Land use change is the most direct factor driving the supply and alteration of ecosystem services. This study employed the Dyna-CLUE tool to simulate future land use distributions under two scenarios—the Constrained Trend (CT) and Optimized Target-driven (OT) scenarios—based on land use data from 2010. Subsequently, their corresponding ecosystem service values (ESVs) were calculated, with the simulation outcomes revealing distinct land use layouts under each scenario. Under the CT scenario, grassland and urban areas expanded, whereas farmland and water bodies declined, reflecting a trend of urbanization at the expense of rural landscapes. In contrast, the OT scenario demonstrated a cessation of built-up land expansion, accompanied by marked increases in forest and water coverage, changes that facilitated the restoration of coastal watersheds, enhancing wetland provision and improving overall ESV. Consequently, per capita ESV increased substantially—from 1751 CNY in 2018 to 2356 CNY, matching the 2010 level—primarily due to the conversion of grasslands and farmlands into forests and wetlands. The OT scenario also improved the spatial distribution of ESVs, forming interconnected ecological zones around urban areas. The results underscore that policies restraining built-up expansion, promoting afforestation, and restoring wetlands can significantly improve ecosystem services and contribute to sustainability.

Disasters caused by natural hazards such as floods and bushfires have increasingly disrupted essential logistics networks in Australia, causing delays, financial losses, and customer dissatisfaction. The Physical Internet (PI) concept in supply chains and freight logistics, aims to address sustainability and related issues in freight transport emphasizes interconnectivity of various aspects of the logistics network. Specifically, PI has been shown to promote shared, hyperconnected logistics networks, that can enhance the resilience, efficiency, and sustainability of supply chains. This study uses the concept of various degrees of sharing within a logistics network, and its applications to existing ones, in order to improve various economic, environmental and societal objectives. A case study is presented based on Brisbane, Australia, which has seen several flooding incidents over the past several decades. The profile of these disasters was gathered and a simulation model was developed to evaluate various configurations of network design towards multiple objectives that consider the perspectives of various stakeholders. The study shows that the adoption of PI concepts has the potential to improve these identified objectives especially in the wake of increasing frequency and intensity of disasters.

Australia's electricity system is undergoing a transition, with each jurisdiction contributing to this shift. Despite progress, about 70% of Victoria's electricity is still generated from brown coal, underscoring the importance of understanding its historical development to inform future transitions. This article presents the Socio-Technical Layout (STL) framework as a graphical tool to map, diagnose, and analyse key elements of socio-technical systems, including technologies, actors, markets and energy-money flows. Applying the STL to Victoria's electricity system uncovers three development phases: emerging, public, and private; and reveals that: (i) complexity - traditionally linked to scale - depends on the lenses (technological, organisational) and viewpoint (household, system operator); and (ii) transformative actors institutionalised socio-technical solutions aligned with societal values and needs. This approach also carries implications for transition agendas. As an explanatory framework with diagnostic capabilities, STLs provide a common language to enhance participatory processes. Stakeholders can use STLs to identify areas ripe for change, test and evaluate potential modifications from different viewpoints, and identify what is needed to support them (new markets, actors). STLs can be formalised into computer models, bridging qualitative and quantitative research. STLs should be complementary to narratives and other transition frameworks, given their representational limitations.

