Sustainable Development Planning Research Articles

Blue Economy and the Impact of Industrialisation on Sustainable Livelihoods: A Case Study of Fisheries in the North Coastal Region of Java

This research explores the impacts of the blue economy and industrialisation on sustainable livelihoods in the coastal areas of the North Coast of Java, with a particular focus on the fisheries sector.The main objective of this research is to analyse how changes in blue economy practices, which include sustainable marine resource management approaches, interact with industrialisation processes and their impact on the survival of local fishing communities.The research method used was qualitative with a case study approach, where data was collected through in-depth interviews with fishermen, government officials, and relevant stakeholders, as well as direct observation in the field. Data analysis was conducted using thematic analysis techniques to identify patterns and significant relationships between the factors involved.The results of this study show that industrialisation in the coastal areas of Java's North Coast has vital and complex impacts on the sustainable livelihoods of local fishing communities. On the one hand, industrialisation provides new economic opportunities, such as jobs in the fishing and manufacturing sectors, which can increase community income. However, on the other hand, negative impacts on the aquatic environment due to industrial activities and overexploitation of natural resources threaten the sustainability of the marine ecosystem, which is the main source of livelihood for fishermen.The managerial implications of these findings emphasise the need to integrate blue economy policies with the maturity of sustainable industrial development planning. Policy development that accommodates the needs of local ecosystems and fishing communities, with a pattern of regulating marine protected zones and supporting the shift to environmentally friendly fisheries practices, is key to ensuring the sustainability of fishers' livelihoods and healthy coastal ecosystems. This research provides important insights for policy makers and practitioners involved in marine fisheries resource management and industry development in coastal areas.

Balancing Economic Growth and Environmental Conservation: Assessing Supportive Policies in Resources-Based Cities in China

This study investigates the impact of comprehensive reforms on the economic development and environmental protection of resource-based cities in China within the context of the `National Sustainable Development Plan for Resource-based Cities (2013–2020)’. Employing a difference-in-differences methodology, we find that these reforms not only bolster economic stability but also significantly enhance urban ecological environment, resulting in a win–win outcome for economic prosperity and environmental preservation. Our analysis reveals that the reforms drive sustained economic growth and ecological enhancement by downsizing industries, adopting green technologies, and optimizing industrial composition. Moreover, we identify that these impacts are more pronounced in mature and declining cities and in regions with robust official promotion strategies and stringent environmental regulations. These findings provide valuable insights for addressing the “resource curse” within social systems and for formulating policies that balance stable economic growth and environmental protection in resource-based cities.

Integrating Ecosystem Service Values into Urban Planning for Sustainable Development

Integrating Ecosystem Service Values into Urban Planning for Sustainable Development

An Overview of Sustainable Desalination with Freezing Crystallization: Current Development, Future Challenges, and Prospects

As global demand for freshwater grows, seawater desalination has become one of the most promising methods for obtaining freshwater. Many coastal nations have included it in their sustainable development plans and are actively advancing related technologies. Compared with traditional desalination methods, such as distillation and membrane-based desalination, seawater freezing desalination offers the benefit of producing large amounts of freshwater at lower costs. This study provides an overview of the main methods and principles of seawater freezing desalination and summarizes the latest research progress. This paper also discusses experimental and simulation studies of different principles. Current research shows that both direct and indirect seawater freezing desalination technologies have become relatively mature, laying a foundation for practical applications. Hydrate-based desalination, eutectic freezing technology, and vacuum freezing technology offer cost-reduction benefits, but existing technologies have limitations, making these areas hot topics in research. Additionally, this paper discusses the experimental progress and simulation methods associated with this, elaborates upon, and analyzes the freezing crystallization process and desalination efficiency from the perspective of the bottom layer of crystal growth, offering valuable insights for future research. It concludes by summarizing and predicting the development of these technologies, emphasizing their great potential due to their low-cost and sustainable features.

