A spatial model for assessment of urban vulnerability in the light of the UN New Urban Agenda guidelines: case study of Assiut City, Egypt

Effat, Hala A.; Ramadan, Mona S.; Ramadan, Rasha H.

doi:10.1007/s40808-021-01281-7

Cited by 11 publications

(5 citation statements)

References 24 publications

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“…The UVA can be applied to different audiences and different scales for prior assessment and decision-making of MPHPP. Effat et al ( 17 ) proposed a Spatial Multicriteria Evaluation model to assess the PHTP of Assiut City, which evaluates 13 indicators related to housing, socio-environmental, and economic conditions using standardized, weighted, and aggregated methods. The result revealed that vulnerable areas tend to have the highest proportion of slums, highest population density, highest urban growth rates, and poor service connectivity, which also implies that “economic level,” “population density,” and “service connectivity” may be the critical factors in assessing MPHPP.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF

Liu,

et al. 2024

Front. Public Health

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IntroductionMetropolitan governance’s efficacy is regularly gauged by its capability for public health preparedness, a critical component, particularly in the post-pandemic climate, as global cities reassess their mitigation abilities. This process has broader implications, curbing mortality rates and amplifying sustainability. Current methodologies for preparedness assessment lean primarily on either Subjective Evaluation-Based Assessment (SBA), predicated on experts’ input on various capacity indicators, or they opt for Data-Based quantitative Assessments (DBA), chiefly utilizing public statistic data.MethodsThe manuscript discusses an urgent need for integrating both SBA and DBA to adequately measure Metropolitan Public Health Pandemics Preparedness (MPHPP), thus proposing a novel entropy-TOPSIS-IF model for comprehensive evaluation of MPHPP. Within this proposed model, experts’ subjective communication is transformed into quantitative data via the aggregation of fuzzy decisions, while objective data is collected from public statistics sites. Shannon’s entropy and TOPSIS methods are enacted on these data sets to ascertain the optimal performer after normalization and data isotropy.Results and discussionThe core contribution of the entropy-TOPSIS-IF model lies in its assessment flexibility, making it universally applicable across various contexts, regardless of the availability of expert decisions or quantitative data. To illustrate the efficacy of the entropy-TOPSIS-IF model, a numerical application is presented, examining three Chinese metropolises through chosen criteria according to the evaluations of three experts. A sensitivity analysis is provided to further affirm the stability and robustness of the suggested MPHPP evaluation model.

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Section: Literature Reviewmentioning

confidence: 99%

Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF

Liu,

et al. 2024

Front. Public Health

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“…Urban development in desert areas presents unique challenges such as water scarcity, harsh climates, environmental conservation, and the need for sustainable resource management (Ramadan and Effat, 2021;Alogayell et al, 2024). Strategies to address these include desalination, water recycling, and rainwater harvesting for water scarcity (Alkhalidi et al, 2018;Amr, 2023) innovative architecture and renewable energy to cope with extreme climates (Günel, 2019;Kutty et al, 2023) environmental conservation efforts to protect biodiversity and prevent ecological degradation (Sankaran and Chopra, 2020;Ramadan R. H. et al, 2022;Effat et al, 2022) and the development of durable infrastructure designed to withstand desert conditions (Riadh, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…The application of Geographic Information Systems (GIS) for planning and land use analysis is essential, aiding in making informed urban planning decisions that consider social, economic, and environmental impacts (GIS) (Taiema and Ramadan, 2021;Mishra, 2023). GIS-based analysis has proven invaluable in mapping and analyzing land use suitability for different uses, determining ecological habitats, assessing geological and agricultural suitability, and evaluating landscapes for planning and services (Abdullahi et al, 2015;AbdelRahman et al, 2016;González-Méndez et al, 2021;Ramadan M. S. et al, 2022;Hakam et al, 2023;Lötz, 2023;Rana and Moniruzzaman, 2023;Watuwaya et al, 2023). This research uses Remote Sensing technology and GIS to explore development opportunities in the Southwestern NEOM region in Saudi Arabia, identifying ideal locations for urban development by considering many parameters such as Land Use-Land Cover, Slope, Faults, High order stream, Geologic map, Quarries, Power supply, Water Supply, Industrial areas, Incinerators, Tourist sites, and Roads.…”

Section: Introductionmentioning

confidence: 99%

Geospatial modeling of optimal zones for sustainable urbanization in southwestern NEOM, Saudi Arabia using geomatics techniques

Alogayell,

Kamal,

Alkadi

et al. 2024

Front. Built Environ.

