Urban cultures and architectural styles vary significantly across cities due to geographical, chronological, historical, and socio-political factors. Understanding these differences is essential for anticipating how cities may evolve in the future. As representative cases of historical continuity and modern innovation in China, Beijing and Shenzhen offer valuable perspectives for exploring the transformation of urban streetscapes. However, conventional approaches to urban cultural studies often rely on expert interpretation and historical documentation, which are difficult to standardize across different contexts. To address this, we propose a multimodal research framework based on vision-language models, enabling automated and scalable analysis of urban streetscape style differences. This approach enhances the objectivity and data-driven nature of urban form research. The contributions of this study are as follows: First, we construct UrbanDiffBench, a curated dataset of urban streetscapes containing architectural images from different periods and regions. Second, we develop UrbanSense, the first vision-language-model-based framework for urban streetscape analysis, enabling the quantitative generation and comparison of urban style representations. Third, experimental results show that Over 80% of generated descriptions pass the t-test (p less than 0.05). High Phi scores (0.912 for cities, 0.833 for periods) from subjective evaluations confirm the method's ability to capture subtle stylistic differences. These results highlight the method's potential to quantify and interpret urban style evolution, offering a scientifically grounded lens for future design.
Matt Franchi, Maria Teresa Parreira, Fanjun Bu
et al.
This paper introduces the Robotability Score ($R$), a novel metric that quantifies the suitability of urban environments for autonomous robot navigation. Through expert interviews and surveys, we identify and weigh key features contributing to R for wheeled robots on urban streets. Our findings reveal that pedestrian density, crowd dynamics and pedestrian flow are the most critical factors, collectively accounting for 28% of the total score. Computing robotability across New York City yields significant variation; the area of highest R is 3.0 times more "robotable" than the area of lowest R. Deployments of a physical robot on high and low robotability areas show the adequacy of the score in anticipating the ease of robot navigation. This new framework for evaluating urban landscapes aims to reduce uncertainty in robot deployment while respecting established mobility patterns and urban planning principles, contributing to the discourse on harmonious human-robot environments.
Recently, learning effective representations of urban regions has gained significant attention as a key approach to understanding urban dynamics and advancing smarter cities. Existing approaches have demonstrated the potential of leveraging mobility data to generate latent representations, providing valuable insights into the intrinsic characteristics of urban areas. However, incorporating the temporal dynamics and detailed semantics inherent in human mobility patterns remains underexplored. To address this gap, we propose a novel urban region representation learning model, Mobility Time Series Contrastive Learning for Urban Region Representations (MobiCLR), designed to capture semantically meaningful embeddings from inflow and outflow mobility patterns. MobiCLR uses contrastive learning to enhance the discriminative power of its representations, applying an instance-wise contrastive loss to capture distinct flow-specific characteristics. Additionally, we develop a regularizer to align output features with these flow-specific representations, enabling a more comprehensive understanding of mobility dynamics. To validate our model, we conduct extensive experiments in Chicago, New York, and Washington, D.C. to predict income, educational attainment, and social vulnerability. The results demonstrate that our model outperforms state-of-the-art models.
