The intersection of energy transition and urban planning for sustainable development: enhancing energy efficiency and sustainability

Incorporating urban thermal comfort into transit-oriented development (TOD) planning: Non-linear heterogeneous built environment effects

Application of hydro-economic modelling to river basin development planning and management in Nepal

Business incubation has emerged as a key instrument for strengthening local economies, promoting entrepreneurship and expanding employment opportunities within South African municipalities. This article evaluates the role of incubation models in advancing local economic development within the Nkangala District Municipality. A qualitative document analysis approach is employed, drawing on municipal development plans, provincial policy documents and recent academic literature. As the study relies exclusively on secondary sources, no ethical clearance was required. The findings demonstrate that incubation models support enterprise development, enhance small business resilience and foster innovation, particularly in rural and semi-urban areas. Municipalities that embed incubation initiatives within their local economic development strategies show improved alignment between local resource endowments and enterprise growth trajectories. Despite these benefits, the analysis identifies persistent challenges related to inconsistent support systems, limited monitoring and evaluation practices, and weak long-term sustainability planning. The study underscores the importance of capacity building, strategic partnerships and context-sensitive incubation designs. It concludes that incubation models offer clear value for local economic development in Nkangala, but their effectiveness is closely tied to governance stability, coordinated institutional support and ongoing learning. Strengthened policy alignment and collaboration with higher education institutions and the private sector are recommended.

Youth unemployment remains a persistent socio-economic challenge in South Africa and is particularly acute within semi-urban and rural District Municipalities. This article examines the effects of youth unemployment in the Nkangala District Municipality in Mpumalanga Province. The study adopts a qualitative research approach based on secondary data drawn from government labour statistics, municipal integrated development plans and recent academic literature. As the study relies exclusively on documentary sources, no human participants were involved and ethical clearance was not required. The findings indicate that elevated youth unemployment in the district contributes to deepening poverty, constrained local economic growth, increased social dependency and weakened community cohesion. Structural factors, including limited industrial diversification, skills mismatches and unequal access to economic opportunities, are identified as key drivers of youth exclusion. The analysis further shows that unemployed youth face heightened exposure to social risks such as substance abuse, criminal activities and long-term disengagement from the labour market. The article argues that effective responses require coordinated municipal planning, strengthened skills development pathways and closer collaboration with the private sector and technical training institutions. The study contributes a district level perspective that demonstrates how national unemployment trends translate into localised development challenges.

This research examines the potential of integrated land-sea spatial planning as a strategic approach to disaster risk reduction in Tanah Laut Regency, South Kalimantan Province, Indonesia. Specifically, it aims to 1) assess spatial overlaps between terrestrial-marine land-use patterns and hazard zones; 2) evaluate coastal typologies and their corresponding vulnerabilities; and 3) formulate sub-district-specific spatial planning recommendations to enhance regional resilience. A mixed-methods design was adopted, combining quantitative spatial techniques and qualitative descriptive analysis. Disaster potential in coastal regions is examined through an integrated assessment of terrestrial disaster risks and marine-based Coastal Vulnerability Index (CVI) analyses. Terrestrial disaster susceptibility was assessed using the Regional Development Planning Agency (RDPA) 2021 disaster risk assessment, while coastal vulnerability was evaluated using CVI parameters and overlaid with terrestrial and marine spatial planning categories. The spatial analysis shows a strong convergence between high terrestrial disaster risk and land-use categories associated with intensive human modification, notably food crop agriculture (23,610.53 ha), plantations (19,718.99 ha), aquaculture, and urban and rural settlements. Protected areas such as mangrove ecosystems, wildlife reserves, and natural tourism parks are located in high-risk coastal belts, while parts of marine conservation reserve areas and capture fisheries areas fall within high and very high CVI classes. Land-rights (LR) overlays demonstrate that high tidal-flood risk coincides with Ownership Rights (OR) and unregistered parcels. Overall, the research demonstrates that sustainable coastal development in Tanah Laut Regency cannot be achieved by treating land and sea as separate planning arenas. Risk-sensitive, typology-based integration of terrestrial and marine spatial plans, supported by ecosystem-based zoning, mangrove restoration, relocation from high-risk zones, and strengthened marine conservation and fisheries management, is essential to enhance disaster resilience and long-term spatial sustainability in Tanah Laut Regency.

