Hasil untuk "Urban renewal. Urban redevelopment"

Abdimalik Ali Warsame, Hudayfe Osman Daror, Mohamed Abdikarim Jama

This study examines the impact of corruption control and natural resource rents on environmental sustainability in East African countries while accounting for the influences of renewable energy, economic growth, and urbanisation. The study utilises panel data spanning 1996–2022 and various econometric methods, such as Pedroni and Kao cointegration methods, pooled mean group (PMG), panel dynamic ordinary least squares (DOLS), and fully modified ordinary least squares (FMOLS). The empirical results revealed that natural resources, corruption control, renewable energy, urbanisation, and economic growth are cointegrated with environmental pollution in the long run. Furthermore, natural resource rent hinders environmental sustainability, while corruption control enhances it in the long run. Renewable energy enhances environmental sustainability in East Africa in the long run. On the contrary, economic growth and urbanisation impede it in the long run. Nevertheless, the study recommends strengthening governance, promoting transparency, and implementing restricted environmental regulations to enhance environmental quality.

Rui Liu, Steven Jige Quan, Zhong-Ren Peng et al.

As cities evolve over time, challenges such as traffic congestion and functional imbalance increasingly necessitate urban renewal through efficient modification of existing plans, rather than complete re-planning. In practice, even minor urban changes require substantial manual effort to redraw geospatial layouts, slowing the iterative planning and decision-making procedure. Motivated by recent advances in agentic systems and multimodal reasoning, we formulate urban renewal as a machine-executable task that iteratively modifies existing urban plans represented in structured geospatial formats. More specifically, we represent urban layouts using GeoJSON and decompose natural-language editing instructions into hierarchical geometric intents spanning polygon-, line-, and point-level operations. To coordinate interdependent edits across spatial elements and abstraction levels, we propose a hierarchical agentic framework that jointly performs multi-level planning and execution with explicit propagation of intermediate spatial constraints. We further introduce an iterative execution-validation mechanism that mitigates error accumulation and enforces global spatial consistency during multi-step editing. Extensive experiments across diverse urban editing scenarios demonstrate significant improvements in efficiency, robustness, correctness, and spatial validity over existing baselines.

امان الله بلوچ, مهرزاد ابراهیمی, هاشم زارع

این پژوهش با استفاده از روش‌شناسی ترکیبی (کمی–کیفی) و داده‌های پانل، به بررسی تأثیر اقتصاد دیجیتال بر رشد سبز در کلان‌شهرهای تهران، مشهد، اصفهان، تبریز، شیراز و کرج در بازه زمانی 2019 تا 2023 می‌پردازد. نمونه‌گیری هدفمند و بر اساس دسترسی به داده‌های کامل و تنوع جغرافیایی–اقتصادی انجام شده است. داده‌ها از منابع معتبر شامل مرکز آمار ایران، بانک مرکزی و سازمان حفاظت محیط زیست گردآوری شده‌اند. تحلیل داده‌ها با بهره‌گیری از مدل Super-SBM برای خروجی‌های نامطلوب زیست‌محیطی، مدل خودرگرسیون فضایی برای اثرات سرریز مکانی، و رگرسیون پانل دیتا با اثرات ثابت صورت گرفته است. نتایج نشان می‌دهد که اقتصاد دیجیتال از طریق کاهش ۳۰ درصدی عدم تطابق منابع و افزایش نوآوری‌های فناوری سبز بر رشد سبز تأثیرگذار است. مشهد و اصفهان به ترتیب با شاخص‌های GGI معادل 1.15 و 1.08 بهترین عملکرد را در این زمینه داشته‌اند، در حالی‌که تهران به دلیل سهم ۲۵ درصدی صنایع آلاینده، نتوانسته است به پتانسیل کامل خود دست یابد (GGI=0.92). همچنین، توسعه اقتصاد دیجیتال در تهران تأثیر مثبتی بر رشد سبز کرج و اسلام‌شهر داشته است. برای بهره‌برداری بهینه از مزایای اقتصاد دیجیتال، تدوین برنامه‌های تحول دیجیتال سبز، ایجاد صندوق‌های نوآوری سبز و طراحی چارچوب‌های حکمرانی منطقه‌ای پیشنهاد می‌شود. این نتایج می‌توانند راهگشای سیاست‌گذاران شهری در ایران و کشورهای در حال توسعه باشند و مسیرهای نوینی برای تحقیقات آینده در حوزه فناوری‌های نوین ارائه دهند.