Limiting global warming in line with the Paris Agreement requires rapid and ambitious decarbonisation of the global building and real estate (BRE) sector. This study presents the first global systematic review and structured alignment assessment of BRE decarbonisation efforts from 212 publications over the past two decades, evaluating them against six relevant alignment factors: temperature-based targets, main indicators, life-cycle scope, decarbonisation goals, target years and assessment scales. Using a multi-criteria scoring and weighting framework, the analysis reveals the evolution and prevalent shortcomings in research. Only four studies are Paris-aligned, while most efforts remain fragmented, narrowly scoped, low in ambition, or disconnected from explicit temperature limits and mid-century net zero goals. Although ambition has increased since 2015, inconsistent terminology, incomplete life-cycle scopes, small assessment scales and delayed policy uptake persist. Significant geographical disparities are evident, with Europe and Oceania leading in whole-life-cycle approaches, while Africa, South America and much of Asia remain underrepresented, despite rapid projected growth in building stocks. The findings demonstrate that current BRE decarbonisation trajectories are largely incompatible with Paris-aligned pathways. Three priority research areas are identified: harmonised definitions and ambition levels, robust data infrastructures, and scalable sector-wide frameworks to enable Paris-compatible decarbonisation within planetary boundaries. POLICY RELEVANCE The systemic misalignments and research-to-policy adoption challenges identified in this research provide policymakers with insights to set Paris-aligned emissions-reduction targets and pathways for national BRE sectors, establish sector-wide governance and support effective contributions from key stakeholders. First, international harmonisation of definitions and standards for whole-life-cycle assessment, data collection and reporting is required. Second, given that operational-emissions-only, building-level approaches are insufficient to achieve Paris-compatible outcomes, it is necessary to include embodied emissions, mandate whole-life-cycle, sector-wide assessments of the national building stock, and implement legally binding limit values, carbon budgets or decarbonisation trajectories into Nationally Determined Contributions. Third, since projected high-growth regions in Africa, South America and Asia are currently underrepresented in the literature, international policy support should focus on establishing the data infrastructures and technical expertise in these areas to ensure global climate goals are not undermined by regional data and capability gaps.

Conventional applications of the CLUE-S model rely on a static driver assumption, using driver data and their associated coefficients from a base year to simulate land-use patterns for a future target year—an approach that implicitly assumes temporally invariant human–land relationships. To address this limitation, this study introduces and compares two simulation models: the Baseline-Driven Pattern (BDP), which follows the conventional protocol by employing base-year drivers to project future land use, and the Target-Driven Pattern (TDP), which instead utilizes driver data and coefficients that correspond synchronously to the target year, thereby capturing the dynamic evolution of driving mechanisms over time. In terms of implementation, the TDP involves updated driver datasets and regression coefficients, enabling a more accurate spatial allocation of land-use demand. Comparative experimental results from Xiamen in China demonstrate that the TDP achieves higher simulation accuracy than the BDP simulation, with notably greater sensitivity to dynamic factors such as transportation infrastructure and policy boundaries. For study periods 1989–2000 and 2000–2010, the accuracy of TDP simulation for all land-use types surpasses that of BDP simulation. As time progresses, the advantage of TDP simulation over BDP simulation becomes more pronounced, resulting in a significant improvement in the simulation accuracy. These findings confirm that the temporal alignment between driver data and the simulation period is a critical determinant of CLUE-S simulation accuracy. This methodological refinement holds significant implications for model-based land-use planning: it allows simulation procedures to explicitly incorporate future driver conditions articulated in planning documents. Moreover, it equips decision makers with a more realistic simulation tool for evaluating the land-use consequences of alternative planning interventions in scenario-based analyses.

Urban green spaces (UGSs) provide city residents contact with nature, offering mental and physical health benefits. However, residents’ access to green spaces in cities can be associated with their socioeconomic status (SESs). This study utilizes the Kernel Density tool as an innovative method to measure UGS inequities and their relationship with cardiovascular disease (CVD) rates. Next, the UGS patterns and their potential implications for CVD are examined across suburbs with a range of SES levels in Melbourne, Australia. The proposed method is tested in conjunction with two commonly used measures of accessibility (Network Analysis) and provision (UGS per capita). The results show that more advantaged suburbs have better access to UGS and lower CVD rates. Moreover, the analysis reveals that a more geographically dispersed UGS pattern, predominantly observed in higher SES suburbs, can be associated with lower CVD than a concentrated pattern, and the integration of the SES and UGS indicators through Kernel Density analysis reveals that inequitable access to green spaces disproportionately impacts the health incomes of socioeconomically disadvantaged communities. Finally, the Kernel Density and Network Analysis tools in ArcGIS can serve as effective supplementary methods for addressing similar considerations in UGS planning and policy.