Public management in rural parish governments faces limitations associated with weak articulation between territorial planning and operational execution, generating gaps between strategic planning instruments and the effective implementation of territorial projects. In this context, the objective of the study was to analyze the strategic articulation between territorial planning and operational execution in rural parish governments. The research was developed under a quantitative explanatory approach with an advanced correlational scope through a non-experimental cross sectional analytical design. Information was collected through documentary analysis of territorial development plans, institutional reports and public management records related to local strategic planning. Data processing was carried out using multivariate statistical techniques including multiple linear regression, structural equation modeling, confirmatory factor analysis, canonical correlation analysis and cluster analysis. The results showed that the coherence of territorial planning presents the highest explanatory weight on operational execution (β = 0.46), followed by institutional operational programming (β = 0.39) and administrative coordination (β = 0.31), with a model determination coefficient of R² = 0.62. The structural model also showed adequate goodness of fit indices (CFI = 0.94; TLI = 0.92; RMSEA = 0.048), while cluster analysis identified three differentiated institutional typologies according to the level of articulation between planning and execution. These findings indicate that the effectiveness of territorial governance depends on the integration between strategic planning, administrative capacities and institutional coordination mechanisms.

ABSTRACT The rapid expansion of fast-growing trees like eucalyptus and Acacia decurrens is driving forest transitions in Ethiopia. While promoted for carbon sequestration and climate mitigation, the combined ecological and economic impacts of land-use change remain underexplored. This study examines ecosystem integrity and economic growth in South and Southeast Ethiopia using panel data from satellite imagery, integrating ecological indicators with night-time lights as a proxy for economic activity. A dynamic difference-in-difference (DID) framework assesses eucalyptus expansion across three agro-ecological zones. Results show heterogeneous effects: normalized difference vegetation index (NDVI) increases dynamically, moisture stress index (MSI) shows no persistent change, and land surface temperature (LST) rises variably across zones. Total ecosystem service value (TESV) increases by 45.4% per hectare per year, with significant gains in regulating, supporting, and cultural services, but minimal effects on provisioning services. Benefits are strongest in montane forests and grassland/woodland zones, weaker in Afro-alpine areas. This study highlights both trade-offs and synergies associated with eucalyptus-based land use and land cover (LULC) change. It also provides a quantitative framework for monitoring ecosystem responses to land-use change. Additionally, it highlights evidence to guide land-use policy, forest governance, and climate-smart development planning in Ethiopia and beyond.

The increasing demand for secure, efficient, and tamper-proof digital payment systems in educational institutions has necessitated the development of automated receipt management solutions. This study presents the design and implementation of a secure web-based Receipt Generation and Verification System that integrates One-Time Password (OTP) authentication and QR code technology to enhance payment transparency and fraud prevention within the School of ICT, Federal Polytechnic Bida. The study adopted a hybrid Software Development Life Cycle (SDLC) approach, combining Waterfall for structured planning and Agile methodology for iterative development and refinement. System requirements were gathered through observation of existing manual receipt processes and stakeholder consultation. The system was developed using HTML, CSS (Bootstrap), JavaScript, PHP, and MySQL, with SMTP integration for automated email delivery of digital receipts. OTP authentication was implemented to secure login and payment authorization processes, while dynamically generated QR codes were embedded in each receipt to enable real-time verification. Testing results demonstrate that the system effectively eliminates delays associated with manual teller submission, reduces the risk of receipt forgery, prevents data loss due to fading ink, and improves financial record accuracy. The QR-based verification mechanism ensures authenticity, while OTP authentication significantly enhances access control and transaction security. The study concludes that integrating OTP and QR code technologies into institutional payment systems improves operational efficiency, transparency, and security. It is recommended that educational institutions adopt secure digital receipt platforms and continuously upgrade encryption and authentication mechanisms to mitigate emerging cybersecurity threats.

Tidal flooding is a recurring hazard in coastal areas and poses a serious threat to the sustainability of community livelihoods, particularly in regions that are highly dependent on coastal-based economic activities. In Bandar Lampung City, frequent tidal flooding events have disrupted the social, demographic, and economic conditions of coastal households, increasing their overall livelihood vulnerability. This study aims to analyze the level of social demographic economic vulnerability of coastal communities using the Livelihood Vulnerability Index (LVI) approach. The assessment focuses on four coastal districts Bumi Waras, Panjang, Teluk Betung Timur, and Teluk Betung Selatan and applies a balanced weighted averaged method to ensure equal contribution of each indicator within the composite index. Standardization of sub-components is conducted to enable consistent aggregation and comparison across districts. The results reveal that all studied districts fall within the vulnerable to very vulnerable categories. Bumi Waras District shows the highest level of vulnerability, primarily driven by a high proportion of female-headed households and limited household expenditure capacity. Panjang District is also characterized by considerable vulnerability due to demographic pressures and reduced labor productivity associated with household age structure. Meanwhile, Teluk Betung Timur and Teluk Betung Selatan exhibit relatively lower vulnerability levels, although persistent dependency ratios and gender-related household characteristics continue to constrain resilience. These findings demonstrate that livelihood vulnerability in coastal urban areas is multidimensional and shaped by the interaction of demographic structure, gender roles, and economic capacity. The study highlights the importance of integrating social and economic dimensions into coastal development planning and disaster risk reduction efforts to enhance household resilience and support sustainable livelihoods in Bandar Lampung City.

