Sustainable Cities Research Articles

Urban Built Environment as a Predictor for Coronary Heart Disease—A Cross-Sectional Study Based on Machine Learning

The relationship between coronary heart disease (CHD) and complex urban built environments remains a subject of considerable uncertainty. The development of predictive models via machine learning to explore the underlying mechanisms of this association, as well as the formulation of intervention policies and planning strategies, has emerged as a pivotal area of research. A cross-sectional dataset of hospital admissions for CHD over the course of a year from a hospital in Dalian City, China, was assembled and matched with multi-source built environment data via residential addresses. This study evaluates five machine learning models, including decision tree (DT), random forest (RF), eXtreme gradient boosting (XGBoost), multi-layer perceptron (MLP), and support vector machine (SVM), and compares them with multiple linear regression models. The results show that DT, RF, and XGBoost exhibit superior predictive capabilities, with all R2 values exceeding 0.70. The DT model performed the best, with an R2 value of 0.818, and the best performance was based on metrics such as MAE and MSE. Additionally, using explainable AI techniques, this study reveals the contribution of different built environment factors to CHD and identifies the significant factors influencing CHD in cold regions, ranked as age, Digital Elevation Model (DEM), house price (HP), sky view factor (SVF), and interaction factors. Stratified analyses by age and gender show variations in the influencing factors for different groups: for those under 60 years old, Road Density is the most influential factor; for the 61–70 age group, house price is the top factor; for the 71–80 age group, age is the most significant factor; for those over 81 years old, building height is the leading factor; in males, GDP is the most influential factor; and in females, age is the most influential factor. This study explores the feasibility and performance of machine learning in predicting CHD risk in the built environment of cold regions and provides a comprehensive methodology and workflow for predicting cardiovascular disease risk based on refined neighborhood-level built environment factors, offering scientific support for the construction of sustainable healthy cities.

Breaking Spatial Constraints: A Dimensional Perspective-Based Analysis of the Eco-Efficiency of Cultivated Land Use and Its Spatial Association Network

Global urbanization has caused enormous challenges that seriously threaten ecological security and the food system. Thus, there is a need for finding an optimal solution for the eco-efficiency of cultivated land use (ECLU) that can promote the development of new-type urbanization, while ensuring the sustainable utilization of limited cultivated-land resources. The quantitative system of multi-scale ECLU used in existing studies is inadequate; it is necessary to establish a measurement system from the perspective of geographical spatial relationship that uses evaluation as a key basis for management. In this study, we considered the Changchun Metropolitan Area and a representative urban–rural transition area as the target regions and customized new ECLU evaluation systems for different scales. The super slack-based measure and gravity and social network analyses methods were applied to evaluate the ECLU and explore the structural characteristics of its spatial association network. The average ECLU value for the Changchun Metropolitan Area was 0.974; the results indicated that most of the study area was eco-efficient. The value of ECLU for the urban–rural transition area varied from 0.022 to 1.323; thus, the highly efficient cultivated land was mainly distributed around the urban built-up area. The spatial association network of ECLU revealed that the overall spatial correlations were relatively weak, with a significant “bipolar” division of ECLU; furthermore, the network hierarchy and stability needed improvement. Moreover, we noted distant attraction capacity and siphoning effects outside regional boundaries. In the Changchun Metropolitan Area, it manifested as a monocentric radiation, with Changchun City as the center. In the urban–rural transition area, the cultivated land in proximity to the newly built urban area was more likely to experience spatial spillover. These findings have important implications for strengthening land-use management and advancing sustainable agricultural development for new-type urbanization. Our study can be used by policymakers and stakeholders to design sustainable urban cities, while improving land-use management and optimizing resource use.