Yanping Qi, Yinghui Zhao, Jingpeng Guo et al.

Resource-exhausted cities face dual crises of economic stagnation and ecological degradation, which is primarily attributable to the inefficient use of industrial land. The redevelopment of industrial land has emerged as a crucial solution to the “resource depletion-urban decline” dilemma. The issue of inefficient industrial land use in resource-exhausted cities is of great significance as it directly impacts both economic development and ecological protection. Therefore, finding effective ways to redevelop this land is essential for the sustainable development of these cities. This research takes Hegang, a representative resource-exhausted city in China, as a case study. A multi-dimensional evaluation framework and an adaptive redevelopment strategy system are constructed in this research. By integrating data related to land use status, land use efficiency, policy constraints, and development potential, a parcel-scale assessment model is established. This model consists of 4 primary indicators and 13 secondary indicators. Through this model, 11.01 km² of inefficient industrial land in the main urban area of Hegang is identified. Standard deviation ellipse and kernel density analysis are employed to reveal the spatial pattern of inefficient land. The results show that the inefficient industrial land in Hegang exhibits a pattern of “overall dispersion with localized agglomeration”. It is found that idle and abandoned land are the dominant types of inefficient industrial land in Hegang’s main urban area, accounting for 69.7% of the total. This finding provides a clear understanding of the nature of the inefficient land use problem in resource-exhausted cities. A strategic framework is proposed, which incorporates classified governance, dynamic restoration, and multi-stakeholder collaboration. This framework offers a governance toolkit with both theoretical depth and practical value for resource-exhausted cities. Breaking the locked relationship between industrial land and resource dependence promotes the deep integration of spatial restructuring and sustainable transformation. The findings of this research provide significant scientific insights for similar cities worldwide to address the challenges they face and achieve harmony between human activities and land use. Future research could focus on further refining the evaluation framework and redevelopment strategies based on different regional characteristics and resource endowments.

Marc Duran-Sala, Martin Hendrick, Gabriele Manoli

Urban-induced changes in local microclimate, such as urban heat islands and air pollution, are known to vary with city size, leading to distinctive relations between average climate variables and city-scale quantities (e.g., total population). However, these approaches suffer from biases related to the choice of city boundaries and they neglect intra-urban variations of urban characteristics. Here, we use high-resolution data of urban temperatures, air quality, population, and street networks from 142 cities worldwide and show that their marginal and joint probability distributions collapse onto a set of general scaling functions. Using a logarithmic relation between urban spatial features and climate variables, we find that average street network properties are sufficient to characterize the entire variability of the temperature and air pollution fields observed within and across cities. These findings provide a unified statistical framework for characterizing intra-urban climate variability, with important implications for climate modeling and urban planning.

Viet Hung Pham, Malte Wagenfeld, Regina Bernhaupt

Traditional urban planning methodologies often fail to capture the complexity of contemporary urbanization and environmental sustainability challenges. This study investigates the integration of Generative Design, Virtual Reality (VR), and Digital Twins (DT) to enhance walkability in urban planning. VR provides distinct benefits over conventional approaches, including 2D maps, static renderings, and physical models, by allowing stakeholders to engage with urban designs more intuitively, identify walkability challenges, and suggest iterative improvements. Preliminary findings from structured interviews with Eindhoven residents provide critical insights into pedestrian preferences and walkability considerations. The next phase of the study involves the development of VR-DT integrated prototypes to simulate urban environments, assess walkability, and explore the role of Generative Design in generating adaptive urban planning solutions. The objective is to develop a decision-support tool that enables urban planners to incorporate diverse stakeholder perspectives, optimize pedestrian-oriented urban design, and advance regenerative development principles. By leveraging these emerging technologies, this research contributes to the evolution of data-driven, participatory urban planning frameworks aimed at fostering sustainable and walkable cities.