This study focuses on the coastal city of Xiamen, examining the factors and driving mechanisms influencing land use changes and spatial patterns. Spatial logistic regression and Statistical Package for the Social Sciences (SPSS) software were employed using grid data with a resolution of 100m to analyze the spatial relationships between six driving factors (such as elevation and slope) and five land use types within the study area. Regression models were established for each factor, and all Relative Operating Characteristic (ROC) tests were passed. Based on the results of the logistic regression analysis, land use changes and spatial distribution were simulated using the updated Conversion of Land Use and its Effects (CLUE) model so as to validate the driving mechanisms. The findings indicate that the six driving factors effectively explain the spatial patterns of land use in the study area. The distance to the coastline is the primary influencing factor in the evolution of spatial patterns, particularly impacting built-up land and farmland, while for forest land, slope is the main factor affecting the spatial distribution. The simulation and accuracy analysis revealed an overall simulation accuracy ranging from 73% to 90.1%, demonstrating that the selected driving factors have effective explanatory power for the spatial distribution of land use. Thus, this study’s results provide valuable insights into the complexity of land use changes and serve as a reference for relevant departments in land use management and planning.

Transitioning to a zero-carbon, sustainable logistics ecosystem requires a fundamental shift in how physical, digital, and organizational systems interact. The Physical Internet (PI) presents a transformative vision for logistics and supply chain management by providing a blueprint for decarbonized, circular, and resilient operations. However, the complex, interdisciplinary nature of its knowledge base presents challenges for coordinated global implementation. This study introduces a dual-model natural language processing (NLP) approach combining transformer-based topic modeling (BERTopic) with maximal marginal relevance (MMR) and generative pretrained transformer (GPT) techniques. This hybrid approach enables the extraction and synthesis of key research themes from over 2600 scientific publications on PI. Thematic analysis revealed eight critical domains, ranging from smart infrastructure and energy systems to cybersecurity and governance that are foundational to PI’s sustainable development and adoption. Furthermore, we evaluated the alignment of these themes with the PI roadmaps and the UN sustainable development goals (SDGs), especially SDG 9 (Industry, Innovation and Infrastructure), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). Results highlight the importance of interoperability, digital twin technologies, renewable energy integration, and secure data exchange for achieving greener and more adaptive logistics networks. This work provides a scalable, data-driven methodology for strategic decision-making and knowledge synthesis, thereby supporting the sustainable transformation of logistics and supply chains.

On-demand delivery in urban areas has been growing rapidly in recent years. Nevertheless, on-demand delivery networks lack an efficient, sustainable, and environmentally friendly operative strategy. An open trading system equipped with on-line auctions provides an opportunity for increasing the efficiency of on-demand delivery systems. Reinforcement learning techniques that automate decision-making can facilitate the implementation of such complex and dynamic systems. This paper presents an on-line auction-based request trading platform embedded within an open trading system as a new scheme for carriers and shippers to trade on-demand delivery requests. The system is developed based on a multi-agent model, composed of carriers, shippers, and the on-line platform as autonomous agents. Deep Q network enabled reinforcement learning is used in the decision-making processes for the agents to optimise their behaviour in a dynamic environment. Numerical experiments conducted on the Melbourne metropolitan network demonstrate the effectiveness of the open trading system, which can provide benefits for all stakeholders involved in the on-demand delivery market as well as the entire system. The reinforcement learning enabled platform can gain more profit when there are more learning carriers. The results indicate that the intelligent open trading system with on-line auctions is a promising city logistics solution.

Urban areas grapple with escalating challenges due to climate change, rapid urbanisation, and shifting demographics. Collaborative efforts and innovative applications of big earth data analytics and digital infrastructures are imperative in tackling the issues facing cities and advancing SDG 11.Modernising urban infrastructure is essential, coupled with a focus on people-centric urban regeneration to enhance the well-being of city residents. Urban resilience, encompassing diverse social, economic, environmental, and governance facets, lies at the core of this mission. A resilient city can endure and recover from disruptions, be they natural disasters or human-made crises.Stakeholder engagement, bridging top-down and bottom-up approaches, is pivotal in fostering the use of earth data to promote sustainability and urban resilience. A literature review and on-going research underscores digital infrastructure's potential in fortifying resilient, sustainable cities. Insights from an international forum on ‘Digital Infrastructure for Climate Resilience’ held in Melbourne, Australia in 2023 inform this perspective.Big earth data analytics combined with Urban Digital Twin technologies, emerge as potent tools for urban stakeholders and decision-makers. Despite challenges, opportunities abound to leverage data and digital platforms to bolster sustainable urban development. Effective leadership, government regulations, standards, and cross-sector collaboration are essential for realising this potential.

