City Area Research Articles

GIS-based spatial approaches to refining urban catchment delineation that integrate stormwater network infrastructure

Rapid urbanization and escalating climate change impacts have heightened stormwater-related concerns (e.g., pluvial flooding) in cities. Understanding catchment dynamics and characteristics, including precise catchment mapping, is essential to accurate surface water monitoring and management. Traditionally, topography is the primary data set used to model surface water flow dynamics in undisturbed natural landscapes. However, urban systems also contain stormwater drainage infrastructure, which can alter catchment boundaries and runoff behavior. Acknowledging both natural and built environmental influences, this study introduces three GIS-based approaches to enhance urban catchment mapping: (1) Modifying DEM elevations at inlet locations; (2) Adjusting DEM elevations along pipeline paths; (3) Applying the QGRASS plug-in to systematically incorporate infrastructure data. Our evaluation using the geographical Friedman test (p > 0.05) and Dice Similarity Coefficient (DSC = 0.80) confirms the statistical and spatial consistency among the studying methods. Coupled with onsite flow direction validation, these results support the feasibility and reliability of integrating elements of nature and built infrastructure in urban catchment mapping. The refined mapping approaches explored in this study offer improved and more accurate and efficient urban drainage catchment zoning, beyond using elevation and topographic data alone. Likewise, these methods bolster predictive stormwater management at catchment scales, ultimately strengthening urban stormwater and flooding resilience.

Digital Adoption by an Organization Supporting Informal Caregivers During COVID-19 Pandemic Showing Impact on Service Use, Organizational Performance, and Carers' Well-Being: Retrospective Population-Based Database Study With Embedded User Survey.

The COVID-19 pandemic has catalyzed a move from face-to-face to digital delivery of services by hospitals and primary care. However, little is known about the impact of digital transformation on organizations supporting unpaid caregivers. Since the start of the COVID-19 pandemic, the value of care provided by such informal caregivers is estimated to be £111 billion (US$ 152.7 billion) in England. This study aims to analyze service uptake patterns (including digital service options) over the pandemic period in an English caregivers' support organization covering a population of 0.98 million; measure changes in organizational performance, service efficiency, and quality; and identify the views of caregivers on service provision and future digital delivery. This was a retrospective analysis of the use of digital versus nondigital support services (January 2019 to June 2021) by caregivers in city and rural geographic areas. We compared organizational performance and service quality indicators for 2 financial years (2019-2020 and 2020-2021). A survey was conducted to identify barriers and facilitators to digital service uptake, the computer proficiency of caregivers (the Computer Proficiency Questionnaire, 12-item version), and preferences for future digital service provision. Quantitative data were analyzed using Stata 13 (StataCorp LLC). Thematic analysis was used for open-text survey responses. The number of caregivers registered with the organization rose from 14,817 in 2019 to 20,237 in 2021. Monthly contacts rose from 1929 to 6741, with remote contacts increasing from 48.89% (943/1929) to 86.68% (5843/6741); distinctive patterns were observed for city versus rural caregivers. There was an increase in one-to-one contacts (88.8%) and caregiver assessments (20.9%), with no expansion in staffing. Service quality indicators showed an improvement in 5 of 8 variables (all P<.05). The 152 carers completing the survey had similar demographics to all registered caregivers. The Computer Proficiency Questionnaire, 12-item version, mean score of 25.61 (SD 4.40) indicated relatively high computer proficiency. The analysis of open-text responses identified a preference for the organization to continue to offer face-to-face services as well as web-based options. The digital services that were the most highly rated were carers' well-being assessments, support needs checks, and peer support groups. Our findings show that staff in the caregiver support organization were agile in adapting their services to digital delivery while dealing with increased numbers of registered clients and higher monthly contacts, all without obvious detriment to service quality. Caregivers indicated a preference for blended services, even while recording high computer proficiency. Considering the economic importance of unpaid caregivers, more attention should be given to organizations funded to provide support for them and to the potential for technology to enhance caregivers' access to, and engagement with, such services.