Metropolitan Construction Carbon Emission Efficiency: An Integrative Static-Dynamic Analytical Framework

Abstract Taking urgent action to combat climate change and promote sustainable cities are part of the 17 Sustainable Development Goals, which demand immediate action from all countries. Enhancing the carbon emission efficiency of the construction industry (CICEE) from the "static-dynamic" perspective is crucial in addressing climate change. This study utilized the super slack-based measure model to analyze static efficiency. The Malmquist-Luenberger index model, multiple non-linear regression model, and principal component analysis were used to research the driving factors dynamically. Factors included technical change (TC), pure technical efficiency change (PEC), and scale efficiency change (SEC), which were subdivided into 21 variables. The panel data was from 11 cities in Zhejiang from 2007 to 2019. The results indicated that the static efficiency values were generally effective, but in 2019, more than half of the cities experienced an average decrease of 52%. Efficiency levels were higher in northern Zhejiang and lower in the southeastern region. CICEE values over one were primarily attributed to high TC levels and stable PEC and SEC conditions. Additionally, a generalized framework for improving CICEE was constructed, assisting policymakers in identifying reasons for low CICEE and providing targeted strategies to reduce emissions and increase efficiency.

Territorial sustainability and the right to housing: a path to sustainable development and urban resilience

Sustainable territorial development, management of the built environment, and the right to housing are directly related, based on a holistic view of sustainability in our cities, as urban sustainability concerns a set of environmental, economic, and social factors. Thinking about sustainable cities means thinking about development and guaranteeing the right to the city and housing for all, so that the use of natural resources is rational, based on preservation and climate justice. This article[1] seeks to analyze one of the largest urban occupations in the interior of São Paulo, the Renascer Community, an area of extreme social and environmental vulnerability, in which around 300 families live without minimum urban infrastructure and basic sanitation. The product of this study will be a survey of the area, carrying out a permacultural project as a proposal for environmental recovery of the degraded area and self-management of the community, based on the circular economy. In addition, urban planning guidelines will also be proposed that seek to work in an integrated manner with the permacultural project to provide an urban infrastructure capable of meeting the community's needs and promoting territorial development. [1] This article is based on the results of the author's undergraduate thesis.

Social Media and Artificial Intelligence for Sustainable Cities and Societies: A Water Quality Analysis Use-case

Crowd-sourcing has been widely explored for monitoring and feedback on infrastructure and services, such as air and water quality analysis. However, the traditional methods of crowd-sourcing for feedback and analysis of water quality, such as offline and online surveys, have several limitations, such as the limited number of participants and low frequency due to the labor involved in conducting such surveys. Social media analytics could overcome these challenges by providing a more sustainable and cost- effective water quality monitoring and analysis tool. This paper explores the potential of social media analytics in such applications by proposing a Natural Language Processing (NLP) framework to automatically collect and analyze water-related posts from social media for data-driven decisions. The proposed framework is composed of two components, namely (i) text classification, and (ii) topic modeling. For text classification, we propose a merit-fusion-based framework incorporating several Large Language Models (LLMs) combined in a late fusion method with optimal weights. In topic modeling, we employed the BERTopic library to discover the hidden topic patterns in the water-related tweets. We also analyzed relevant tweets originating from different regions and countries to explore global, regional, and country-specific issues and water-related concerns. We also collected and manually annotated a large-scale dataset, which is expected to facilitate future research on the topic.

Urbanization and Urban Sprawl in the Post-Colonial Era Douala City, Cameroon

The history of the port city of Douala spans pre-colonial period, colonial period of the Germans and French occupation, the post- colonial era and the contemporary situation with continuous occupancy of the coastal environment. This article looks at the relationship between the history of the city of Douala to the resulting urban situation focusing on governance structure as well as rapid urbanization. The findings show that governance structure allowing for a duality of modern political system and traditional cultural system of kingships and chiefdoms has an effect to the resulting urban sprawl. Moreover, rapid urbanization under this condition has an overall impact to the challenges resulting from urban sprawl including development of settlements that do not have basic services. Developing comprehensive urban planning policies that prioritize sustainable and green building practices and transport systems, promoting the use of locally sourced building materials, use of technology to encourage generation of renewable energy, encouraging a broader participation of local communities in the planning and development of the city are some possible interventions recommended to ensure a more sustainable and resilient city of Douala.