Spatiotemporal dynamics of LULC change and implications for sustainable urban growth in Saudi Arabia

This study investigates the spatiotemporal dynamics of land use and land cover (LULC) change in Saudi cities between 2013 and 2023. Using Landsat satellite imagery and a Maximum Likelihood Classifier, LULC changes are analyzed in nine cities to understand the impact of Saudi Arabia’s rapid urbanization following the oil crisis. The objectives are: (1) to evaluate the LULC changes in nine cities between 2013 and 2023; (2) to explore the spatiotemporal patterns of LULC changes in this period; and (3) to interpret the urban expansion that occurs in Saudi Arabia in the light of the kingdom sustainable development plan. The results identifiy four primary LULC change models: Urbanization, Vegetation Recovery, Land Degradation, and Ecological Transition Models. The Urbanization and Land Degradation Models determine Saudi Arabia’s urban growth trend, posing significant challenges to sustainable development. Most cities experienced substantial increases in impermeable surfaces and developed lands, while concurrently losing high terrain and barren areas. However, the small cities showed lower urbanization and land degradation rates than major cities, showing an opportunity to sustainably grow by adopting sustainable planning approaches. The study’s findings show that more targeted and comprehensive policies are needed to address the challenges of urbanization and land degradation, mitigate environmental impacts, and ensure long-term resilience. It underscores the importance of considering Ecological Urbanism in urban development plans.

Spatial Coordination Analysis and Development Methods of the Catering Sector in Yongkang City

The catering sector is recognized as a crucial driver for stimulating domestic consumption and fostering sustained economic growth. A scientifically informed spatial planning of the catering sector in county-level cities can help mitigate the overconcentration or excessive dispersal of resources, thereby enhancing the efficiency of land and commercial resource utilization, reducing waste, and promoting sustainable development within a county’s economy. This study focuses on Yongkang City, located in central Zhejiang Province, as a case study. Using Python 3.1 software to extract point-of-interest (POI) data, spatial analysis techniques such as standard deviation ellipses and kernel density estimation are employed to elucidate the spatial distribution characteristics of the catering sector, comprehensive transportation, and public services in Yongkang City. Furthermore, a coupling coordination degree model is utilized to quantify the coupling coordination degrees between the catering sector and comprehensive transportation (D1), as well as between the catering sector and public services (D2), ultimately assessing the overall coupling coordination degree among the three sectors (D3). Based on the analysis results, the coupling coordination degrees are categorized into five levels, followed by a detailed evaluation of the catering sector’s development across different subdistricts. The findings indicate a certain degree of spatial imbalance in the distribution of the catering sector in Yongkang City, with the western region exhibiting a more favorable development trajectory. Notably, Dongcheng Subdistrict achieved the highest coupling coordination degree (0.993), while the northern region, hindered by underdeveloped economic conditions and limited transportation infrastructure, exhibited the lowest coordination degree (0.098). Considering the unique developmental characteristics and current conditions of each subdistrict, this study advocates for the formulation of a long-term sustainable development plan for the catering sector in Yongkang City. The findings of this research may offer valuable insights for other regions and countries, thereby promoting the sustainable advancement of the catering sector.

Transportation connectivity development strategy in the Wakatobi islands, Indonesia

This study aims to analyze connectivity or accessibility between regions in Wakatobi islands, both within and between islands, to understand the available transportation network. Based on an understanding of the dynamics of connectivity, it is expected to provide a solid foundation for the development of more efficient and sustainable transportation infrastructure in the future. A combination of qualitative and quantitative approaches is used to explore data more comprehensively and accurately. The two primary airports and several ports are still insufficient in enhancing connectivity for both the residents and tourists within the archipelago. Improving road, sea, and air transportation networks is a necessity and expectation to improve connectivity between regions. An analysis of accessibility potential provides an overview of transportation costs and expensive and long travel fares. There are several needs that need to be met in the form of the revitalization of local ports, the development of the concept of Air Buses between crossing ports, optimizing routes between airports, and the implementation of Bus/BRT (Bus Rapid Transit) on each island with feeder lines. Furthermore, the development of connectivity in Wakatobi must consider various alternative modes of transportation, increasing service frequencies, and developing supporting infrastructure. This conclusion is the basis for the preparation of a holistic and sustainable connectivity development plan in the Wakatobi archipelago.