Spatio-temporal pattern analysis of coastal zone in Nansha based on remote sensing technology

Among the most important and active areas of coastal cities is the coastal zone. Examining the changes in the coastal zone of Nansha District is helpful in identifying the spatiotemporal evolution pattern and driving force of this area, as well as serving as a guide for the preservation and exploitation of its resources. This is due to the fact that remote sensing's ability to collect and analyze coastlines can show minute variations in the way the water and land interact. The article uses drone orthophotos and Landsat and Quickbird paired with eight different sceneries from 1987 to 2021 to extract the coastline using remote sensing (RS) and geographic information system (GIS) techniques. The spatiotemporal features of the evolution of the Nansha shoreline are examined in order to guarantee correctness. and the motivating elements are talked about. The findings indicate that: 1) Over the previous 30 years, there has been a consistent upward tendency along Nansha District's shoreline. Among these, the percentage of artificial shoreline is growing annually, growing by about 56%, while the natural coastline is decreasing annually, decreasing by 70%. 2) There is a shift in the type of shoreline from natural to sea-reclamation, engineering construction, and aquaculture. 3) The modifications to the coastline have occurred in three phases: the first was the agricultural phase; the second was the port petrochemical phase; and the third was the reasonable restraint phase (quality construction). Wanqingsha, Longxue Island, and Nansha Bay's coastlines are all close to significant expansion areas of coastline. 4) The primary causes of the changes in the Nansha District shoreline are human activity, regional policy, and natural elements.

GACDNet:Mapping winter wheat by generative adversarial cross-domain networks with transformer integration for zero-sample extraction

Accurate extraction of winter wheat area is essential for wheat yield estimation. Remotely sensed images have limited coverage, are taken at different times, from different angles and in different geographical areas, and the spectral information of the same feature varies from image to image. Machine learning methods are very popular in extracting winter wheat planting area, there are differences between different images, namely the distribution differences between source domain data and target domain data, the results obtained by these methods directly applied to other areas are not satisfactory. To achieve cross regional extraction of winter wheat area, we propose generative adversarial cross-domain networks for image classification under the same image type. The cross-domain network proposed comprises a generative network and a feature extractor. The generative network creates diverse and acceptable samples from the initial input data, constrained by the contrast loss. The feature extractor converts the initial input data and the generated data into a high-level representation. Two time series datasets were constructed and a series of experiments were conducted on these datasets, obtaining high-precision and optimal classification results. Sample training was performed using 70%, 50%, 30% and 10% of the data on both datasets. The study results demonstrated the high performance and cross-domain capability of our network. Furthermore, the winter wheat cultivation area of the entire Zhoukou city was extracted, yielding results with an accuracy of 94.23%. Extensive experiments and applications on the dataset demonstrate that our method is feasible and reliable.

Spatial and temporal analysis of thyroid cancer incidence in Guilan Province, Northern Iran, 2009–2018

BackgroundThyroid cancer is one of the most common malignancies of the endocrine system, the fifth most common malignancy in women worldwide, and the second most common cancer in women over 50 in 2019. It is the sixth most common cancer in both sexes and the third most common cancer in women in Guilan province. This study was conducted to describe the geographic variation and investigate any changes in the trend of the thyroid cancer incidence rate. MethodsThis study was conducted on the data of the Guilan University of Medical Sciences cancer registration system. The crude and age-standardized incidence rate was calculated per 100,000 person-years. Joinpoint regression analysis evaluated the time trends and annual percent changes (APC). The incidence rate was estimated separately for each city and high-risk areas were shown on the province map using GIS software. Results1742 cases of thyroid cancer (83.7 % in women and 16.3 % in men) were registered in Guilan province from 2009 to 18. The incidence of thyroid cancer was 5.1-fold higher in women than men. The results of the joinpoint regression analysis showed that the age-standardized incidence rate of thyroid cancer in both sexes has increased significantly over ten years (APC: 26.4; 95 %CI: 22.5–30.4), (P-value < 0.001). In our study, Astaneh-ye Ashrafiyeh, Lahijan, and Langarud cities were identified as high-risk areas of the province for both sexes. ConclusionThe trend of incidence of thyroid cancer in Guilan province is increasing. Also, a wide geographical variation was found in the incidence of thyroid cancer.