Expropriation of real estate - key tool in achieving sustainable cities and communities

This article presents an analysis of the issues related to the emergence of the need for expropriation of real estate as a principal instrument for the creation of sustainable cities and communities. Therefore, following the analysis, it can be concluded that with the signing of the Association Agreement with the European Union by the Republic of Moldova, it is necessary to develop the country according to European standards. Consequently, an important component of the Sustainable Development Objective is the development of infrastructure. The development of infrastructure inevitably entails the expropriation of real estate for the construction of technical and public utilities, as well as road networks. The quality of road infrastructure, the quality of water supply, and the quality of electricity supply at the international level were subjected to analysis. Given that all infrastructure development projects are financed with foreign funds, an analysis was conducted of the volume of investments allocated by the European Bank for Reconstruction and Development (EBRD) and their distribution. In order to gain insight into the current state of affairs in Moldova, an investigation was conducted into the provision of technical building infrastructure elements by the country's development regions. It was found that, at this time, investments are required for infrastructure development, as a significant proportion of localities lack the necessary water supply and sewerage networks, as well as natural gas (see Table 1). It thus follows that the principal instrument for achieving these objectives is the expropriation of real estate for public utility.

Rola miast w strategiach i procesach rozwojowych UE

THE ROLE OF CITIES IN THE EU’S STRATEGIES AND DEVELOPMENT PROCESSES: AN EXAMPLE OF POLISH COASTAL CITIES The aim of this article is to identify the role of cities in the process of Europeanisation. Particular attention is paid to relatively under-researched local entities, such as coastal cities, which primarily fulfil functions related to the environment, spatial planning, housing, tourism and logistics. The article highlights the growing role of cities in the Europeanisation process, influenced by both internal (top-down, bottom-up) and external (ad extra) factors. The research objective was achieved by using the Multi-Level Governance (MLG) concept and research methods specific to the social sciences, including historical (logographic) and civilisation studies (spiral development), as well as new institutionalism in a sociological context. The operationalisation of these approaches was carried out using Griffinger’s concept (smart cities) and the SDG paradigm, in particular Goal 11 (Sustainable cities and communities).

KAJIAN PERKEMBANGAN POLA RUANG FISIK SPASIAL PERMUKIMAN KUMUH DI KAWASAN KARYA MAKMUR, DENPASAR

A livable settlement is a target within the Sustainable Development Goals (SDGs), aimed at creating resilient, inclusive, safe, and sustainable cities and communities. The Karya Makmur area in Denpasar is one of the regions facing significant slum settlement issues. This study aims to identify spatial and physical changes in the area over the past 18 years (2006-2023) and uncover the factors driving the development of slum settlements in this region. A qualitative approach was used, combining map overlay analysis (superimposed analysis) with field data validation. Results indicate that Karya Makmur has undergone major transformations in land use patterns, buildings, and circulation, while showing minor changes in settlement characteristics. The densification process driven by urbanization is identified as the primary factor contributing to the rapid growth of slum areas in this region. This research aims to contribute to future efforts in slum area improvement and planning

Cross-Cultural Consumer Lifestyles and Sustainable Tourism in Rural Communities in Palembang Indonesia

