Relying on in-domain annotations and precise sensor-rig priors, existing 3D occupancy prediction methods are limited in both scalability and out-of-domain generalization. While recent visual geometry foundation models exhibit strong generalization capabilities, they were mainly designed for general purposes and lack one or more key ingredients required for urban occupancy prediction, namely metric prediction, geometry completion in cluttered scenes and adaptation to urban scenarios. We address this gap and present OccAny, the first unconstrained urban 3D occupancy model capable of operating on out-of-domain uncalibrated scenes to predict and complete metric occupancy coupled with segmentation features. OccAny is versatile and can predict occupancy from sequential, monocular, or surround-view images. Our contributions are three-fold: (i) we propose the first generalized 3D occupancy framework with (ii) Segmentation Forcing that improves occupancy quality while enabling mask-level prediction, and (iii) a Novel View Rendering pipeline that infers novel-view geometry to enable test-time view augmentation for geometry completion. Extensive experiments demonstrate that OccAny outperforms all visual geometry baselines on 3D occupancy prediction task, while remaining competitive with in-domain self-supervised methods across three input settings on two established urban occupancy prediction datasets. Our code is available at https://github.com/valeoai/OccAny .
Urban design profoundly impacts public spaces and community engagement. Traditional top-down methods often overlook public input, creating a gap in design aspirations and reality. Recent advancements in digital tools, like City Information Modelling and augmented reality, have enabled a more participatory process involving more stakeholders in urban design. Further, deep learning and latent diffusion models have lowered barriers for design generation, providing even more opportunities for participatory urban design. Combining state-of-the-art latent diffusion models with interactive semantic segmentation, we propose RECITYGEN, a novel tool that allows users to interactively create variational street view images of urban environments using text prompts. In a pilot project in Beijing, users employed RECITYGEN to suggest improvements for an ongoing Urban Regeneration project. Despite some limitations, RECITYGEN has shown significant potential in aligning with public preferences, indicating a shift towards more dynamic and inclusive urban planning methods. The source code for the project can be found at RECITYGEN GitHub.
This study examines a case of urban renewal in Shibuya, one of Tokyo’s most prominent downtown areas, featuring Miyashita Park, a dilapidated 10,000‐square‐meter park that transformed into a modern commercial complex consisting of a multistory commercial building with a roof park and an 18‐story hotel. Shibuya Ward, the park’s administrator, selected private companies—initially Nike Japan and subsequently Mitsui Fudosan—as the redevelopment agency to install and operate park facilities—a public–private partnership that went beyond the conventional park concept by building sophisticated commercial facilities. This redevelopment, which began at the end of the 2000s, was met with fierce opposition. To investigate these dynamics, the article draws on qualitative content analysis of Shibuya Ward Assembly minutes (2008–2020), obtained from the official digital archive, alongside media coverage. By systematically reviewing committee and plenary debates where key policy decisions were made, the study traces how the project was planned, debated, and implemented. The findings show that despite legal ambiguities and strong criticism, the ward advanced the project by framing the park as an unprofitable facility requiring private‐sector expertise, redefining regulatory boundaries, and limiting resident participation to a formal procedure. This process illuminates how public–private‐partnership‐led redevelopment, embedded in Japan’s broader neoliberal urbanism, can proceed through strong political conviction at the local level amid opposition and limited transparency. The study contributes to international debates on urban public space, highlighting how local governments act not only as regulators but also as active promoters of privatization and the erosion of urban commons.
The micro-renewal of rural heritage in urban villages transcends spatial transformation, profoundly altering social structures and relational dynamics. Recent research has emerged concerning the cultural impact of rural revitalization on rural heritage. However, little research has been undertaken regarding the specific mechanisms via which various renewal orientations influence the community. This study focuses on the case of Whampoa Village in Guangzhou, China, specifically highlighting the rehabilitation of its ancestral temples. Utilizing a field–space–society analytical framework, it analyzes how these revitalized ancestral temples enhance community resilience and instigate a reverse reconfiguration of spaces. Moreover, it emphasizes that the varied rehabilitation approach of ancestral temples, by including different social groups, fosters the establishment of new community connections. NGOs and small investors act as the primary catalysts for the preservation and inheritance of cultural heritage. The redevelopment initiative in Whampoa Village has enhanced spatial diversity, thereby reinforcing and transforming existing community structures. Nonetheless, it highlights the potential for spatial inequities arising from capital-driven commercialization in these rural regions. This article seeks to enrich the global database of cultural heritage by including cases from southern China and to contribute to the literature on the preservation of rural cultural assets.