Prediction of flood sensitivity based on Logistic Regression, eXtreme Gradient Boosting, and Random Forest modeling methods

ABSTRACT Floods are one of the most destructive disasters that cause loss of life and property worldwide every year. In this study, the aim was to find the best-performing model in flood sensitivity assessment and analyze key characteristic factors, the spatial pattern of flood sensitivity was evaluated using three machine learning (ML) models: Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), and Random Forest (RF). Suqian City in Jiangsu Province was selected as the study area, and a random sample dataset of historical flood points was constructed. Fifteen different meteorological, hydrological, and geographical spatial variables were considered in the flood sensitivity assessment, 12 variables were selected based on the multi-collinearity study. Among the results of comparing the selected ML models, the RF method had the highest AUC value, accuracy, and comprehensive evaluation effect, and is a reliable and effective flood risk assessment model. As the main output of this study, the flood sensitivity map is divided into five categories, ranging from very low to very high sensitivity. Using the RF model (i.e., the highest accuracy of the model), the high-risk area covers about 44% of the study area, mainly concentrated in the central, eastern, and southern parts of the old city area.

Population analysis using GIS software tools A case study of Chengdu

Understanding how the population is distributed geographically helps governments and organizations allocate resources more efficiently. For example, they can allocate funds for infrastructure development, healthcare facilities, schools, and public services based on the population's concentration and distribution. City planners can use population distribution data to design cities and urban areas effectively. They consider factors like housing needs, transportation infrastructure, and zoning regulations based on the population's spatial distribution. This study takes Chengdu as an example, and the article analyzes the spatial structure distribution of the population in Chengdu in the last decade based on the census data of 2012, 2017, and 2021, using analysis methods such as population distribution structure index (PDSI), mean pointer center, and population center of gravity, combined with Geographic Information System (GIS) technology. According to the analysis, it can be concluded that the population distribution pattern in Chengdu has not changed much, but the city area has been expanded. Besides, the policy adjustment has a certain impact on the population center of gravity but not as much as other factors. At last, topography, transportation, and economic development all have an impact on the population distribution of Chengdu.

A data-driven approach to urban charging facility expansion based on bi-level optimization: A case study in a Chinese city

This paper addresses the optimization of urban charging facilities expansion in response to the growing charging demand and proposes a data-driven bi-level optimization framework. The proposed framework combines a mixed-integer programming model for siting and capacity planning, an improved sparrow search algorithm (ISSA) for hyperparameter optimization of the CNN-BiLSTM model, and the application of Benders decomposition with Lagrangian relaxation using Gurobi for solving the model. The proposed approach is empirically evaluated through a case study conducted in an administrative area of a Chinese city, using comprehensive charging records and other relevant information. The results demonstrate that the ISSA consistently outperforms other algorithms, showing an average improvement of 23.97 % in root mean square error, 19.25 % in average absolute percentage error, and 1.50 % in the determination coefficient. The modified Diebold-Mariano test confirms the significant advantage of ISSA. Based on the model analysis, the study recommends constructing 20 new charging stations in the case city, with more than half equipped with fast chargers. This strategy ensures that 95 % of the area can find a charging station within 5 min while also ensuring the operator's profitability. The research findings provide effective support for investment decisions related to charging facilities.

Role of nonspecific risk factors in atopic dermatitis

The increasing prevalence of atopic dermatitis (AD) over recent decades suggests that environmental factors play an important role in the etiology and pathogenesis of the disease. Nonspecific factors refer to external (or exposomal) factors and include human and natural factors that influence the health of a population: for example, the socioeconomic status of the patient; climate, including air temperature, exposure to ultraviolet radiation, air pollution; and living in a city or rural area. Although studies have shown the influence of these factors on the course of AD, in general, none of them significantly increases or decreases the risk of developing the disease. This review briefly discusses studies on the role of nonspecific environmental risk factors and their impact on the course of AD in children and adults.