Accurate porosity prediction is essential for reliable reservoir characterization in data-limited and heterogeneous formation. Traditional approaches generally have a difficulty handling the inherent complexities and uncertainties of well log data. This study applies and compares three machine learning (ML) approaches, including Artificial Neural Network optimized with Levenberg-Marquardt (ANN-LM), Random Forest (RF), Fuzzy Logic (FL) along with a baseline Multiple Linear Regression (MLR) model, to estimate total porosity from standard geophysical well-logs in three wells from the Mazalai Gas Field (MGF), Kohat Basin, Pakistan. The models utilize sonic, neutron porosity, bulk density, and gamma ray as input parameters. The ANN-LM model was trained using backpropagation and K-fold cross-validation. RF was implemented as an ensemble of decision trees with feature ranking, FL employed Gaussian membership functions in ten bins, and MLR served as a baseline linear method. Model performance was evaluated using the coefficient of determination (R²) and root mean square error (RMSE). ANN-LM showed the strongest generalizability and robustness, achieving R² = 0.99 and RMSE = 3.5 pu by effectively minimizing errors in complex, nonlinear and heterogenous data. RF and FL performed reasonably well achieving R 2 equal to 0.89 and 0.85 respectively, but showed reduced generalization to unseen data. MLR demonstrated the lowest performance acquiring R 2 =0.82. Additionally, A Taylor diagram analysis revealed that ANN-LM provided the most accurate and statistically consistent predictions, closely matching the reference data. These results show machine learning, especially well-optimised neural networks, greatly improves porosity prediction from logs, strengthening reservoir evaluation and development planning in MGF-like settings.

Traditional field-based ecological surveys are inefficient in mountainous regions with steep slopes and deep valleys, highlighting the need for new quantitative remote sensing–based approaches. To account for complex terrain, four representative topographic factors (slope, relief, dissection, curvature) were selected via Digital Elevation Model (DEM) analysis to develop a Terrain Complexity Index (TCI), replacing the dryness component in the Remote Sensing Ecological Index (RSEI). Combined with greenness, wetness, and heat factors from Landsat 8, TCI was integrated using principal component analysis to form a Terrain-Adjusted RSEI (TARSEI), extending ecological assessment from two to three dimensions. In a mountainous case study in Huzhou City, Zhejiang, China, TARSEI showed a marked 34.2-percentage-point improvement over the original RSEI. Its high-value areas captured 82.3% of ecotourism points of interest, versus 48.1% for RSEI, demonstrating its enhanced accuracy for terrain-specific analysis. TARSEI further identified 28 new ecotourism resource clusters totaling 520.1 km2 (8.9% of the city area), with a 98.5% overlap with high TARSEI zones. These results confirmed TARSEI’s effectiveness and provided robust scientific support for sustainable ecotourism development and spatial planning. With its high accuracy, stability, and universality, TARSEI is a promising and transferable tool for ecotourism resource assessment and spatial planning and management in complex terrain regions.

The “Almirante Padilla” Naval Academy (ENAP), on the occasion of its 90th anniversary, launches the OnBoard Knowledge Journal, an open-access platform for the dissemination of research in engineering, technology, and social sciences. This first issue highlights advances in renewable energy systems, software development planning, virtual reality for education, Wi-Fi network optimization through AI, as well as studies on illegal fishing, digital transformation, maritime security, and education supported by digital technologies. With this initiative, ENAP strengthens its role as Colombia’s Maritime University and reaffirms its commitment to knowledge generation, scientific development, and institutional leadership.