Objective: To investigate how cross-cultural consumer lifestles influence rural tourism with the aim of evaluating the effectiveness of sharing economy knowledge partnerships (SEKPs) aimed at achieving UN’s Sustainable cities and communities goal (SDG 11) by transforming remote rural communities into sustainable tourism destinations in Indonesia. Theoretical Framework: Draws on the concepts of consumer lifestyles, rural tourism, sharing economy, postcolonialism, cross-culturalism, sustainable cities and communities, to development a conceptual framework for the study. Method: We adopt mixed research designs, involving questionnaire survey, observations, and semi-structured interviews between February-March 2022 in Indonesia. We asked participants about their willingness to collaborate to develop tourism in rural communities. The data collected was subjected to SPSS multiple regression and NVivo thematic content analysis. Results and Discussion: We identified three factors influencing consumer lifestyles relating to UN’s SDG11: ‘collectivism’, ‘strategic orientation’, and ‘power-relationship’. We discussed these relational factors under seven thematic findings: ‘performance orientation’, ‘thinking strategically’, ‘anxiety tolerance’, ‘integrative relationship’, ‘gender balance’, ‘relational tendency’, and ‘market dynamism’. Research Implications: The findings have implications for theory and practice in the field of sustainable tourism destination development, considering the urgency for achieving SDG11. Future research would include a wider range of stakeholders in Indonesia and other Southeast Asia countries to enhance the generalisability of the findings. Originality/Value: The adoption of a Postcolonial lens and a Cross-cultural perspective help to clarify the concepts of consumer lifestyles, the role of SEKPs, and importance of achieving UN’s SDG11 in the transformation of rural communities into sustainable tourism destinations in Palembang, Indonesia.

An explainable AI framework for spatiotemporal risk factor analysis in public health: a case study of cardiovascular mortality in South Korea

ABSTRACT Understanding environmental disease risk factor analysis at the district level is essential for gaining valuable insights into regional disease variations, offering a broader perspective compared to individual-level studies. Recently, explainable artificial intelligence (XAI) has received increasing attention in the analysis of factors affecting public health. However, previous purely data-driven XAI-based risk factor analyses faced challenges in capturing regional effect of environmental variables, leading to confusion regarding key spatiotemporal risk factors. Therefore, this study proposes a framework that includes two complementary XAI-based risk factor analyses following two assumptions. Regionally rescaled environmental variables must account for the unequal effects on environmental factors, which are likely influenced by variations in adaptation capacity to weather conditions and differences in exposure-response relationships to air pollutants. District-level disease distribution highlights geographic disparity in sociodemographic vulnerability, whereas temporal variation in diseases by district underscores temporal environmental impacts. Based on these two hypotheses, we rescaled environmental variables using two complementary schemes: one that employs the district-level disease distribution as the target variable, and another that utilizes the temporal residual of the disease within each district. We evaluated this framework by analyzing the association between cardiovascular age-standardized mortality rate (CVD-ASMR) and various risk factors in South Korea from 2010 to 2019, using high-performing random forest and light gradient boosting models with additive Shapley explanation. Compared to previous purely data-driven XAI-based analyses, the proposed schemes achieved significantly better results in capturing regional exposure-response relationships. In two complementary schemes, the most explainable factor to districts with high CVD-ASMR was low education level related to sociodemographic vulnerability, whereas the most explainable factors to high temporal CVD-ASMR patterns were low greenness and high air pollution levels. In addition, the two complementary schemes enabled us to reasonably analyze the interaction effect of the two risk factors, i.e. temperature and air pollutants. Furthermore, high CVD-ASMR and its high temporal variation were observed in situations of high sociodemographic vulnerability with poor air quality. These findings provide insightful public health planning for sustainable cities and society by pinpointing high-risk areas and tailoring strategies to address regional environmental challenges.

The Contribution of Biomass Energy on Urban Sustainable Development: Opportunities and Challenges

This paper examines the biomass energy issue, particularly its potential and problems in urban sustainability development. With the increase in demand for energy worldwide and sources of traditional fossil fuels gradually dwindling, biomass and other new and sustainable sources become more critical. A qualitative approach is taken to develop the framework, considering literature reviews and content analysis as the techniques employed. The results highlight the potential of biomass in meeting energy demands at the global scale but simultaneously stress the need for would-be expertise management to leverage the potential. The advantages of biomass energy include but are not limited to the enhancement of economic development, environmental upgrading, and boosting energy security by decreasing the dependence on fossil fuels. Land allocation disputes and negative energy balance issues complicate the situation, but recent technologies have eliminated such helpless considerations. The policy and planning implications show that such biomass energy potential cannot be fully exploited without government policy support, infrastructure investment, and international cooperation. This research tries to show above all that, despite the limitations, biomass energy provides significant benefits for city sustainability through the diversification of energy supply, intending to achieve goals compatible with global sustainable development. Areas for future research are provided, leaning toward more quantitative and empirical research to solve problems and verify theories. In fact, cities need to use biomass energy with ecological and equitable perspectives in mind.