Satisfaction Analysis Of The Bogor Pulo Armyn Community Health Center Website Users Using The End User Computing Satisfaction Method

Public health center is facility service organizing health​ effort health society and efforts health individual level First with more prioritize effort promotive and preventive , for reach degrees health community in the work area . One of The health centers in Bogor City are: Public health center Pulo Armyn Bogor City, where Public health center the using the website as a media provider information related service Public health center . For know level satisfaction user end to a website, then need did it study about analysis level satisfaction user end from that website. Researcher do analysis related level satisfaction user at the end of the website using the End User Computing Satisfaction Method with 6 indicators in the his that is regarding Content, Accuracy, Format, Ease of Use, Timeliness. Data collection is carried out with spread questionnaire to employees and residents who live there place live in the Bogor City area, distribution questionnaire done for 2 weeks with total respondent data namely 107 users . Data obtained tabulated with compile to in table and calculated magnitude percentage its , validity test and reliability test his with using Rstudio tools. Result of research that has been done showing that 57 users feel satisfied with amount percentage 53.3%. Followed with 34 users feel No satisfied with percentage 31.8 %, 14 users feel very satisfied with amount percentage 13.1% and 2 users feel very not satisfied with amount percentage 1.9%. Keywords : Analysis​ Satisfaction , End User Computing Satisfaction , Website Public health center

Exploring Wildfire Evacuation Strategies for Diverse Communities

Wildfire evacuations have become a persistent challenge all over the world in recent years. Studies have proposed various evacuation strategies, such as vehicle reduction, phased evacuation, and prohibition of on-street parking, which have demonstrated effectiveness in specific communities. However, a comprehensive study that generalizes the effectiveness and applicability of these strategies across different types of communities is lacking. This generalization could hold significant value for small, resource-strapped communities situated in wildland–urban interface zones (i.e., comprising a mix of residences and flammable vegetation) that lack the resources to conduct dedicated evacuation studies. In this study, two indicators, the ratio of background traffic volume to the number of evacuees (RBE), and the ratio of the capacity of the main evacuation roads to the number of evacuees (RCE) were derived to categorize communities into specific groups based on their characteristics during wildfire events. Through evacuation simulations of some typical real-world communities, the applicability and effectiveness of each strategy for each group was assessed. For the given scenarios considered, the findings revealed that for communities with high a RBE and low RCE, promoting carpooling with more than two people per vehicle, extending phased evacuation intervals with safety assurance for evacuees, and enforcing on-street parking prohibition made evacuations more effective. For other communities, encouraging families to use fewer vehicles and implementing a 15-min phased interval, if possible, could potentially be useful.

Comprehensive spatial distribution of patients with first-episode psychosis (FEP) and its relation to socio-economic factors.

The functional-cognitive impact of first-episode psychosis (FEP) is extremely relevant and implies dysfunction from early life stages like adolescence and youth. Like other illnesses, FEP incidence is also influenced by environmental factors. It is necessary to attend to this age group with early interventions and to act on the environmental factors that the literature correlates with increased FEP incidence: socio-economic aspects, social adversity, bullying at school or cannabis use. In this context, identifying the areas of cities where FEP patients concentrate is important to perform early interventions. The spatial analysis of patient distribution in a whole city is one way to identify the most vulnerable areas and to propose psycho-social interventions for the possible prevention and/or early detection of FEP by improving urban mental health. An epidemiological study of point patterns to determine the areas of a city with a higher incidence of patients with FEP. To do so, the addresses of FEP cases were georeferenced from 1 January 2016 to 31 October 2022, and 109 FEP patients were analysed. Data from a random sample of 383 controls, comprising their addresses, age, and sex, were randomly obtained from the official city council database. By GIS, the areas with higher FEP incidence were analysed to see if they coincided with the zones where inhabitants with lower incomes lived. The risk ratio of the FEP patients was compatible with the constant risk ratio in Albacete (p = 0.22). When performing the process separately with cases and controls only in men and women, the results were not significant for both distributions (p value: 0.12 and 0.57, respectively). Nonetheless, areas within the city had a significantly higher risk. These groups of cases coincided with those who had lower income and more inequality for women, but this pattern was not clear for men. Classifying city areas per income can help to determine the zones at higher risk of FEP, which would allow early healthcare and preventive measures for these zones.