Kenya faces significant seismic and landslide risks due to its location along the East African Rift System. Historical earthquakes, such as the 1928 Subukia event (magnitude 6.9), have caused widespread damage, and recent deadly landslides, including the 2019 West Pokot disaster, have resulted in over 70 fatalities and the displacement of thousands. The study employs a comprehensive analytical framework encompassing vulnerability assessment, risk assessment, preparedness measures, mitigation strategies, response mechanisms, and rehabilitation protocols. A vulnerability matrix identifies residential buildings, informal settlements, rural hill communities, and vulnerable populations (children, elderly, persons with disabilities) as high-risk elements, while a risk assessment matrix reveals that landslides present more frequent and immediate threats compared to earthquakes, which though less frequent, carry potential for devastating impacts. The findings indicate that effective preparedness requires integrating early warning systems, public education, emergency drills, stockpiling of relief supplies, and evacuation planning. Mitigation strategies include hazard mapping, enforcement of building codes, slope stabilization, reforestation, and land-use planning regulations. The study highlights the stark implementation divide between developed nations with institutionalized preparedness and developing countries like Kenya facing challenges of limited resources, weak enforcement, fragmented coordination, and systemic vulnerabilities. The paper concludes that multi-faceted, collaborative, and continuous preparedness planning, incorporating scientific data with community-based approaches, is essential for reducing disaster impacts, saving lives, and minimizing economic losses. Recommendations include strengthening institutional capacity, enforcing building regulations, investing in early warning technologies, promoting community awareness, and mainstreaming disaster risk reduction into national and county development plans.

Increasing human activities and climate change have intensified the shift of land use, and the construction of land use models has become a hot spot in the study of land use change. Taking Shaanxi Province as the study area, the prediction performances of four models, namely, CA-Markov, CLUES, FLUS, and PLUS, were comprehensively compared, and the contribution of driving factors was analyzed by combining the LightGBM model. The model accuracy was verified based on the land use data from 2017 to 2022 to explore the applicability and differences of different models in predicting land use changes. The results show that: ① From 2017 to 2022, the areas of forest land, cultivated land, and construction land in Shaanxi Province increased, while the area of grassland decreased significantly by 4 085.63 km2. ② The LightGBM model verified the high explanatory power of driving factors on land use patterns and showed that natural factors dominated the distribution of ecological land (forest land, grassland, and water), while socio-economic factors significantly affected the changes in construction land. ③ The OA of CA-Markov, CLUES, FLUS, and PLUS were 0.90, 0.92, 0.92, and 0.93, respectively, and the Kappa coefficients were 0.86, 0.88, 0.88, and 0.90, respectively. The prediction accuracy of PLUS was higher, and the prediction performance of PLUS in the main land types was relatively accurate. The total deviation of FLUS in different land types was the smallest, followed by the PLUS model. ④ For the spatial distribution results, CA-Markov had a single model, but its operation was the most convenient. The patch distribution of CLUES was relatively clustered, and the patches predicted by the FLUS model were distributed in patches. The expansion pattern was closer to the actual situation. The patch distribution in the PLUS result was the most dispersed and fragmented. Different models had different usage conditions and parameter requirements, and the setting of driving factors may also have affected the prediction effect. This study can provide important methodological support and data reference for land use change prediction and provide a scientific basis for future spatial optimization management and sustainable development planning.

To critically assess the intrinsic potential and structural characteristics of the “Women’s Football Reform and Development Plan of the People’s Republic of China (2022–2035)” in both its design and implementation, this study draws on public policy instrument theory and sports development theory to construct a three-dimensional coordinated analysis framework of “policy instruments–policy goals–policy actors.” Using NVivo 12.0 software, we systematically coded 106 policy provisions in the Plan and, through content analysis, conducted quantitative and qualitative analyses of the distribution of instrument types, the tendency of goal support, and the degree of actor participation. First, policy instruments were classified into supply-type, environment-type, and demand-type, and each category’s frequency and functional characteristics were coded and tallied. Second, five goal dimensions—elite football, campus football, grassroots football, football industry, and football culture—were used to reveal the relative resource emphasis within the document. Third, from the perspectives of government, social organizations, and enterprises, we evaluated each actor’s role and responsiveness within the Plan. Findings indicate that environment-type instruments dominate (50.9%), focusing on strategic planning, institutional guarantees, and incentive mechanisms; supply-type instruments account for 38.7%, emphasizing talent development, infrastructure, and funding; while demand-type instruments constitute only 9.4%, such as market investment, social capital activation, and service outsourcing, reflecting an underutilization of market mechanisms. Goal support is skewed toward elite and campus football (73.5% of instruments), whereas grassroots football and the football industry each receive only 9.4%, and football culture a mere 3.4%, resulting in weak grassroots outreach and cultural development measures. Actor coordination is limited: government undertakes 52.8% of the response tasks, social organizations 37.7%, and enterprises only 9.4%, hindering the formation of a “government–social–enterprise” collaborative governance model. Based on these insights, we propose three optimizations: (1) expand the provision of demand-type instruments by strengthening fiscal incentives, government procurement, and service outsourcing to integrate administrative resources with market mechanisms; (2) coordinate the five goal dimensions by balancing resource allocation, increasing support for grassroots football, industry development, and football culture, and establishing robust goal-evaluation and feedback mechanisms; and (3) build a collaborative governance model among government, social organizations, and enterprises by repositioning the government as a “coordinator,” leveraging the expertise of social organizations, and incentivizing enterprise investment in event operations and industry chain development. This study not only uncovers structural issues in the Plan’s design but also offers systematic theoretical and practical pathways to enhance policy implementation effectiveness and promote the sustainable development of women’s football.

