The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI’s capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.

The COVID-19 pandemic has fundamentally transformed the global education landscape, compelling institutions to adopt e-learning as an essential tool to sustain academic activities. This research examines the critical impact of e-learning on arts and science college students in Coimbatore, with an emphasis on its influence on their readiness for campus recruitment. Using a survey of 300 students, this study investigates their perceptions of online education, highlighting both its advantages, such as flexibility and accessibility, and its challenges, including engagement barriers and technical limitations. Data was collected through structured questionnaires and analyzed using statistical methods to draw meaningful insights. The research also explores the efficacy of online assessments in recruitment processes and assesses students’ awareness of available e-learning platforms and courses. The urgency of this study lies in addressing the pressing need to optimize digital education models as institutions globally transition toward blended learning post-pandemic. The findings underline the dual potential and limitations of e-learning, concluding with actionable recommendations to enhance its effectiveness, particularly in preparing students for competitive employment opportunities.

Rapid population growth and inadequate adherence to scientific and managerial principles in urban planning have intensified numerous challenges, pushing major Iranian cities toward instability. Tehran, as the capital and one of the most urbanized regions in the country, faces significant sustainability threats that require immediate attention. These challenges are not unique to Tehran but represent a broader issue faced by rapidly urbanizing cities worldwide, particularly in developing countries. Addressing such challenges is critical to fostering sustainable development on a global scale. While urban sustainability has been extensively studied, limited research has focused on the indicators of urban instability and their tangible impacts on sustainable urban planning. This study aims to bridge this gap by identifying and analyzing key factors contributing to urban instability across economic, environmental, and social dimensions, with Tehran serving as a representative case. The findings reveal that economic instability is driven by uncertainty in economic policies, fluctuating housing prices, non-standard housing conditions, income disparity, unemployment, and cost of living pressures. Environmental instability is exacerbated by climate change, urban heat islands, floods, transportation mismanagement, energy insecurity, pollution, and insufficient green infrastructure. Social instability arises from limited social interaction, unequal access to services, weak community participation, social harms, and diminished urban safety and welfare. By framing these local challenges within a global context, the study underscores the interconnectedness of these dimensions and highlights the necessity for integrated, evidence-based approaches that combine local insights with global best practices. The findings aim to contribute to the broader discourse on sustainable urban development by offering actionable insights and strategies that can be adapted and implemented in other rapidly urbanizing cities. This research serves as a guide for policymakers, urban planners, and stakeholders worldwide, emphasizing the importance of holistic and resilient urban strategies to address the multifaceted challenges of sustainability and instability.

Urban planning is critical to managing rapid urban growth, particularly in African regions experiencing high urbanization rates. This study focuses on Bol, Lake Chad Province, a city facing significant challenges due to inadequate planning frameworks compounded by recurrent humanitarian and climate crises. It fills an empirical gap by analyzing how local planning mechanisms respond to these socio-environmental complexities, with a focus on the interplay between institutional structures, legislative frameworks, and resource allocation. The study assesses urban planning practices in Bol to identify challenges and opportunities, with the aim of improving institutional effectiveness, aligning policies with realities, and integrating climate resilience strategies. Using a qualitative methodology, it combines field surveys, stakeholder interviews, and document analysis, using SWOT (Strengths, Weaknesses, Opportunities, Threats) and PESTEL (Political, Economic, Sociocultural, Technological, Environmental, Legal) frameworks for data analysis. The findings reveal that ineffective institutions, poor inter-sectoral coordination, outdated legislative frameworks and resource constraints hamper sustainable urban development in Bol. To address these issues, the study proposes to strengthen local institutional capacities, foster stakeholder collaboration, and modernize urban planning policies through participatory approaches. The study highlights the need to integrate resilience strategies into urban settings to mitigate climate change impacts and improve governance. These measures not only address immediate challenges, but also advance urban planning theory and provide a basis for future research on adaptation strategies in crisis-prone regions. This study offers practical insights for policy makers and contributes to developing more sustainable and resilient urban planning systems in similar contexts.