प्रस्तुत लेखमा नेपालको गोलिया काठ मापनको ऐतिहासिक पृष्ठभूमि र विभिन्न मापदण्डको विकास र विस्तारबारे विवेचना गर्नुका साथै उपलब्ध तथ्याङ्क र सूचनाको उपयोग गरेर मापदण्डको विकासक्रमको समीक्षा गरिएको छ । गोलिया काठ उत्पादक, गोलिया प्रशोधन गर्ने काठ व्यवसायी र स्वतन्त्र वन विज्ञसँगको अनौपचारिक छलफलबाट प्राप्त जानकारी उपयोग गरेर मापदण्ड परिवर्तनमा प्रभाव पार्ने आन्तरिक र बाह्य शक्तिको पहिचान गरिएको छ । काठ व्यवसायीको पक्षपोषण हुने गरी मापदण्ड परिवर्तन गर्ने निर्णय भएको आशङ्का गर्ने सुविधा घटनाक्रमले दिएको छ । उक्त पृष्ठभूमिमा मापदण्ड परिवर्तनको अर्थराजनीति बारे विश्लेषण र विवेचना गरिएको छ । मापदण्ड परिवर्तनबाट हुन पुगेको गोलियाको अवमूल्यनले उत्पादन कार्यमा संलग्न श्रमिक, निजी रुख धनी, साना किसान, सामुदायिक वन समूहको आम्दानीमा परेको नकारात्मक प्रभावबारे तथ्यगत विश्लेषण गर्नुका साथै लेखकले आर्जन गरेको तालिम र विषयगत कार्यानुभव समेतको आधारमा आलोचनात्मक समीक्षा गरिएको छ । निर्णय प्रक्रियामा स्वार्थ समूहको प्रभाव नरहेको पुष्टि गर्न सरकारी निकायले दाबी गर्ने मापन सूत्रको व्यावहारिक मान्यतालाई प्रस्तुत लेखले अस्वीकार गर्दै हालको मापदण्डको स्थानमा परिष्कृत मापदण्डलाई अभ्यासमा ल्याउँदा गोलिया उत्पादनमा सहभागी श्रमिक, साना किसान र वन उपभोक्ताको आम्दानीमा वृद्धि हुने र सरकारी राजस्व बढ्ने आकलन गरेकाले यसबारे पहलको निम्ति सम्बन्धित निकायको ध्यानाकर्षण गर्न पाँच बुँदे नीति सिफारिस गरिएको छ ।
Abstract (in English)
This article explores the historical evolution of log measurement in Nepal’s forestry sector, tracing its development and expansion over time. The review draws on available data and information, supplemented by insights from informal discussions with timber producers, wood traders, processing entities, and independent forest experts. These sources help identify both internal and external factors that have influenced changes in the standards. The sequence of events allows one to suspect that the decision has been made to change the log scaling standards in a manner that favors timber traders. Within this context, the article critically examines the economic and political dimensions of the changes, highlighting their adverse impacts - particularly the undervaluation of logs - on the incomes of log harvesting workers, private tree owners, smallholder farmers, and community forest groups. Drawing on the critical analysis of available data, as well as the author's academic training and professional experience, the article challenges the notion that the revision process was free from interest group influence. It argues instead that vested interests played a significant role in shaping the outcomes. The paper further anticipates that replacing the current standards with more refined ones could significantly boost the wages of workers, small farmers, and forest users, while also enhancing government revenue. To address this, the article concludes with a five-point policy recommendation aimed at encouraging relevant agencies to take appropriate action.
درک تعامل میان انسان و محیط در زمینه شهرنشینی فزاینده، یکی از چالشهای اصلی در حوزه مطالعات شهری است. این پژوهش با هدف ترسیم ساختار فکری و روندهای نوظهور در حوزه میانرشتهای علوم رفتاری و محیط ساختهشده، از یک رویکرد ترکیبی علمسنجی و تحلیل محتوا بهره میبرد. با تحلیل دادههای کتابشناختی از پایگاههای Scopus و Web of Science از طریق نرمافزار VOSviewer و بررسی محتوایی ۵۶ مقاله کلیدی، نقشه جامع این حوزه علمی ترسیم گردید. یافتهها نشان میدهد که پژوهشها عمدتاً بر برنامهریزی شهری (۳۳٪) و طراحی منظر (۲۱٪) متمرکز هستند. دو جریان فکری اصلی و مکمل شناسایی شد: یک جریان متمرکز بر ابعاد «روانشناختی-اجتماعی» رفتار و دیگری متمرکز بر تأثیر «فرم کالبدی و مداخلات برنامهریزانه»، که این دو رویکرد در نشریات مرجعی چون Journal of Cleaner Production و Transportation Research Part A تجلی یافتهاند. نتایج، بیانگر یک گذار پارادایمی از رویکردهای عینیگرایانه به سمت تحلیلهای عملگرایانه و یکپارچه است. این مقاله با شناسایی شکافها و قطبهای پژوهشی، راهنمایی برای مطالعات آتی جهت ارتقای کیفیت فضاهای شهری از طریق مداخلات طراحانه آگاهانهتر ارائه میدهد.
Urban transformations have profound societal impact on both individuals and communities at large. Accurately assessing these shifts is essential for understanding their underlying causes and ensuring sustainable urban planning. Traditional measurements often encounter constraints in spatial and temporal granularity, failing to capture real-time physical changes. While street view imagery, capturing the heartbeat of urban spaces from a pedestrian point of view, can add as a high-definition, up-to-date, and on-the-ground visual proxy of urban change. We curate the largest street view time series dataset to date, and propose an end-to-end change detection model to effectively capture physical alterations in the built environment at scale. We demonstrate the effectiveness of our proposed method by benchmark comparisons with previous literature and implementing it at the city-wide level. Our approach has the potential to supplement existing dataset and serve as a fine-grained and accurate assessment of urban change.