China’s vast rural landscape exhibits pronounced regional disparities in both foundational resources and development potential. In the context of nationwide rural revitalization efforts, the emergent divergence in village development pathways underscores a pressing need for context-specific, classified interventions. To furnish a scientifically grounded typology of villages and inform differentiated development planning, this investigation focuses on Hubei Province as an illustrative case. Synthesizing survey data from 32,457 villages, we developed a multidimensional evaluation framework encompassing four pivotal domains: economic vitality, social service provision, ecological integrity, and cultural value. Leveraging the Self-Organizing Feature Map (SOFM) neural network—an unsupervised machine learning algorithm—we performed a cluster analysis on multi-source, heterogeneous datasets. This technique enabled the objective delineation of spatial typological patterns among Hubei’s villages, elucidated their underlying classification architecture shaped by multifaceted drivers, and demonstrated the methodological robustness and applicability of this approach for large-scale village categorization. Grounded in the derived typologies and informed by strategic directives from higher-tier planning instruments, we conducted a nuanced examination of the distinctive attributes characterizing each village type. The findings provide scientific evidence and decision-making support for village classification and rural revitalization planning in Hubei Province, with valuable implications for other regions with similar development foundations in China.

<p><em>The Kelurahan Cinta Statistik (Kelurahan Cantik) Program is a development program implemented by the Central Statistics Agency (BPS) to improve literacy and utilization of statistical data at the village level as a basis for data-driven development planning. The success of this program is greatly influenced by stakeholder readiness, particularly in terms of human resources. This study aims to determine stakeholder readiness in implementing the Kelurahan Cinta Statistik Program in Kebun Geran Village. This study used a qualitative approach with descriptive methods. Data collection techniques were conducted through interviews, observation, and documentation. The results indicate that stakeholder readiness in implementing the Kelurahan Cinta Statistik Program in Kebun Geran Village is in the sufficient category. Village heads have a good understanding and play an active role in supporting the program, while statistical agents and village officials have basic knowledge and skills that still need to be improved. Supporting stakeholders demonstrate a positive attitude and participation, but their involvement is still limited. Based on the Diffusion of Innovation Theory, this program is in the early to intermediate adoption stage, requiring strengthening of human resource capacity and infrastructure support for optimal and sustainable program operation.</em></p>

The necessity to follow both the sustainable economic development and simultaneously preserve the environment is a burning question to the way of development followed by India. In this paper, the author will present green development plans, which will transform India into Viksit Bharat by 2047. It examines the policy forms, technology development and investment policies that are integrating economic expansion and environmental protection. The use of renewable energy, sustainable urbanization, resource-efficient industrial practices, and the circle of the economy are the main areas of attention. Analyzing the current programs and forecasting the scenarios, the given work of study reveals the realistic possibilities of the balance between the evolution of the economy and the preservation of nature. The findings point to the necessity to develop the capacity to strengthen the sustainability objectives in the long-term through multi-stakeholder collaboration, regulation reformation and capacity-building initiatives.

This study provides a comprehensive evaluation of the Ministry of National Education’s (MoNE) strategic plans spanning the years 2015–2024 through a content analysis methodology. The primary aim is to investigate the alignment between the strategic objectives defined by MoNE and the performance indicators that measure the attainment of these objectives using qualitative document analysis. The research thoroughly analyzes MoNE’s 2015–2019 and 2019–2023 strategic plans, associated performance reports, and Turkey’s National Development Plans. Findings reveal a high level of achievement in objectives related to education quality and infrastructure development. However, significant discrepancies and inconsistencies were found between set targets and performance indicators, particularly in critical areas such as teacher professional development and school leadership capacity. The main reasons for these gaps include resource limitations, policy changes, and local implementation differences. The study emphasizes the need for strategic objectives to be realistically set, measurable, and resource-based. It further recommends the development of comprehensive training programs and practical support mechanisms to enhance teachers’ professional growth and strengthen school leaders’ capacities. Strengthening performance monitoring systems, developing regionally adaptive strategies tailored to local needs, and improving coordination between policy and implementation are also highlighted. In conclusion, effective and coherent execution of strategic planning and implementation processes is essential to ensure sustainable progress in education.