Assessing Tourism Resources: Inputs for Municipal Tourism Development Plan in Libona, Bukidnon

The COVID-19 pandemic presented a challenge to global tourism, prompting a shift towards local tourism. It presented an opportunity in Libona, Bukidnon as means for economic recovery. This study aims to establish a comprehensive tourism profile for the municipality of Libona, Bukidnon, to support sustainable tourism development planning. Utilizing a combination of primary and secondary data, including interviews, field visits, and stakeholder consultations, the study assesses the current state of tourism enterprises, infrastructure, market profile, and human resources in the region. Key areas for development and strategic interventions are identified through a SWOT analysis. The findings emphasize the need for accurate tourism data and informed planning to balance economic growth with the preservation of socio-cultural values and environmental sustainability. The study provides actionable recommendations to enhance the local tourism sector, ensuring long-term benefits for the community and stakeholders.

Assessing and gauging the carbon emission efficiency in China in accordance with the sustainable development goals

In light of the growing urgency of climate change, carbon emissions reduction has emerged as a pivotal concern within global governance. In this paper, we take carbon emission efficiency (CEE) as the research object to characterize the relationship between economic, social, and environmental development in the context of the Sustainable Development Goals (SDGs). According to the regional division standard of eight comprehensive economic zones in China, this paper analyzed the spatial differences, evolutionary characteristics, and influencing factors of CEE in 257 Chinese cities over the period 2003–2019. The analysis conducted the Dagum Gini Coefficient, Markov Transition Probability Matrix, and geographically and temporally weighted regression model (GTWR). The results demonstrate that: (1) The CEE of Chinese cities exhibits an upward trajectory. (2) The inter-differences among the eight comprehensive economic zones represent the primary spatial source of CEE divergence. (3) The CEE of Chinese cities is a staged process of gradual enhancement with spatial spillover effects. (4) Environmental regulation, energy consumption intensity, and green finances are significant factors affecting CEE, and the direction and intensity of their influence have distinct spatial heterogeneity. Ultimately, this paper proposes measures to narrow the development gap between regions and enhance the CEE across the region. Meanwhile, implementing regional refinement management and formulating differentiated regional sustainable development planning.

Predicting well productivity in cratonic regions using remote sensing lineaments and weathered cover thickness: A case study from Bobo Dioulasso, Burkina Faso

In western African cratonic regions, fractured crystalline bedrock, Neoproterozoic sedimentary covers, and regolith deposits constitute the most productive aquifer systems. Structural lineaments derived from remote sensing data and weathered cover thickness from borehole interpretations provide cost-effective methods for evaluating well productivity in regions with limited economic resources and hydrogeological knowledge, such as Houet province in Western Burkina Faso. Structural lineaments were interpreted using 1:200,000 Landsat TM images and 1:50,000 aerial photographs, revealing NE and NW as the most significant directions. An analysis of 101 borehole stratigraphic profiles from rural water supply program reports revealed the weathering depth and cover thickness. Borehole productivity exhibited a strong correlation with increased weathered cover thickness. Negative well results were concentrated in areas with less than 5 m of cover. In contrast, significant differences in specific yield rates were observed with greater thicknesses, ranging from 2.5 m³/d for 20 m of saturated thickness to 7.6 m³/d when the regolith reached a depth of 40 m. These preliminary groundwater exploration tools effectively target successful well sites by accounting for differing lithologies, regional tectonics, and regolith development. This approach is particularly relevant for cratonic regions with limited resources and hydrogeological knowledge, aiding in sustainable groundwater development and land-use planning.

Geospatial analysis of alarmingly increasing flood vulnerability and disaster risk within the northeast himalaya region of India

