Climate change has led to an increase in global temperature and frequent intense precipitation, resulting in a rise in severe and intense urban flooding worldwide. This growing threat is exacerbated by rapid urbanization, impervious surface expansion, and overwhelmed drainage systems, particularly in urban regions. As urban flooding becomes more catastrophic and causes significant environmental and property damage, there is an urgent need to understand and address urban flood susceptibility to mitigate future damage. This review aims to evaluate remote sensing datasets and key parameters influencing urban flood susceptibility and provide a comprehensive overview of the flood causative factors utilized in urban flood susceptibility mapping. This review also highlights the evolution of traditional, data-driven, big data, GISs (geographic information systems), and machine learning approaches and discusses the advantages and limitations of different urban flood mapping approaches. By evaluating the challenges associated with current flood mapping practices, this paper offers insights into future directions for improving urban flood management strategies. Understanding urban flood mapping approaches and identifying a foundation for developing more effective and resilient urban flood management practices will be beneficial for mitigating future urban flood damage.

Background: In recent decades, Bangladesh has improved maternal health outcomes significantly. However, disparities in access to maternal healthcare facilities over time remain, particularly in a densely populated country like Bangladesh. This research seeks to highlight the growing use of maternal health facilities from 2011 to 2022 and to reveal key determinants influencing utilization. Method: The analysis used dataset extracted from the 2011, 2014, 2017–2018, and 2022 rounds of Bangladesh Demographic Health Survey (BDHS). Temporal trends in maternal health services across survey years are depicted by descriptive statistics. Overall utilization was examined using pooled data. Multivariable logistic regression identified the associated factors influencing the usage of maternal healthcare services. Results: The study revealed an upward trend in the use of maternal health facilities throughout the survey years. In 2022, women were 1.57 times more likely to have four Antenatal care visits, 5.36 (95% CI: 4.34–6.63) times more likely to have facility‐based delivery, and 5.61 (95% CI: 4.63–6.79) times more likely to receive skilled birth attendance compared to 2011. Higher utilization was associated with urban residence with odds of 1.35 (95% CI: 1.16–1.58), 1.28 (95% CI: 1.09–1.51), and 1.34 (95% CI: 1.16–1.55) for ANC, FBA, and SBA, respectively. Higher maternal education showed odds of 4.59 (95% CI: 3.27–6.43), 4.44 (95% CI: 3.14–6.29), and 6.07 (95% CI:4.52–8.16), and richest households utilized maternal health care services 2.59 (95% CI: 1.99–3.38), 4.64 (95% CI: 3.53–6.10), and 4.34 (95% CI: 3.40–5.43) times more for ANC, FBA, and SBA, respectively. Conclusion: This study demonstrates significant improvements in maternal healthcare engagement in Bangladesh over the past decade. Exposure to media and longer birth intervals were associated with higher utilization. Regional, religious, and household‐level disparities were also evident, whereas factors such as employment and larger family size were linked to reduced service use. However, disparities remain across regions, socioeconomic groups, and household characteristics, underscoring the need for targeted interventions.