Recent evaluations of Large Multimodal Models (LMMs) have explored their capabilities in various domains, with only few benchmarks specifically focusing on urban environments. Moreover, existing urban benchmarks have been limited to evaluating LMMs with basic region-level urban tasks under singular views, leading to incomplete evaluations of LMMs' abilities in urban environments. To address these issues, we present UrBench, a comprehensive benchmark designed for evaluating LMMs in complex multi-view urban scenarios. UrBench contains 11.6K meticulously curated questions at both region-level and role-level that cover 4 task dimensions: Geo-Localization, Scene Reasoning, Scene Understanding, and Object Understanding, totaling 14 task types. In constructing UrBench, we utilize data from existing datasets and additionally collect data from 11 cities, creating new annotations using a cross-view detection-matching method. With these images and annotations, we then integrate LMM-based, rule-based, and human-based methods to construct large-scale high-quality questions. Our evaluations on 21 LMMs show that current LMMs struggle in the urban environments in several aspects. Even the best performing GPT-4o lags behind humans in most tasks, ranging from simple tasks such as counting to complex tasks such as orientation, localization and object attribute recognition, with an average performance gap of 17.4%. Our benchmark also reveals that LMMs exhibit inconsistent behaviors with different urban views, especially with respect to understanding cross-view relations.
The implementation of intelligent transportation systems (ITS) has enhanced data collection in urban transportation through advanced traffic sensing devices. However, the high costs associated with installation and maintenance result in sparse traffic data coverage. To obtain complete, accurate, and high-resolution network-wide traffic flow data, this study introduces the Analytical Optimized Recovery (AOR) approach that leverages abundant GPS speed data alongside sparse flow data to estimate traffic flow in large-scale urban networks. The method formulates a constrained optimization framework that utilizes a quadratic objective function with l2 norm regularization terms to address the traffic flow recovery problem effectively and incorporates a Lagrangian relaxation technique to maintain non-negativity constraints. The effectiveness of this approach was validated in a large urban network in Shenzhen's Futian District using the Simulation of Urban MObility (SUMO) platform. Analytical results indicate that the method achieves low estimation errors, affirming its suitability for comprehensive traffic analysis in urban settings with limited sensor deployment.
he physical demonstration of the rapid growth in urbanisation in developing countries like Nigeria is often evidence of the social and economic transformations occurring in these countries. This paper aims to assess urbanisation trends, urban renewal, and sustainable urban development in Nigeria in view of the governmental policies that affect urbanisation trends, urban renewal, and sustainable urban development. The paper reviews current literature on the causes of global Urbanisation trends, the effects of urbanisation trends, and Urbanisation in Nigeria, which have resulted from rapid population growth and changes in the urban structure. By aligning urbanisation, urban renewal strategies, and policies that foster sustainable urban development with the Sustainable Development Goals (SDGs), Nigeria can work towards creating cities that promote the safety, inclusivity, resilience, and sustainability of its inhabitants.
خیابانهای شهری، فضاهایی پویا و واجد حس حرکت به شمار میروند که برای استفاده پیاده و سواره و یا بعضاً فقط پیاده طراحی میشوند. این فضاها غالباً به نیازهای افراد استفادهکننده از آن، بهدرستی پاسخگو نبوده و مردم به خیابان بهعنوان مسیری صرفاً برای گذر سواره مینگرند. هدف از این پژوهش، بررسی جامعی از خیابان شهری و شناسایی شاخصهای محیطی و انسانی مؤثر در ارتقا کیفیت آن است. این تحقیق ازنظر هدف، کاربردی و ازنظر روش با استفاده از فن دلفی و روش معادلات ساختاری انجام شده است. با استفاده از روش اسنادی و کتابخانهای، نظرات و دیدگاههای صاحبنظران جمعبندی شده و بهصورت شاخصهای پیشفرض ارائه گشته است. در مرحله اول، جامعه آماری تحقیق 20 نفر از کارشناسان خبره در زمینه موردمطالعه در نظر گرفتهشده است. شاخصهای اولیه با توجه به نتایج پرسشنامه، در چهار مرحله با استفاده از تکنیک دلفی فازی تحلیلشده و شاخصهای نهایی با استفاده از آزمون کولموگروف-اسمیرنوف، نرمال بودن آنها سنجیده شده و جهت تأیید نهایی شاخصهای مستخرج از مرحله اول، از روش تحلیل عاملی تائیدی (CFA)، برای ایجاد مدل معادلات ساختاری استفاده شده است. در این بخش به دلیل نامعلوم بودن جامعه آماری با استفاده از فرمول کوکران حجم جامعه آماری 384 نفر از افراد عادی در نظر گرفته شد. در انتها با استفاده از آزمون فریدمن، شاخصها، رتبهبندی شده تا میزان تأثیرگذاری هر یک مشخص گردد. نتایج یافتهها حاکی از شناسایی کاملی از مجموعه شاخصهای مؤثر در ارتقا کیفیت خیابان شهید بهشتی شهر کرج را دارد.