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Our study meticulously pursued its objectives through a strategic data-gathering approach and a thorough analytical evaluation. In the data collection phase, we undertook an exhaustive accumulation of geographical and environmental information, utilizing high-resolution satellite images and diverse thematic maps. We employed GIS-based models and the Analytical Hierarchy Process (AHP) to effectively determine the most suitable areas for urban development. These models pinpointed zones along the coastal areas and nearby plains, spanning 198.89 square kilometers or 8.25% of the total study area, as highly appropriate for development due to their potential for desalination and tourism, and proximity to vital infrastructure such as the forthcoming NEOM airport and high-speed railway connections. The findings from the Southwestern NEOM model corroborate with NEOM’s strategic goals, especially validating the chosen location for The Line. This location is considered ideal due to its accessibility, terrain suitability, and capability to incorporate renewable energy and sustainable water management, thereby supporting the strategic aims and placement of the initiative. This not only highlights the strategic positioning of these areas but also aligns with the Saudi Vision 2030, fostering economic diversification and sustainable development. Together, these actions have established a comprehensive framework for urban planning that respects environmental conservation and promotes sustainable development objectives. By incorporating socio-economic and cultural factors, our research offers a well-rounded approach to urban development, ensuring that new infrastructure is both environmentally considerate and strategically situated to promote enduring growth and community wellbeing in Southwestern NEOM.

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“…As a result, the tasks of monitoring, assessing, and predicting air quality have become increasingly crucial, particularly in the context of disease outbreaks ((Nimesh et al, 2014;Samal et al, 2019;Taufik et al, 2020;Liu B. et al, 2021;). This has led to the development of advanced tools for evaluating pollution ( (Liu B. et al, 2021;Liu H. et al, 2021;Huang et al, 2021;Liao et al, 2021;Effat et al, 2022;).…”

Section: Introductionmentioning

confidence: 99%

Advancing air quality forecasting in Abu Dhabi, UAE using time series models

Ramadan,

Abuelgasim,

Al Hosani

2024

Front. Environ. Sci.

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This research enhances air quality predictions in Abu Dhabi by employing Autoregressive Integrated Moving Average (ARIMA) models on comprehensive air quality data collected from 2015 to 2023. We collected hourly data on nitrogen dioxide (NO2), particulate matter (PM10), and fine particulate matter (PM2.5) from 19 well-placed ground monitoring stations. Our approach utilized ARIMA models to forecast future pollutant levels, with extensive data preparation and exploratory analysis conducted in R. Our results found a significant drop in NO2 levels after 2020 and the highest levels of particulate matter observed in 2022. The findings of our research confirm the effectiveness of the models, indicated by Mean Absolute Percentage Error (MAPE) values ranging from 7.71 to 8.59. Additionally, our study provides valuable spatiotemporal insights into air pollution historical evolution, identifying key times and areas of heightened pollution, which can help in devising focused air quality management strategies. This research demonstrates the potential of ARIMA models in precise air quality forecasting, aiding in proactive public health initiatives and environmental policy development, consistent with Abu Dhabi’s Vision 2030.

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A spatial model for assessment of urban vulnerability in the light of the UN New Urban Agenda guidelines: case study of Assiut City, Egypt

Cited by 11 publications

References 24 publications

Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF

Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF

Geospatial modeling of optimal zones for sustainable urbanization in southwestern NEOM, Saudi Arabia using geomatics techniques

Advancing air quality forecasting in Abu Dhabi, UAE using time series models

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