مقدمه: نزاع دستهجمعی یکی از پدیدههای اجتماعی چالشبرانگیز است که از دیرباز در اجتماعات محلی بویژه روستایی وجود داشته است. ایران بعلت تنوع قومیتی و همه گیری پدیده مهاجرت و تبعید در طول تاریخ همواره بستری مناسب برای این پدیده بوده است. پژوهش حاضر با هدف شناخت علل و منشاء نزاع ها و رقابت های محلی بین دو روستای باغخواص و علی آباد قشقایی از توابع شهرستان ورامین و اثرات آن بر توسعه اجتماع محلی انجام شده است. این پژوهش همچنین به دنبال ارائه راهکارهایی برای کنترل و کاهش این پدیده می باشد. روش: رویکرد پژوهش حاضر کیفی و مبتنی بر نظریه داده بنیاد است. به جهت جمع آوری داده ها مصاحبه های نیمه ساختارمندی با 36نفر از مطلعین محلی و اعضای سازمان های محلی تا رسیدن به اشباع نظری انجام شد. یافته ها: تحلیل داده های مطالعه و مدل پارادایمی نشان می دهد، حاشیه نشینی، تفاوت فرهنگی، تعصبات درون گروهی، اختلافات ملکی و مالکیتی، کسب سرمایه نمادین و گذشته نگری عوامل موثر بر پدیده تمایزگذاری بوده اند. اهالی در مقابل این پدیده راهبردهای نزاع جمعی، رقابت طلبی، انسداد منابع، چانه زنی منفی و حمایت گری را اتخاذ کرده اند، پیامد این راهبردها نیز تخریب گری، گسست ظرفیت های اجتماعی، مهاجرت، کاهش مشارکت، فقدان اعتماد نهادی و نهادخواهی بوده است.نتیجه گیری: یافته های پژوهش نشان می دهد اصلی ترین راهبردها جهت کنترل نزاع ها و رقابت های محلی، تغییر شیوه ها و نوع محصول کشاورزی، نهادخواهی و بسط الگوی موفق تعاملات سنتی–مناسکی به سایر عرصه ها می باشد.
مقالۀ حاضر به مطالعۀ نقش کارآفرینان در تکامل صنعت نساجی مدرن در منطقۀ شاهدیۀ یزد میپردازد. در این مطالعه تأثیر عوامل جغرافیایی، اجتماعی و فرهنگی در این فرایند و همچنین چگونگی بهرهگیری کارآفرینان از حکشدگی محلی و خانوادگی برای توسعۀ این شبکه تحلیل میشود.روششناسی این تحقیق کیفی و مطالعۀ موردی است و از تکنیکهای متعدد جمعآوری دادهها استفاده شده که مهمترین آنها مصاحبههای نیمهساختاریافته است.یافتهها نشان داد شبکۀ نساجی شاهدیه از سال 1330 تا 1402 دو چرخۀ تکامل را پشت سر گذاشته است. چرخۀ اول شبکه مبتنی بر تولید روفرشی از سال 1330 تا 1368 است. چرخۀ دوم با تولید رومبلی از سال 1368 آغاز شد. توسعۀ صنعت نساجی مدرن در شاهدیه را میتوان نمونۀ بارزی از شکلگیری و رشد یک شبکۀ بازیگر متشکل از بازیگران انسانی (کارآفرینان محلی، جوامع خانوادگی و محلی کارآفرینان، مقامات دولتی محلی، طراحان پارچه، تاجران نخ و پارچه و غیره) و نهادهای غیرانسانی (میراث اجتماعی-اقتصادی و صنعتی منطقه، موقعیت جغرافیایی، تغییرات فناورانه در نساجی، تغییرات اقلیمی و کمبود آب، تغییر ذائقههای اجتماعی و...) دانست.نتیجۀ تحقیق بیانگر آن است که توسعۀ این صنعت، حاصل درهمتنیدگی پیچیدۀ کنشگران انسانی (کارآفرینان، خانوادهها و دولت) و هستارهای غیرانسانی (میراث، جغرافیا، فناوری و اقلیم) است. این رویکرد نشان میدهد چگونه این همزیستی به تابآوری و پویایی اکوسیستم صنعتی منجر شده که میتواند الگویی موفق برای توسعه در مناطق مشابه باشد.