Neighbourhood environments shape older adults' social interactions. This research conceptualises a comprehensive set of perceived and objective measures of neighbourhood social and built environments, including third places, with older adults' social interactions. In Melbourne, based on the person-environment fit framework, mediation analyses showed that the perceived social environment measures of community spirit, participation in community groups and belonging to suburb, were the strongest predictors of social interactions, followed by a few types of perceived third places. Our findings suggest that policymakers should focus on how the objective environment characteristics are interpreted as levers when planning for changes.

The transition to sustainable agriculture necessitates a greater understanding of plants in the field with automated plant phenotyping. Leaf segmentation is critical in this domain, enabling the accurate assessment of plant traits essential for managing the growth of economically viable crops and plants. This paper reviews recent developments in leaf segmentation methodologies, focusing on the emerging paradigm of promptable segmentation. Promptable segmentation, exemplified by Meta AI’s Segment Anything Model (SAM), offers flexibility and versatility by allowing users to provide various prompts for segmentation tasks. However, challenges such as complex backgrounds, overlapping leaves, and computational complexity persist. The paper discusses strategies such as prompt engineering, post-processing of segmentation outputs, and fine-tuning segmentation models to address these challenges. Future research includes exploring occlusion handling techniques, adopting parameter-efficient fine-tuning methods, collecting and leveraging publicly available datasets, synthetic data generation, and embracing video-based data collection. By overcoming these challenges and harnessing the potential of promptable segmentation, researchers can create automated plant phenotyping for any plant species, leading to more accurate, efficient, and scalable solutions for agricultural sustainability.

New community-scale developments should address both greenhouse gas emissions mitigation and climate adaptation goals. This paper presents a systematic approach to energy master planning (EMP) of net-zero emissions communities via probabilistic analysis of the resilience and cost effectiveness of various energy provision portfolios (supply, conversion and storage) in early design stage. Applied in the EMP of a new university satellite campus, comprising of five buildings with mixed energy uses, both the 2050 net-zero emissions and the energy resilience objectives are met by an energy provision portfolio that consists of air source heat pumps for heating and cooling, and a combination of PV panels, purchased green power, standard (non-green) grid power, battery and thermal heat and cold storage tanks - with only a modest 6% increase in costs compared to a reference solution. The case project demonstrates the financial feasibility of a resilient energy system that also meets a net-zero emissions objective.

Wood and other bio-based building materials are often perceived as a good choice from a climate mitigation perspective. This article compares the life cycle assessment of the same multi-residential building from the perspective of 16 countries participating in the international project Annex 72 of the International Energy Agency to determine the effects of different datasets and methods of accounting for biogenic carbon in wood construction. Three assessment methods are herein considered: two recognized in the standards (the so-called 0/0 method and −1/+1 method) and a variation of the latter (−1/+1* method) used in Australia, Canada, France, and New Zealand. The 0/0 method considers neither fixation in the production stage nor releases of biogenic carbon at the end of a wood product's life. In contrast, the −1/+1 method accounts for the fixation of biogenic carbon in the production stage and its release in the end-of-life stage, irrespective of the disposal scenario (recycling, incineration or landfill). The −1/+1 method assumes that landfills offer only a temporary sequestration of carbon. In the −1/+1* variation, landfills and recycling are considered a partly permanent sequestration of biogenic carbon and thus fewer emissions are accounted for in the end-of-life stage. We examine the variability of the calculated life cycle-based greenhouse gas emissions calculated for a case study building by each participating country, within the same assessment method and across the methods. The results vary substantially. The main reasons for deviations are whether or not landfills and recycling are considered a partly permanent sequestration of biogenic carbon and a mismatch in the biogenic carbon balance. Our findings support the need for further research and to develop practical guidelines to harmonize life cycle assessment methods of buildings with bio-based materials.