Geoenvironmetally the eastern part of the Himalaya region is highly vulnerable to flood and other natural disasters as it consists of fragmented and tectonically active geology and geomorphology, very high monsoon rainfall (>360 cm) and subsequent runoff, rugged hilly terrain with high ranges of elevation and slope, dense drainage density etc. Other hand, the unplanned developmental activities keep going and scaling up this vulnerability and risk to floods and other disasters. Addressing this burning issue, a geospatial technology-based case study of the Kohima district, Nagaland state (India), is presented here. The geospatial "technology-based" analyses employed in the study are thematic GIS mapping of flood hazard, vulnerability and risk controlling factors; and performing overlay operation using the AHP model in GIS software to generate spatio-temporal map layers of flood vulnerability and disaster risk. Results reveal that the region is under a high rate of monsoon climate change (increasing temperature, rainfall, rainy days, rainfall events and flood events with an annual rate of 0.35 %, 1.12 %, 0.36 %, 2.67 % and 4 % respectively), land use degradation (increasing built-up area with 0.60 %, annual rate decreasing forest, shrubs and water bodies with 0.80 % accumulated annual rates respectively) and demographic changes (increasing urban as well and rural population density with 0.53–2.10 % and 0.55–2.14 % respectively). Accumulated impacts of climate change, land use degradation and demographic changes causing an increase in flood hazard, vulnerability and disaster risk. Flood hazard zones and vulnerability zones extending with 0.50 % (4.89 km2) and 0.84 % (8.16 km2) annual rates respectively, subsequently the flood risk zones categorized as a moderate, high and very high potential risk, have been spreading out with a yearly rate of 0.07 % (0.65 km2), 0.13 % (1.31 km2) and 0.03 % (0.33 km2) respectively. It decreases the area under low and very low-risk zones by 0.17 % (1.63 km2) and 0.07 % (0.65 km2) annual rates respectively. Following up on these annual rates, the spatial distribution of flood hazard, vulnerability and risk zones for the next decade (2031–2040) have also been projected, revealing alarming situations, if flood disaster risk reduction (F-DRR) measures were not implemented in timely. It is strongly believed that the proposed study will be very useful for district-level planners and administrators to implement sustainable development planning, for the scientific fraternity to enhance their research work in the field of flood disaster management and for individuals for their safety in terms of life and property.

Predicting normalized difference vegetation index using a deep attention network with bidirectional GRU: a hybrid parametric optimization approach

AbstractScalable and accurate normalized difference vegetation index (NDVI) prediction is necessary to track the status of vegetation and the environment and to support proper ecological management. Herein, we present an innovative deep-learning approach to improve NDVI prediction performances by considering enhanced temporal modeling and hybrid optimization processes. The analysis is based on a core model that integrates a Bidirectional Gated Recurrent Unit (BiGRU) with the profound attention feature since the primary research incorporates the capability of complex temporal in addition to NDVI-time series value. The model performs better through a dual algorithm combining the waterwheel plant algorithm (WWPA) and statistical fractal search (SFS) named WWPASFS-BiGRU. The proposed approach is evaluated using real-world NDVI datasets, demonstrating its capability to outperform traditional models and state-of-the-art deep learning methods. Key performance metrics highlight the model’s accuracy, with a root mean square error (RMSE) as low as 0.00011, reflecting its superior predictive ability. Comparative experiments showcase the robustness of our model across different environmental conditions and geographical settings, affirming its applicability in diverse ecological forecasting scenarios. Additionally, extensive statistical validation, including ANOVA and Wilcoxon tests, confirms the model’s consistency and reliability. The effectiveness of the WWPASFS-BiGRU model is illustrated through applications in predicting NDVI trends across regions in Saudi Arabia, providing critical insights for ecosystem management and sustainable development planning.

Artificial light at night reveals hotspots and rapid development of industrial activity in the Arctic

Climate warming enables easier access and operation in the Arctic, fostering industrial and urban development. However, there is no comprehensive pan-Arctic overview of industrial and urban development, which is crucial for the planning of sustainable development of the region. In this study, we utilize satellite-derived artificial light at night (ALAN) data to quantify the hotspots and the development of light-emitting human activity across the Arctic from 1992 to 2013. We find that out of 16.4 million km2 analyzed a total area of 839,710 km2 (5.14%) is lit by human activity with an annual increase of 4.8%. The European Arctic and the oil and gas extraction regions in Russia and Alaska are hotspots of ALAN with up to a third of the land area lit, while the Canadian Arctic remains dark to a large extent. On average, only 15% of lit area in the Arctic contains human settlement, indicating that artificial light is largely attributable to industrial human activity. With this study, we provide a standardized approach to spatially assess human industrial activity across the Arctic, independent from economic data. Our results provide a crucial baseline for sustainable development and conservation planning across the highly vulnerable Arctic region.