Bahrain, a longstanding tourist destination in the Gulf region, has seen its economy benefit significantly from tourism. However, the improper development of tourism has led to negative impacts on urban tourism in historic areas, risking the loss of authenticity. This study aims to explore factors influencing the development of tourism strategies in Muharraq city, focusing on residents' perceptions. A qualitative approach was used, including a comprehensive literature review, interviews with residents to capture their views on tourism-related issues, and a self-administered questionnaire with key officials and stakeholders. The study identifies critical factors affecting tourism development and offers recommendations for enhancing cultural tourism in Muharraq. The findings provide valuable insights for policymakers to create sustainable strategies that balance economic growth with cultural preservation, ensuring that Muharraq remains a culturally vibrant city while promoting sustainable urban tourism. This research contributes to the broader field of urban tourism studies by highlighting the importance of local perceptions and participatory approaches in shaping effective tourism policies. By addressing key elements that influence tourism development, the study supports the creation of strategies that safeguard heritage while fostering sustainable growth in one of Bahrain's most culturally significant cities.
Condominium housing is a critical housing option, but its affordability measures continue to be debatable. This study examined the mutual effect of housing & transportation monthly expenses on housing location affordability and accessibility, considering three comparable locations- inner-city, intermediate, and outer-city condominium locations in Addis Ababa, Ethiopia. 1152 condominium residents were surveyed to assess urban housing location affordability using the combined H+T affordability index, GIS, one-way ANOVA, and Logit model. Housing affordability is diversified in the city, distance to CBD & transport are significant factor. Outer-city and intermediate neighbourhoods are unaffordable & inaccessible, with 55% and 48% index, respectively. Outer-city residents and lower-incomers face higher financial burdens. Nevertheless, inner-city is affordable & accessible, and residents enjoy better proximity to services. It contributes insights to enhance literature and debates on the model. H+T index provides up-to-date understanding and informs policymaking for innovative, smart, and sustainable, location-sensitive, integrated, and pro-poor policies.
Amina Aidaoui, Assoule Dechaicha, Djamel Alkama
et al.
As urbanization continues to shape the world's landscape, concerns have intensified over environmental degradation and depletion of natural resources. Accordingly, international agendas emphasize managing urban sprawl for inclusive, resilient, and sustainable cities. On this basis, this study consists of exploring the nexus of urbanization and advanced technologies following a methodological approach based on a bibliometric analysis using the Dimensions Database to analyse research related to urban sprawl and LULC Changes from 1994 to the recent years; and a systematic review to synthesize existing literature on different methodologies integrating GeoAI technologies and LULC Analytics in the process of monitoring landscape, which optimizes Urban Planning and empowers predictive modelling to monitor environmental changes, therefore, promoting intelligent decision-making and inclusive growth via enabling the creation of targeted policies that address socio-economic disparities, environmental sustainability and infrastructure enhancement. By improving comprehension of scientific concepts, this article aims to fill the knowledge gap between urban studies and remote sensing using machine learning.
Shahed Alhadyan, Mohammad AlRahahleh, Mysaa Khwaileh
Addressing economic and social inequalities in urban settings, particularly those that affect marginalized groups, is becoming more challenging. In less privileged urban areas, women entrepreneurs face restricted opportunities, specifically in limited retail activities in urban spaces. This study examines the effects of implementing a tactical urbanism solution known as "Retailscape," as represented by Spacena, to address the existing socio-economic disparity. Spacena is an urban furniture piece designed to respect and accommodate PWD, serving as a platform for showcasing locally made products. Employing qualitative methods, including focus groups, interviews, and observations, the research assesses Spacena's economic and social impact. Key themes identified through coding reveal a strong desire for inclusive spaces, economic empowerment, and enhanced social integration. Findings indicate that Spacena is perceived as an opportunity for economic advancement, income generation, and social interaction among residents. However, concerns about project sustainability and regulatory challenges persist. This study demonstrates that tactical urbanism can effectively address economic disparities and foster social cohesion in marginalized communities, suggesting that similar small-scale interventions could have broad, positive implications for sustainable urban design. The findings highlight how Spacena’s low-cost, scalable design and its positive impact on community inclusivity can serve as a model for replicating similar urban interventions in areas with comparable economic and social challenges.