Overcoming Barriers to Sustainable Green Transportation in Ho Chi Minh City: A Pathway Toward Achieving SDGs 11 and 13

Ho Chi Minh City (HCMC), Vietnam’s largest urban center, is home to over 9 million people and faces significant challenges due to rapid urbanization and the heavy reliance on personal vehicles. Over 95% of urban passenger transport in HCMC relies on high-emission cars, contributing to severe air pollution and slowing progress toward the United Nations Sustainable Development Goals (SDGs). Greening HCMC’s transport system is essential to reducing emissions and achieving SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action). Despite ongoing efforts, many barriers continue to hinder this transition. This paper aims to identify and prioritize these barriers using the fuzzy TOPSIS method. The results highlight limited infrastructure investment, a lack of charging stations, and unclear policies as the top obstacles. Other challenges include poor service quality, dependence on private vehicles, low community awareness, high fuel prices, and the cost of green vehicles. These findings offer a foundation for proposing solutions and prioritizing actions to build an eco-friendly transport system. This would directly support the SDGs related to sustainable cities, climate action, and public health. A thorough analysis of these barriers and their impact is vital to expedite and enhance the “greening” process by focusing on factors with significant and decisive influence.

Investigating the urban eco-environmental quality utilizing remote sensing based approach: evidence from an industrial city of Eastern India

Urbanization, coupled with industrialization, leads to both economic growth and exponential urban growth, resulting in deteriorating environmental quality in urban areas, which poses a significant threat to the sustainability of cities. Hence, to restore biodiversity and ensure regional sustainability, it is necessary to immediately evaluate the eco-environmental quality of urban areas. The present research investigates the spatio-temporal changes in urban eco-environmental quality of the Asansol industrial city using an integrated ‘Urban Eco-Environmental Index’ (UEEQI) developed utilizing the Google Earth Engine platform and a remote sensing-based approach. The study used four spectral indices, including Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Normalized Difference Built-up Index (NDBI), Normalized Difference Bareness Index (NDBaI), along with Land Surface Temperature (LST) (as a thermal index), derived from the remote sensing data to measure environmental quality. Global Moran’s I and LISA were used to quantify spatial autocorrelation, showing the clustering of similar values or outliers of UEEQ within geographic space. The findings showed that high mean values of NDBI and NDBaI contributed to a lower mean UEEQI value of 0.38 in 2021 compared to previous decades. The spatio-temporal distribution of UEEQI showed that the ‘Very Poor’ category had grown from 0.06% in 1991 to 2% in 2021, while the ‘Poor’, ‘Good’, and ‘Excellent’ categories had declined. Over the 30 years, the UEEQI showed a rising trend of ‘Highly Degraded’ and ‘Degraded’ areas while decreasing the trend of ‘Improved’ or ‘Highly Improved’ environmental quality in the city. Moran’s scatter plot illustrated a highly positive clustered pattern of UEEQ across the city. Hotspots were mainly found in urbanized areas that had an “Average” urban eco-environment quality. Conversely, areas covered with bare surfaces, fallow lands, and brickfields were recognized as Coldspots. This study is crucial for determining specific regions of declining environmental quality and encourages local authorities and decision-makers to integrate eco-environmental conservation zones into city planning to foster healthier, more resilient, and sustainable cities.