How does the value of ecological restoration techniques affect ecosystem carbon density: A resource endowment-based perspective

In the context of carbon neutrality and carbon peaks, innovations in ecological restoration technology play a key role in carbon adsorption and maintaining ecological balance. Regional governments, tasked with formulating differentiated and rational ecologically sustainable development plans and carbon-neutral strategies tailored to various resource endowment conditions, require timely identification of the mechanisms by which ecological restoration technologies affect the carbon density of ecosystems. Based on data from 31 provinces in China from 2006 to 2021, this study employed the Spatial Durbin Model with both time and space fixed effects to examine the impact of the value of ecological restoration technologies on ecosystem carbon density under varying resource endowments. The empirical results indicate that (1) the value of ecological restoration technology has a significantly positive effect on ecosystem carbon density, particularly in neighbouring areas; (2) energy resource endowment exhibits a significantly inverted U-shaped boundary effect, whereby regions with moderate energy endowment can optimise the positive impact of ecological restoration technology; (3) the heterogeneity analysis, based on levels of regional environmental governance and forest cover, shows that in regions with less investment in environmental infrastructure and lower forest cover, ecosystem carbon density is more sensitive to the value of ecological restoration techniques, making their carbon sink effect more pronounced. This study elucidates the key role of ecological restoration techniques in enhancing carbon storage, promoting the goal of carbon neutrality, and identifying optimal pathways for increasing ecosystem carbon stocks across various regions with differing resource endowments. Moreover, it provides a reference for accelerating the achievement of carbon neutrality targets.

A Review on Sustainable Marketing Strategy for Crocs

Crocs is an American shoe brand. This study talking about how brand marketing and brand decisions have made Crocs' success, decline, and return to the masses a popular trend again. Nowadays the social economy rapid develop. various products advent more faster, the new things with creativity could always attract peoples attention. However, the society trend changed quickly, then all brands need to think about how they could expand their customer base in addition to consolidating their existing customers same as Crocs. To make a sustainable marketing strategy crocs needs to combine their brand history, the market requirement, their brand positioning, and their consumer buying behavior. Therefore, the purpose of this study is to provide a sustainable development plan for Crocs from the author's point of view through the several items of information above. The sustainable development suggestions in this paper include, but are not limited to, clarifying brand positioning and target customer groups, developing e-commerce sales channels, etc.

Communication as a Strategic Asset of Sustainable Development Planning of Rural Territorial Systems

Successful application of the communicative approach focused on the involvement of local communities in the process of planning the sustainable development of rural territorial systems greatly increases the effectiveness of planning processes. Where state management policy guarantees the participation of local communities in the process of rural territorial systems development, creates conditions for their involvement in the dialogue with local authorities, the chances of successful implementation of sustainable development plans increase significantly. The article makes an attempt to substantiate the necessity of introducing the communicative approach into the management system of rural territorial systems, as it will allow transforming the system of regional planning in Russia and achieving real breakthrough results in the sphere of development of social-ecological-economic components of rural territorial systems.

Towards Sustainable Rural Development: Assessment Spatio-Temporal Evolution of Rural Ecosystem Health through Integrating Ecosystem Integrity and SDGs

Rural ecosystem health (REH) serves as an effective metric for assessing the damage degree and stability state within rural systems and their components. It reflects the interaction and the balance among rural subsystems, emphasizing the harmonious development of resources, agriculture, environment, economy, and society that are fundamental to sustainable rural development. Most regional-scale ecosystem health assessments primarily focus on either the natural state of the ecosystem or external disturbances affecting it, often neglecting human ecological systems characterized by economic and social dimensions. Taking Chongqing as an example, we established an improved REH assessment framework by integrating ecological integrity from the perspective of a social-economy-natural compound ecosystem. Furthermore, we innovatively incorporated the Sustainable Development Goals (SDGs) into the formulation of the REH indicator system to quantitatively elucidate the spatiotemporal characteristics. The results indicated that: (1) The REH in Chongqing exhibited an evolutionary pattern characterized by a subsequent rise, maintaining values between 0.363–0.872 from 2000 to 2018. This trend reflected a distinct two-stage development characteristic, with the rural socio-economic subsystem contributing the most at 33.36%, followed closely by the rural environmental subsystem at 27.84%; (2) In 2018, the REH across the 36 districts and counties in Chongqing displayed spatial differentiation patterns described as “collapse in the west, high levels in the northeast, and localized surges”. The areas ranked from smallest to largest REH were metropolitan, western, southeastern, and northeastern areas; (3) Four levels (e.g., disease, single health, compound health, and comprehensive health) and twelve sub-levels of REH were defined using a dominant factors method. Finally, we analyzed the driving factors from four aspects of urbanization development: policy regulation, urban-rural factors flow, and regional differences. We also proposed differentiated planning and policies for sustainable rural development in Chongqing.