This paper explores the integration of Urban Digital Twin (UDT) technology in Melbourne's Greenline Project, focusing on a performance-based framework that aligns with Sustainable Development Goals and city-specific sustainability objectives. Recognising the complexities of urban ecosystems while anchoring on human-centric 'placemaking' - a participatory process involving the planning, design, and management of public spaces - the key capabilities and challenges in developing, implementing and applying UDTs and related technologies to achieve these objectives are reviewed and synthesised. Challenges in data collection and/or access, their use and integration into decision-making processes and capturing the dynamic interaction between physical and virtual environments, including updating UDT models are highlighted. The review emphasises the role of urban planners and stakeholders in driving UDT development and applications by better understanding and stating objectives, leveraging interdisciplinary collaboration for effective technology application, crucial for robust data management, analytics, and community contribution. International examples illustrate the potential utility of Digital Twins in enhancing urban planning, design, and operational management. The paper presents a preliminary framework to guide the further development of the Greenline Project and inform future research that is needed for improved and effective deployment and use of UDTs in other urban revitalisation projects.Practitioner pointersUrban planners have a central role in directing Urban Digital Twin technologies to address socio-economic and sustainability challenges facing cities and communities.Interdisciplinary collaboration, skills development, user-friendly technologies and sharing of real-time spatial data will drive innovation and support sustainable urban development.Developing performance frameworks will enhance planning and design practice, project monitoring and management and communications related to sustainable urban regeneration.

Today, more than 700 cities worldwide have made net-zero pledges. Managing these bold targets, however, is not easy given the complexity of urban systems. Although holistic mitigation efforts are vital, individual sectors are likely to face their own challenges and require tailor-made solutions. This Voices asks: what are the challenges and opportunities in transforming cities toward net-zero carbon emissions?

Vertical fire spread along highly flammable claddings is a major safety issue for buildings. In this project, a potential new type of cladding material, 3D Glass Fibre Reinforced Polymer (3D GFRP) with improved thermal stability, and fire performance is developed. 3D GFRP nanocomposite samples were fabricated with different percentages of Sepiolite (Sep), Sepiolite-phosphate (SepP), Ammonium Polyphosphate (APP) flame retardant, and 3D glass fabrics. Synthesis of SepP, dispersion analysis of nanoparticles, and manufacturing process have been studied. The characterisation of materials was conducted using Scanning Electron Microscopy, Helium Ion Microscopy, Transmission Electron Microscopy, Thermogravimetric Analysis (TGA), and X-ray Diffraction Analysis. The thermal stability and fire behaviour of the 3D GFRP nanocomposite was studied via TGA and cone calorimeter test. TGA results showed that the optimum amount of additives that improved the thermal stability is 15% flame retardants. Results of cone calorimeter tests showed that different percentages of APP, Sep, and SepP decreased the peak of the heat release rate between 4% and 42%. Also, the effects of APP flame retardant in improving thermal and fire reaction properties were more than Sep and SepP. The test results of 3D GFRP nanocomposite also showed a prospective cladding that can benefit the construction industry in near future.

This research aims to identify the key indicators of land-use change that affect ecosystem service in the coastal city of Xiamen. The methods of transfer matrix and land-use dynamic degree are used to analyze land-use change, and the spatial distribution of ecosystem service values (ESV) is mapped from 1989 to 2018 using cluster analysis. During this 30-year period, the built-up land expanded rapidly through occupation of farmland and landfilling of the watershed. The biggest contribution to the reduction of ESV in this stage is the loss of farmland followed by the loss of watershed. By 2018, the spatial distribution of ESV had become very unbalanced and polarized. The high-value areas are mainly distributed in the northern mountainous areas, with the low-value areas concentrated in the flat areas near the coastline, and only a few medium-value areas of ESV remained. Generally, from 1989 to 2018, the ESV in Xiamen decreased by about CNY 200 million in total, with the largest proportion of ESV reduction (CNY 120 million) occurring in the 2000–2010 period. Considering ESV categories, the significant reduction of Regulating Service (53.5–57.8%) was mainly due to the loss of water areas (CNY −70 million) to low ESV areas (built-up land) in urbanization, followed by the loss of farmland (CNY −50 million). This means that Xiamen should strengthen the protection of ecological lands in future urban planning to alleviate and reverse the current ecological imbalance.