Smart and Sustainable Doha? From Urban Brand Identity to Factual Veracity

Doha, the capital of Qatar, is the country’s administrative, economic, and political hub. With most of Qatar’s population residing in the metropolitan area, Doha effectively functions as a city-state. While the rapid growth of this Gulf metropolis is often celebrated as an emerging center of economic and cultural activity, the subtle yet crucial socio-cultural influences shaping its development as a rentier city-state are frequently overlooked in the existing literature. This research article explores the unique challenges rentier cities like Doha face in becoming truly smart and sustainable. Using a case study approach, the analysis draws from secondary data sources, including city reports, policy documents, and academic studies. By examining publicly available data and Doha’s urban planning history, the article identifies the critical issues and challenges the city faces, particularly following the 2022 FIFA World Cup. It reviews existing planning policies and offers insights into current initiatives and future directions aimed at achieving smart and sustainable development. The findings suggest that while Doha has made considerable progress, more inclusive and comprehensive policies are needed to move beyond entrenched socio-cultural influences and align the city’s growth with its broader sustainability and smart city goals.

The Coupling Coordination Relationship Between Urbanization and the Eco-Environment in Resource-Based Cities, Loess Plateau, China

Resource-based cities face numerous sustainability challenges, making the coupled and coordinated relationship between urbanization and the eco-environment critical for sustainable development strategies. The Loess Plateau is an essential energy base and ecologically fragile area in China, holding unique and significant research value. This research employed the Remote Sensing Ecological Index (RSEI) and the Compound Night Light Index (CNLI), based on MODIS and night light data, to investigate the socio-economic development and eco-environmental changes across 25 resource-based cities on the Loess Plateau (LP) in China over the past 20 years. The Coupling Coordination Degree Model (CCDM) and Multi-Scale Geographically Weighted Regression (MGWR) were utilized to assess the relationship between urbanization and ecological factors. The average RSEI values for these cities ranged from 0.4524 to 0.4892 over the 20 years, reflecting an upward trend with a growth rate of 8.13%. Simultaneously, the average CNLI values ranged from 1.5700 to 6.0864, with a change of 4.5164. Over the past two decades, all cities in the study area experienced rapid urbanization and ecological development. The correlation between urbanization and ecological factors strengthened, alongside an increasing spatial heterogeneity. While the coupling coordination relationship in most cities showed improvement, many remained within the low to middle grades. These findings enhance the understanding of the intricate relationships between urbanization and ecology, offering valuable insights for policy-making aimed at creating sustainable and livable resource-based cities.

Quantitative study on the relationship between land use and land cover and diatom community in urban streams.

The study of the impact of urbanization on river ecosystems is an important part of constructing sustainable cities. How to quantitatively study the impact of urbanization on river ecosystems is the difficulty of urban ecological research. This study quantitatively investigated the effects of LULC on water quality and diatom assemblages in urban streams by correlation analysis, multivariate analysis, and path analysis. The results showed that (1) the percentage of LULC type in buffer 600m of reference stream sites is significantly different from that of urban stream sites. In reference sites, the average percentage of green was 94.2%, barren 3.3%, and impervious surface 2.5%. In urban upstream sites, the average percentage of impervious surface was 63.1%, green 32.8%, water 3.3%, and barren 0.8%. In urban downstream, the average percentage of impervious surface was 59.0%, green 36.5%, water 2.7%, and barren 1.8%. (2) One-way analysis results showed that water quality variables were significantly differences among the sites. The correlation analysis results indicated that LULC had a significant influence on water quality. Green had a significant negative correlation with high concentrations of NO3-N, NH4-N, and Cond. but positively correlated with MSUBST. RDA results showed that the selected water quality variables, MSUBST, and LULC types have a significant impact on the spatial patterns of the diatom assemblages. (3) Path analysis results showed that both LULC types and water quality variables exerted significant effects on diatom assemblages. This study first clarifies the quantitative relationships among LULC types, water quality, and diatom assemblages in the Beijing area. And green land was positively correlated with water quality and river ecosystems. We believed that increasing green space in urban core areas is an effective measure for improving water quality and restoring river ecosystems in the urban area.