This paper chronicles the history of interstate highway construction through the Weequahic Section of Newark, New Jersey. It expands the analysis of urban redevelopment in Newark, New Jersey, by shifting the focus from the Central Ward, the primary site of urban renewal, to the Weequahic Section, one of several districts in the broader Newark landscape. Tracing how urban renewal led to a broader set of changes in the Newark cityscape, this paper examines how city and state officials exploited Newark’s geographic resources, not for the benefit of Weequahic residents or Newark citizens more generally, but for downtown and regional commercial interests, and suburban commuters. Using newspapers to map out the chronology of events; municipal and state studies, and official correspondence to document state intentions and policy decisions; and organizational minutes, flyers, and correspondence to discern local reactions to highway construction, this work will show that the construction of the highway through Weequahic was not inevitable.
ABSTRACT Social sustainability is an increasingly important aspect of urban development and renewal. Other than looking at preserving the greenery, ecosystems, and physical environment, urban scientists are also looking at ensuring the preservation of history, heritage, identity, and the memories of the people involved. With an increasing demand for public participation in the process of urban and heritage preservation, social sustainability cannot be achieved without the involvement of communities and individuals who are the “most ordinary everyday citizens.” Hence, capturing the oral history accounts and personal narratives of these “most ordinary everyday citizens” becomes crucial in documenting life and the collective or social memory of a place. In Singapore, Kampong Lorong Buangkok is the last remaining village or kampong on the mainland. Under the current Urban Redevelopment Authority (URA) Masterplan 2019, the kampong is expected to give way to a 3-lane bi-directional highway, 2 schools (primary and secondary), and a public park. This paper provides a glimpse into the broad themes drawn from the oral history accounts and personal narratives documented from the residents living in the kampong, as part of a project to capture the rich history and heritage about the kampong and its residents, in a bid to “preserve” the kampong as urbanization and gentrification are imminent.
In Tarlabasi, an Istanbul neighbourhood facing massive redevelopment and displacement, marginalised residents speak about belonging, stigma, and what their community means to them. Based on a long-term ethnographic study that includes interviews, photographs, and archival research, Constanze Letsch examines how territorial stigmatisation is weaponised by the state and how differently stigmatised groups try to fight against the vilification of their neighbourhood. The contested plans of urban renewal threaten not only their homes and workplaces but a rapidly vanishing Istanbul: socio-demographic interdependencies and networks that have developed over decades.
Quantification of the overall characteristics of urban mobility using coarse-grained methods is crucial for urban management, planning and sustainable development. Although some recent studies have provided quantification methods for coarse-grained numerical information regarding urban mobility, a method that can simultaneously capture numerical and spatial information remains an outstanding problem. Here, we use mathematical vectors to depict human mobility, with mobility magnitude representing numerical information and mobility direction representing spatial information. We then define anisotropy and centripetality metrics by vector computation to measure imbalance in direction distribution and orientation toward the city center of mobility flows, respectively. As a case study, we apply our method to 60 Chinese cities and identify three mobility patterns: strong monocentric, weak monocentric and polycentric. To better understand mobility pattern, we further study the allometric scaling of the average commuting distance and the spatiotemporal variations of the two metrics in different patterns. Finally, we build a microscopic model to explain the key mechanisms driving the diversity in anisotropy and centripetality. Our work offers a comprehensive method that considers both numerical and spatial information to quantify and classify the overall characteristics of urban mobility, enhancing our understanding of the structure and evolution of urban mobility systems.
Urban land use structures impact local climate conditions of metropolitan areas. To shed light on the mechanism of local climate wrt. urban land use, we present a novel, data-driven deep learning architecture and pipeline, DeepLCZChange, to correlate airborne LiDAR data statistics with the Landsat 8 satellite's surface temperature product. A proof-of-concept numerical experiment utilizes corresponding remote sensing data for the city of New York to verify the cooling effect of urban forests.
Abstract This article examines The Boston Document, a documentary photography project that chronicled urban renewal in Boston from 1959–1968. The project was created by a largely unknown yet crucial documenter of Boston, Irene Shwachman (1915–1988). A large portion of the document focuses on the demolition of the West End, a neighborhood home to lower-class and immigrant residents. In the early 1950s, the Boston Redevelopment Authority labeled the neighborhood a slum, and implemented a redevelopment plan. The West End’s ‘renewal’ resulted in the destruction of a vibrant, diverse neighborhood and the displacement of thousands of residents. This article argues that Shwachman reinterprets a documentary photography methodology to incorporate the perspectives and histories of city citizens in her chronicle of urban change. Through this approach, I argue that Shwachman’s photographs present a subjective, personal investigation into Boston, centering the perspectives of city residents and underscoring how people shape and activate their urban landscape. In examining The Boston Document in this renewed context, this article reclaims histories and perspectives removed from Boston’s landscape through redevelopment.