous regions where terrain imposes significant barriers to mobility. However, existing national planning standards in China rely on uniform service radii or walking-time thresholds, often failing to reflect the true accessibility conditions in complex highland environments. To address this gap, this study develops a Multi-Factor Integrated Mountain Walkability Model (MIMWM) that incorporates high-resolution Digital Elevation Models, slope-adjusted walking speeds, land-use resistance coefficients, and physiological walking capacity decline at altitude. Embedded within the Two-Step Floating Catchment Area framework, the model is applied to Diqing Tibetan Autonomous Prefecture in Yunnan Province, a high-altitude region characterized by rugged terrain and sparse healthcare infrastructure. Results demonstrate that traditional Euclidean and network-based methods substantially overestimate accessibility, particularly within the 15–60 min walking thresholds. The MIMWM reveals a critical threshold effect at approximately 30 min, beyond which accessibility improvements diminish. Moreover, most residents in the study area fall below the baseline criteria for access set by national healthcare standards, highlighting the inadequacy of uniform service thresholds in mountainous settings. This study underscores the dominant influence of terrain and walking capacity constraints and advocates for location-specific accessibility metrics and near-distance infrastructure investment to improve rural health equity. The model provides a replicable approach for integrating terrain sensitivity into healthcare accessibility planning in other topographically complex regions.