Mahshid Gorjian

Urban morphology has a significant impact on sustainable urban outcomes in the ecological, social, and economic sectors. Nonetheless, academics lack clarity and consensus on how to quantify urban morphology indicators, which impedes multidisciplinary research and the creation of integrated sustainable solutions. This comprehensive study develops a detailed taxonomy of urban form indicators related to sustainability, describes quantitative approaches for investigating the linkages between urban morphology and sustainability, and examines research trends, gaps, and future directions. A review of 89 carefully selected studies showed 365 distinct urban morphology measures, with significant variation in names, interpretations, and data formats. The measures were divided into six categories: urban tissue configuration, roadway network, building plot characteristics, land use, natural elements and greenspace, and urban expansion, each with its own subclass. The study indicates that, even though urban morphology is intrinsically spatial, spatial modeling is rarely used to investigate its relationships with sustainability. The research shows a regional bias, with insufficient representation of studies focusing on the Global South and natural elements. This synthesis calls for a standardized classification framework as well as more broad, spatially explicit techniques to foster multidisciplinary research and support effective policy and planning for sustainable urban development.

Ruixing Zhang, Bo Wang, Tongyu Zhu et al.

Urban profiling aims to predict urban profiles in unknown regions and plays a critical role in economic and social censuses. Existing approaches typically follow a two-stage paradigm: first, learning representations of urban areas; second, performing downstream prediction via linear probing, which originates from the BERT era. Inspired by the development of GPT style models, recent studies have shown that novel self-supervised pretraining schemes can endow models with direct applicability to downstream tasks, thereby eliminating the need for task-specific fine-tuning. This is largely because GPT unifies the form of pretraining and inference through next-token prediction. However, urban data exhibit structural characteristics that differ fundamentally from language, making it challenging to design a one-stage model that unifies both pretraining and inference. In this work, we propose Urban In-Context Learning, a framework that unifies pretraining and inference via a masked autoencoding process over urban regions. To capture the distribution of urban profiles, we introduce the Urban Masked Diffusion Transformer, which enables each region' s prediction to be represented as a distribution rather than a deterministic value. Furthermore, to stabilize diffusion training, we propose the Urban Representation Alignment Mechanism, which regularizes the model's intermediate features by aligning them with those from classical urban profiling methods. Extensive experiments on three indicators across two cities demonstrate that our one-stage method consistently outperforms state-of-the-art two-stage approaches. Ablation studies and case studies further validate the effectiveness of each proposed module, particularly the use of diffusion modeling.

Faris Henry Gergis

This scoping review examines governance models in sustainable urban mobility schemes, focusing on citizen participation. Analysing 15 papers from 2010 to March 2023, it differentiates between Democracy-Driven Governance (DDG) and Governance-Driven Democratisation (GDD). Key considerations are stakeholder composition, scheme design, and collaboration motives. Findings indicate that GDD approaches are prevalent, impacting stakeholder integration and exposing participation limitations. The latter accentuates the significance of Collaborative Forms of Governance (CFoG) in fostering substantive citizen participation, thereby contributing to the attainment of SDG 16.7 and SDG 11.2. Consequently, this review elucidates CFoG dynamics, providing critical insights into sustainable urban mobility decision-making practices.