Leishmania in skin of Rattus rattus from the urban area in the Corrientes city, Argentina

Objective: the objective of the present work was the detection of Leishmania sp. in Rattus rattus tail base skin through polymerase chain reaction (PCR) techniques. Material and Method: We analyzed 45 Rattus rattus skin samples from the urban area of the city of Corrientes in Argentina. The Leishmania spp detection was performed by nested PCR technique. Results: Leishmania DNA was detected in 22 samples out of 45 processed (49%) in the first round of amplification, and in 14 samples (31%) in the second round (31%). Conclusions: These results contribute to increase the existing information in our region on the possible relationship between Leishmania and Rattus rattus, considering the high prevalence found in skin added to the total absence of lesions. Other aspects should be further studied to establish the role of these animals in the epidemiological chain of the disease in an urban area endemic to leishmaniasis in other animal species.

Urbanization intensifies the imbalance between human development and biodiversity conservation: Insights from the coupling analysis of human activities and habitat quality

AbstractIntensified human activities have been seriously threatening the structure and ecological processes of ecosystems, resulting in habitat degradation. Therefore, coordinating the coupling between human activities and habitat quality (HQ) is crucial for high‐quality sustainable regional development and human well‐being. This study evaluated the human activities and HQ in the Pearl River Delta (PRD) urban agglomeration in China from 2000 to 2020 using the human footprint index (HFI) and the integrated valuation of ecosystem services and tradeoffs model. Then, we employed bivariate spatial autocorrelation and a coupling coordination degree (CCD) model to explore the synergistic relationship between human activities and HQ. The results show that spatial changes in HQ were predominantly driven by human activities. The gradual outward urban expansion resulted in significant HQ degradation. Slight HQ improvement by ecological restoration in urban outskirts cannot offset HQ losses caused by urbanization. During the study period, high‐HQ low‐HFI clusters decreased by 1.02%, while low‐HQ high‐HFI clusters increased by 4.67%, the two main clustering types in the PRD. Despite the CCD between HFI and HQ increased after 2010, the continuous changes of CCD characteristics from the HFI significantly lagged type to the HQ lagged. HFI showed an inverted U‐shaped relationship with CCD. The CCD peaks during 2000–2020 corresponded to HFI decreasing from 0.711 to 0.566. This indicates that the risk of decoupling between human activities and HQ gradually increased. Furthermore, CCD levels and characteristics in different bivariate clusters exhibited varying changes over time. These results reveal that the spatiotemporal dislocation between urbanization and ecological restoration induced the spatial nonstationarity of the coupling relationship between human activities and HQ. Urbanization exacerbates the imbalance between human development and biodiversity conservation. Therefore, we suggest reasonably delimiting urban boundaries, controlling the scale of urban sprawl, and strengthening biodiversity protection in areas undergoing rapid urbanization. In addition, we advocate for the division of ecological barrier zones, urban development buffer zones, and urban built‐up areas, each with tailored management and protection measures. Our findings can provide an important reference for the ecological restoration of urban agglomerations.