Research on the Practical Path of Green Finance in the Low-carbon Transformation of Smart Cities: A Case Study of the Transformation and Development of European Smart Cities

This study aims to explore the practical path of green finance in promoting low-carbon transformation of smart cities by taking the transformation of smart cities in Europe as a case study. The successful experience of smart city transformation in Europe is deeply studied through case analysis, and the application of green finance and its impact mechanism on urban transformation are discussed. The study found that green finance plays an important role in the transformation of smart cities in Europe, which promotes the transformation of cities to lowcarbon and smart direction through the practice path of policy formulation, technological innovation and sustainable development planning. This study provides a reference for the low-carbon transformation of smart cities in other regions, and has certain theoretical and practical significance for promoting sustainable urban development.

Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study

Accurate classification of rail transit stations is crucial for successful Transit-Oriented Development (TOD) and sustainable urban growth. This paper introduces a novel classification model integrating traditional methodologies with advanced machine learning algorithms. By employing mathematical models, clustering methods, and neural network techniques, the model enhances the precision of station classification, allowing for a refined evaluation of station attributes. A comprehensive case study on the Chengdu rail transit network validates the model’s efficacy, highlighting its value in optimizing TOD strategies and guiding decision-making processes for urban planners and policymakers. The study employs several regression models trained on existing data to generate accurate ridership forecasts, and data clustering using mathematical algorithms reveals distinct categories of stations. Evaluation metrics confirm the rationality and accuracy of the results. Additionally, a neural network achieving high accuracy on labeled data enhances the model’s predictive capabilities for unlabeled instances. The research demonstrates high accuracy, with the Mean Squared Error (MSE) for regression models (Multiple Linear Regression (MLR), Deep-Learning Neural Network (DNN), and K-Nearest Neighbor (KNN)) remaining below 0.012, while the neural networks used for station classification achieve 100% accuracy across seven time intervals and 98.15% accuracy for the eighth, ensuring reliable ridership forecasts and classification outcomes. Accuracy in rail transit station classification is critical, as it not only strengthens the model’s predictive capabilities but also ensures more reliable data-driven decisions for transit planning and development, allowing for more precise ridership forecasts and evidence-based strategies for optimizing TOD. This classification model provides stakeholders with valuable insights into the dynamics and features of rail transit stations, supporting sustainable urban development planning.

Strategi Perencanaan Destinasi Tukad Bindu sebagai Daya Tarik Wisata di Kota Denpasar

Tukad Bindu, a river tourism site in Denpasar, Bali, attracts a significant number of domestic tourists. However, it currently lacks a well-defined strategic plan for sustainable development, which is crucial for establishing it as a competitive tourist destination in Denpasar City. This study aims to identify the development potential along Tukad Bindu, Denpasar, Bali, using qualitative methods and SWOT analysis. The research primarily focuses on river revitalization as a catalyst for tourism, enhancing agricultural productivity, tourist attractions, and fostering active community involvement. The findings suggest that the SO (Strengths-Opportunities) strategy can be employed by maintaining river revitalization as a key driver for tourism while also boosting agricultural productivity and tourist attractions. The ST (Strengths-Threats) strategy involves empowering the community through active participation to mitigate potential threats. The WO (Weaknesses-Opportunities) strategy is facilitated by providing educational programs through the Denpasar City Environmental Service to the surrounding community. Meanwhile, the WT (Weaknesses-Threats) strategy underscores the importance of collaboration with the government and private sector to improve tourism promotion, develop cultural and agricultural tourism attractions, and ensure the sustainability of future programs. This study recommends the adoption of these strategies as concrete steps to fully leverage the development potential around Tukad Bindu, Denpasar, Bali. The successful implementation of these strategies is anticipated to positively impact tourism, agriculture, and the welfare of the local community.