Yu Wen, Hong Qi, Tao Long

Safety has become the bottom line and fundamental goal of urban renewal with the accelerated urbanization process. Building a safe and stable urban residential environment is a meaningful way to improve cities’ “social-ecological” resilience. Based on the theory of environmental crime prevention and space syntax, taking Tiexinli old residential area in Qinhuangdao City as the research object, using Depth map software to quantitatively analyze the integration degree, synergy degree, connectivity degree, depth value, visual clustering coefficient, and choice value of the residential space, the results show that the accessibility of the spatial system of the old residential area is differentiated. The accessibility of the by-pass road is the lowest and lacks activity support. The spatial layout of the residential area is single and concurrent, and the entrances, exits, and the subsidiary road fail to play a good role in ” access control. ” The environment and landscape of green space between houses and negative space in the residential area are poorly maintained, and the visibility effect is limited. Therefore, the renovation of the old residential area should focus on optimizing the road system, increasing the monitoring of the activities of the people, and enriching the activities of the public space. This research contributes to addressing potential crime issues in urban renewal. It offers feasible and forward-looking approaches to crime prevention and control in the redevelopment of old residential areas in Asian countries. Additionally, this method can be applied in the planning and design of new residential areas to identify and rectify potential crime risks within design schemes, ensuring the safety and living quality of residential communities.

Margherita Fadda

As the African continent continues to urbanise, cities are becoming increasingly central to the transformations of societies and economies. Many studies highlight the limits of urban planning in these cities, emphasising the high share of population living in slums and the low levels of services that reach neighbourhoods. Less attention is given to the urban planning activities that try to prevent or improve these conditions. This analysis of urban plans illustrates that plans are more widespread than commonly thought. They also, for the large part, consider spatial growth. The low number of cities that grew within the projected boundaries of these plans is a symptom of numerous bottlenecks that constrain planning systems in these countries. Examples of these include the disregard of the full built-up areas at the time of the plan's approval and the missing link between the plans and the financial means allocated for its delivery. This article identifies opportunities to overcome these barriers such as flexible and adaptable urban plans that consider the entire built-up area of the agglomeration.

Yecheng Zhang, Tangqi Tu, Ying long

Due to rapid urbanization over the past 20 years, many newly developed areas have lagged in socio-economic maturity, creating an imbalance with older cities and leading to the rise of "ghost cities." However, due to the complexity of socio-economic factors, no global studies have measured this phenomenon. We propose a unified framework based on urban vitality theory and multi-source data, validated by various data sources. We derived 8841 natural cities globally with an area over 5 square kiloxmeters and divided each into new urban areas (developed after 2005) and old urban areas (developed before 2005). Urban vitality was gauged using the density of road networks, points of interest (POIs), and population density with 1 km resolution across morphological, functional, and social dimensions. By comparing urban vitality in new and old urban areas, we quantify the ghost cities index (GCI) globally using the theory of urban vitality for the first time. The results reveal that the vitality of new urban areas is 7.69% that of old ones. The top 5% (442) of cities were designated as ghost cities, a finding mirrored by news media and other research. This study sheds light on strategies for sustainable global urbanization, crucial for the United Nations' Sustainable Development Goals.

Fan Lu, Kwan-Yee Lin, Yan Xu et al.

Text-to-3D generation has achieved remarkable success via large-scale text-to-image diffusion models. Nevertheless, there is no paradigm for scaling up the methodology to urban scale. Urban scenes, characterized by numerous elements, intricate arrangement relationships, and vast scale, present a formidable barrier to the interpretability of ambiguous textual descriptions for effective model optimization. In this work, we surmount the limitations by introducing a compositional 3D layout representation into text-to-3D paradigm, serving as an additional prior. It comprises a set of semantic primitives with simple geometric structures and explicit arrangement relationships, complementing textual descriptions and enabling steerable generation. Upon this, we propose two modifications -- (1) We introduce Layout-Guided Variational Score Distillation to address model optimization inadequacies. It conditions the score distillation sampling process with geometric and semantic constraints of 3D layouts. (2) To handle the unbounded nature of urban scenes, we represent 3D scene with a Scalable Hash Grid structure, incrementally adapting to the growing scale of urban scenes. Extensive experiments substantiate the capability of our framework to scale text-to-3D generation to large-scale urban scenes that cover over 1000m driving distance for the first time. We also present various scene editing demonstrations, showing the powers of steerable urban scene generation. Website: https://urbanarchitect.github.io.