A novel methodology for assessing resources and environmental carrying capacity with emphasis on ecosystem services: A multi-disciplinary approach to sustainable urban planning

Due to increased human activities, urban areas face challenges in maintaining their environment and natural resources in support of development. As a result, it is necessary to plan according to the availability of resources and the state of the environment to achieve sustainable development. For this purpose, Carrying capacity (CC) can be used to assess the sustainability of cities as complex Social-Ecological Systems (SES). By emphasizing Ecosystem Services (ESs) and regional thresholds, this paper proposes a novel methodology to evaluate Urban Resources and Environmental Carrying Capacity (URECC). At first, an integrated simulation model is developed by combining an ecosystem services simulation model, a surface and ground water simulation model, a priority-based water allocating model, and a demands (i.e., water, food, and energy) estimation model. To evaluate URECC, various measurement indicators are developed and combined with a multi-stage decision-making (MSDM) method. Also, the decision-making sequences of management strategies and climate change scenarios are used to evaluate changes in the future. Based on the results, in the two base stages (2013–2016) and (2017–2020), without applying strategies, the average value of pressure-support, distance, and composite indices changed by +1.5%, −75.6%, and −66.7%, respectively, indicating a decrease in the CC. The future period (i.e., 2021–2040) was divided into four-year decision-making stages. According to the results, with the implementation of top sequences of strategies, the average values of pressure-support, distance, and composite indices would surpass those of maintaining the current trend by 49.4%, 123.5%, and 63.7%, respectively. In conclusion, management actions such as the development of semi-centralized and decentralized wastewater treatment networks, the simultaneous expansion of green space and built-up land, the implementation of artificial recharge, the improvement of irrigation efficiency, the management of urban water consumption, and the use of vegetation with low to medium water demands are effective for strengthening the URECC.

Examining the Influence of Locus of Control on Citizenship Behavior: The Mediating Role of Naturalistic Intelligence in Urban Sustainability

This study aims to examine the relationship between Locus of Control (LOC), Naturalistic Intelligence (NI), and Behavioral Citizenship (BC) in the context of sustainable cities in Indonesia. The primary objective is to investigate how LOC influences BC and the mediating role of NI in this relationship. The research was conducted in Tanjung Priok, North Jakarta, with a sample of 200 participants. Data were collected using a questionnaire with a 5-point Likert scale, and analysis was performed using Path Analysis with SmartPLS software. The key findings demonstrate that LOC positively impacts both NI and BC, with NI serving as a significant mediator between LOC and BC. Individuals with a high sense of control over their lives and strong naturalistic intelligence are more likely to engage in pro-environmental and community-oriented behaviors. These findings underscore the importance of psychological factors in promoting sustainable citizenship behaviors. The study contributes to the literature by highlighting the role of naturalistic intelligence as a crucial mediator in the relationship between personal control and active citizenship. It also offers practical insights for urban policymakers and community leaders, emphasizing the need to incorporate environmental education and psychological empowerment into urban sustainability programs to foster greater community engagement and responsibility.

Global Healthy and Sustainable City Indicators: Collaborative development of an open science toolkit for calculating and reporting on urban indicators internationally

Measuring and monitoring progress towards achieving healthy, equitable and sustainable cities is a priority for planners, policymakers and researchers in diverse contexts globally. Yet data collection, analysis, visualisation and reporting on policy and spatial indicators involve specialised knowledge, skills, and collaboration across disciplines. Integrated open-source tools for calculating and communicating urban indicators for diverse urban contexts are needed, which provide the multiple streams of evidence required to influence policy agendas and enable local changes towards healthier and more sustainable cities. This paper reports on the development of open-source software for planning, analysis and generation of data, maps and reports on policy and spatial indicators of urban design and transport features for healthy and sustainable cities. We engaged a collaborative network of researchers and practitioners from diverse geographic contexts through an online survey and workshops, to understand and progressively meet their requirements for policy and spatial indicators. We outline our framework for action research-informed open-source software development and discuss benefits and challenges of this approach. The resulting Global Healthy and Sustainable City Indicators software is designed to meet the needs of researchers, planners, policy makers and community advocates in diverse settings for planning, calculating and disseminating policy and spatial urban indicators.