Environmental challenges and air pollution in Bac Lieu, Vietnam: assessing sources and impacts

AbstractBac Lieu, a region with diverse industries like handicrafts, agriculture, tourism, and a thriving marine economy, faces environmental challenges from climate change, resource exploitation, and rising air pollution due to vehicular, industrial, and agricultural emissions, along with waste management issues. The materials and methods employed in this study encompassed various phases critical for assessing air quality and devising an Air Quality Management Plan (AQMP) for Bac Lieu province. The AQMP framework involved activities such as baseline assessments, emission inventories, air quality monitoring, and modeling using dispersion models like AERMOD. The study proposed the application of the AirQ + model to analyze the correlation between air quality and human health, emphasizing the short-term effects of pollutants on respiratory and cardiovascular diseases, and estimating potential avoidable cases in Bac Lieu province. The emissions inventory in Bac Lieu province categorizes sources into point, mobile, and area. Major CO emissions come from waste burning, cooking, and mixed sources, while traffic significantly impacts CO levels. Residential areas show significant PM10, PM2.5, and NO2 emissions. Point sources impact nearby areas, notably in districts like Hong Dan and Phuoc Long. Cooking activities lead to high PM10 and CO emissions, especially in Bac Lieu city. Traffic emissions, particularly in urban hubs, significantly contribute to pollution, notably in Bac Lieu City, Vinh Loi, and Hoa Binh districts. Transportation emissions in urban zones contribute significantly to air pollution, while rural areas are influenced by various activities like burning, construction, and cooking, shaping diverse local air quality.

Coastal Flood Induced Salinity Intrusion Risk Assessment Using a Spatial Multi-criteria Approach in the South-Western Bangladesh

AbstractBangladesh is extremely vulnerable to sea-level rise and other climate-induced extreme events, such as flooding, storm surge, and salinity intrusion. The south-western coastal region of Bangladesh is particularly vulnerable to salinity intrusion caused by cyclone induced storm surges and coastal floods. Salinity intrusion endanger land productivity by increasing both soil and surface water salinity. Detailed risk assessment using spatial mapping approach can contribute to mitigating the effects of salinity intrusion on natural capital and the environment. In this study, we established and evaluated a spatial multi-criteria approach for mapping the risk levels of areas to salinity intrusion impacts using field data and geospatial techniques at the local scale. We evaluated the viability of the proposed approach using Khulna District, a major coastal city and saline prone area in the south-western Bangladesh. We considered three risk components (i.e. vulnerability, exposure and hazard) with 16 relevant criteria for the study. For each criterion, an Analytical Hierarchy Process (AHP) was used to build and weight spatial raster map layers. Individual maps for each risk component were generated using a weighted sum technique, and lastly, a risk map was created by combining those. Our generated maps correctly identified relevant spatial dimensions as well as risk levels (i.e. very-high to very-low). The outcomes of our study suggest that the southern (east and west) parts of the study area are mostly susceptible to salinity intrusion due to higher storm surge impacts, lower elevation, and land use patterns than other parts. We validate our findings using a qualitative and quantitative approach. We believe that this novel approach would be useful to create risk maps that policymakers and relevant stakeholders could potentially use to evaluate risks posed by flood induced salinity intrusion in coastal regions of Bangladesh and elsewhere with similar geo-climatic context.

Urban vitality and built environment from the perspective of spatiotemporal heterogeneity

ABSTRACT The spatiotemporal heterogeneity of the built environment’s effects on urban vitality is analysed through geographically and temporally weighted regression models. It is found that residents’ travel time and patterns lead to temporal heterogeneity, which is manifested by the fluctuation of the environmental effect of the peak in the morning and evening and the difference between weekdays and weekends. This is especially evident in the business district. Spatial heterogeneity is mainly reflected in the difference between the new urban area and the old city area. Single-function green spaces in areas with high functional complexity still have a weak attraction to people. Land use mix, scale and location are rather nonstationary in the dimensions of time and space.

Optimizing service design for the intercity demand responsive transit system: Model, algorithm, and comparative analysis