Said Nuhu, Neema Munuo, Lazaro Mngumi

The regularisation of informal settlements has become a common initiative for addressing urban development and growth in many cities in Sub-Saharan Africa. Yet, its governance is still complex and unexplored. This study thus aims to examine and understand the governance challenges of regularising informal settlements in peri-urban Tanzania. A case study design with a combination of discussions from two participatory workshops and document analysis was used to collect empirical and theoretical data. Findings show that the regularisation of informal settlements is challenged by existing structural governance operations driven by stakeholders, particularly community leaders and planning and surveying firms. Consequently, regularisation processes are delayed or halted, which demoralises the landholders. To ensure effective and efficient governance structures for regularisation activities, it is essential that responsible actors diligently play their roles as mandated in the policy and legal documents. Accountability and transparency should be reinforced in the operation and implementation of regularisation schemes to ensure adherence to guiding policies and laws.

Francesco Chiacchiera, Gianluigi Mondaini

The study delves into the realm of adaptive reuse, exploring its potential in sustainable urban development, particularly focusing on public buildings within the cultural and creative sectors. Through a multiple case study analysis, both qualitative and quantitative methods were employed to scrutinize design strategies and spatial transformations in recent adaptive reuse projects of existing structures. This research investigates the evolution of adaptive reuse, highlighting its historical and theoretical underpinnings, and subsequently examines contemporary approaches towards existing structures in cultural, creative, and public domains. The study findings reveal common characteristics and innovative design strategies employed in recent adaptive reuse projects, emphasizing the transformative potential of neglected or abandoned urban spaces. Utilizing a comprehensive methodology involving case study analyses and diverse data collection techniques, the research underscores the significance of adaptive reuse as an established practice in contemporary architectural and urban design. The article's contribution to the social and economic dimensions of urban development lies in understanding and promoting sustainable, resource-saving strategies. This work paves the way for future research, suggesting potential expansions in creating an 'atlas of adaptive reuse' and exploring comparative analyses between existing reuse and new construction, specifically focusing on public buildings with civic-cultural uses.

Anthony Vanky, Ri Le

Increasing computational power and improving deep learning methods have made computer vision technologies pervasively common in urban environments. Their applications in policing, traffic management, and documenting public spaces are increasingly common. Despite the often-discussed biases in the algorithms' training and unequally borne benefits, almost all applications similarly reduce urban experiences to simplistic, reductive, and mechanistic measures. There is a lack of context, depth, and specificity in these practices that enables semantic knowledge or analysis within urban contexts, especially within the context of using and occupying urban space. This paper will critique existing uses of artificial intelligence and computer vision in urban practices to propose a new framework for understanding people, action, and public space. This paper revisits Geertz's use of thick descriptions in generating interpretive theories of culture and activity and uses this lens to establish a framework to evaluate the varied uses of computer vision technologies that weigh meaning. We discuss how the framework's positioning may differ (and conflict) between different users of the technology. This paper also discusses the current use and training of deep learning algorithms and how this process limits semantic learning and proposes three potential methodologies for gaining a more contextually specific, urban-semantic, description of urban space relevant to urbanists. This paper contributes to the critical conversations regarding the proliferation of artificial intelligence by challenging the current applications of these technologies in the urban environment by highlighting their failures within this context while also proposing an evolution of these algorithms that may ultimately make them sensitive and useful within this spatial and cultural milieu.

Bhubaneswor Dhakal, Kedar Adhikari

Many critical problems are intensified in rural Nepal despite the policy advice and financial support from international agencies to alleviate them. This study attempted to explain the causes and policy solutions to the problems based on secondary sources of data and the authors’ insights. It identified that international agencies involved actively in policymaking and guided the land resource management policy to result in the best benefits to the people in privileged regions and other countries. The policies ruined institutions, resource conditions, social-ecological systems, and social environments essential for sustaining mountain farming and the rural economy in the country. The destructions exacerbated emigration, farming land abandonment, indigenous farming practice loss, food insecurity, and cultural heritage degradation. Adverse impacts of the policy interventions are exposed higher in disadvantaged areas and especially in the regions of indigenous ethnic communities. Those policies have institutionally placed the communities suffering for generations and increased risks of out-breaking interethnic conflicts and national security threats on many dimensions. This study explained some pragmatic policy measures to manage the agriculture and forestry resources for community wellbeing and national security. It also demonstrated how the national expert-driven policies would be for addressing the current problems in rural areas and the holistic development of the nation.

Congxi Xiao, Jingbo Zhou, Jizhou Huang et al.

Urban villages (UVs) refer to the underdeveloped informal settlement falling behind the rapid urbanization in a city. Since there are high levels of social inequality and social risks in these UVs, it is critical for city managers to discover all UVs for making appropriate renovation policies. Existing approaches to detecting UVs are labor-intensive or have not fully addressed the unique challenges in UV detection such as the scarcity of labeled UVs and the diverse urban patterns in different regions. To this end, we first build an urban region graph (URG) to model the urban area in a hierarchically structured way. Then, we design a novel contextual master-slave framework to effectively detect the urban village from the URG. The core idea of such a framework is to firstly pre-train a basis (or master) model over the URG, and then to adaptively derive specific (or slave) models from the basis model for different regions. The proposed framework can learn to balance the generality and specificity for UV detection in an urban area. Finally, we conduct extensive experiments in three cities to demonstrate the effectiveness of our approach.

Gopi Nath Mainali

राज्यले प्रभावकारी सेवा व्यवस्थापन र स्वच्छ राजस्व परिचालन एवम् जिम्मेवारीपूर्ण खर्च गर्नको निम्ति प्रभावकारी सार्वजनिक वित्तीय व्यवस्थापन महत्वपूर्ण हुन्छ । यस लेखको उद्देश्य वित्तीय व्यवस्थापनको संक्षिप्त विकासक्रम र वर्तमान अवस्थाको लेखाजोखा गर्दै सार्वजनिक वित्तीय व्यवस्थापनका उद्देश्य, सार्वजनिक वित्तीय व्यवस्थापन चक्र तथा नेपालमा देखिएका प्रमुख सवाल र चुनौतीको पहिचान गर्नु र भावी दिनमा अवलम्वन गर्नैपर्ने केही नीतिगत तथा कार्यगत पक्षमा सुझावहरू पेश गर्नु हो । सार्वजनिक वित्तीय व्यवस्थापनका दश वटा चुनौतीहरूको पहिचान गर्दै सुधारका लागि वास्तविक बजेट निर्माण, योजना र खर्च संरचनाबिच तार्किक सम्बन्ध, स्वचालित वित्तीय कारोबार, सूचना समावेश गर्ने खरिद प्रणाली, एकीकृत सार्वजनिक वित्तीय सूचना व्यवस्थापन प्रणाली, सम्पूर्ण बजेट प्रलेखीकरण प्रणाली, नतिजामूलक अनुगमन र कम्प्युटर–सहकृत लेखा परीक्षण, आदि सुझावहरू पेश गरिएका छन् । Abstract (in English) Effective public financial management is important for effective service management, clean revenue mobilization, and responsible spending. The purpose of this article is to present a brief history of financial management and assessessment the current situation, and to identify the purpose of public financial management, the working of public financial management cycle, the major issues and challenges in Nepal, and to suggest some policy and action plan to be adopted in coming days. Identifying some ten challenges of the current public financial management, suggestion are offered which include practices and measures for actual budget, the logical relationship between planning and expenditure structure, automated financial transactions, procurement system that captures information, integrated financial information management system, whole-of-the-budget documentation system, result-based monitoring and computer-asisted accounting.