Intercity Demand Responsive Transit (IDRT) system, providing on-demand “door-to-door” services for intercity travelers, have been recently implemented in a few cities and gained popularity. To devise a theoretical tool for designing efficient IDRT system, this study proposes a continuous approximation (CA) model to describe the operation metrics of the IDRT. In a two-city system, an optimization model is proposed to study the zoning strategies in the main city, the service area in the satellite city, and headways. The objective is to minimize the average system cost, including the costs of both the operators and the passengers. A two-stage partition algorithm is proposed to generate a near-optimal solution by combining the greedy algorithm and sensitivity-based coordination optimization method. Subsequently, we develop a direct solution algorithm to establish a lower bound for the optimal solution, facilitating a comparison with the near-optimal solution. Throughout all sensitivity analyses, the gaps between the near-optimal solution and the lower-bound solution remain below 3 %. The comparison results demonstrate that the computation time and solution quality of the two-stage partition algorithm are considered acceptable. Simulation is performed to test the validity of the CA model, and the errors in the average system costs are less than 1.16 %. Sensitivity analyses are carried out to evaluate the impacts of several key parameters (e.g., demand densities and line-haul distances) on the optimization results. By comparison with Intercity Fixed Route Transit (IFRT), it can be seen that the choice of IDRT depends on passengers' preference for door-to-door transportation. This study may serve as a valuable reference for the practical implementation of IDRT

Evaluation of water use impacts caused by real estate development with gentrification traits in the metropolitan area of San Luis Potosí

Water resource management is a technical, social, and political issue worldwide. Water, being a public good, is characterized as follows: “Unlike private goods, public goods are indivisible and cannot be satisfactorily met by the market or other private initiatives. The provision of public goods requires cooperation or coercion, either through collective action or effective government.” In this sense, water is a human right, as stated by the UN in its sixth sustainable development goal, which aims to “ensure availability and sustainable management of water and sanitation for all.” Gradually, housing in the city of San Luis Potosí has shifted from being affordable for the entire population to becoming increasingly unattainable. Due to the growing demand for housing driven by common population growth and urban development, in recent years, vertical construction-both residential and commercial-has been implemented as a potential solution to this phenomenon, now accounting for 10% of constructions in this area in the capital city, according to the Registro Único de la Vivienda as of 2023. However, such constructions have brought new challenges to urbanization in San Luis Potosí city. As noted by Lozano Niño Y., areas, where high-socioeconomic-status apartment buildings with gentrification features proliferate, were not planned to support high population densities. Eventually, one of the possible consequences of high densification in these areas will be the inadequacy of basic services such as water. While vertical housing offers an alternative to maximize land use within the urban sprawl and could address housing demands, there is also a need to improve public services and urban infrastructure in the surrounding areas where these constructions are planned to prevent social inequality in terms of public service distribution. This study aims to analyze the relationship between case studies—buildings with gentrification features-and their impact on the use and distribution of potable water among the inhabitants of the urban sprawl of San Luis Potosí, by using geospatial methods and technologies.

Green Infrastructure Fluctuations in Urban Agglomeration of Shanxi Province, China: Implications for Controlling Ecological Crises

The rapid urbanization process means that even moderate-sized cities can quickly become part of larger urban agglomerations, creating new urban zones. Urban Green Infrastructure (UGI) plays a crucial role in these clusters, acting as precious green spaces essential for maintaining ecological safety. This study combines fluctuation analysis based on Morphological Spatial Pattern with traditional landscape pattern analysis, comprehensively addressing the evolution of UGI in terms of quantity, characteristics, and morphology. We selected the Taiyuan-Jinzhong agglomeration as our study area, which is currently in an agglomeration process. The results demonstrated the critical role of surrounding mountains as natural ecological barrier zones. During urban agglomeration, management strategies focused on large-scale afforestation to ensure the quantity of UGI. However, this approach also led to a more clustered landscape with reduced connectivity. Additionally, linear or small-scale UGI types such as branch and islet have seen reductions over the past decade. Changes in internal morphological and complex fluctuations within UGI can harm the formation of ecological networks and potentially negatively affect biodiversity and ecological safety. The research highlights how ecological protection and urban planning policies can influence UGI fluctuations. Therefore, urban managers should not just concentrate on maintaining the quantity of UGI, but also give consideration to changes in its internal features and morphology. Before cities further agglomerate into larger urban clusters, it is crucial to address deficiencies in UGI, continuously improving type configurations and functional structures at the landscape scale. Through strategic planning of UGI, cities can mitigate ecological risks and foster sustainable urban development.