با افزایش روند شهری شدن در جهان، میزان مصرف در حال افزایش است. یک پیامد اجتنابناپذیر مصرف بیشتر، افزایش سریع مقدار زباله جامد تولیدی است. امروزه شرایط مدیریت پسماند در کشورهای درحالتوسعه نامناسب است. طی دو دهه اخیر، علیرغم فعالیتهای سازمان مدیریت پسماند و سازمان فرهنگی شهرداری مشهد برای ترویج تفکیک زباله و مدیریت صحیح پسماند، نرخ تفکیک زباله از مبدأ در شهر مشهد در حد قابل قبول نیست و نیاز است به بررسی چالشهای مدیریت پسماند است تا مشکلات و دلایل مدیریت نامناسب پسماند در شهر مشهد شناسایی شود. هدف اصلی تحقیق شناسایی چالشهای مدیریت پسماند و دلایل آن در شهر مشهد است. دادههای این مطالعه کیفی از طریق مصاحبه عمیق گردآوری شده و از روش تحلیل مضمون برای تحلیل دادهها استفاده شده است. با کمک نمونهگیری هدفمند و با معیار اشباع نظری با 25 نفر از مصاحبهشوندگان مصاحبه انجام شد و نهایتاً دادههای گردآوری شده در قالب دو مضمون فراگیر و هشت مضمون سازمان دهنده، کدگذاری و تحلیل گردید. نتایج تحقیق درباره مشکلات مدیریت پسماند در مشهد نشان میدهد که چهار مضمون سازمان دهنده رفتارهای ناپایدار زیستمحیطی شهروندان، نارسایی قانونی-ساختاری، ناکارآمدی اجرایی و مشکلات مرتبط با زائران در ایام پیک مهمترین چالشهای مدیریت پسماند در شهر مشهد هستند. همچنین چهار مضمون سازمان دهنده خلأهای فرهنگی و اجتماعی، نگاه کالایی و درآمدی به پسماند، بازدارندگی پایین قوانین و ضعف سازمانی مهمترین دلایل چالشهای مدیریت پسماند در شهر مشهد است.
Public participation is essential to preserving cultural heritage and achieving heritage sustainability. Although external drivers such as policy, economy, and technology have been widely studied, internal motivations – particularly generational differences in heritage value perception – remain underexplored. This study adopts the Value – Attitude–Behaviour (VAB) hierarchy to examine how differences in heritage value perception influence place attachment and participation intention. Using a structured non-probability survey, the study finds that Gen-Z shows the highest participation intention, while Gen-Y is the lowest, reflecting differences in value perception and attachment: Gen-Z prioritises aesthetic and scientific values; Gen-Y shows weaker social and cultural value perceptions; Gen-X shows stronger emotional ties. Social and cultural values are the strongest predictors of participation, with historic value having the greatest indirect effect. These findings support generation-responsive, locally grounded, and inclusive heritage strategies that enhance social cohesion and sustainable urban development.
The article discusses the post-war redevelopment of Amuri, a wooden workers' district in Tampere, identifying those involved in the redevelopment and the forces driving this process. Amuri is special due to the area's close connection to the Finlayson textile factory. Urban renewal provided a platform for collaboration between various stakeholders, enabling the implementation of local governance. The renewal was driven forward by city officials and planners, landowners such as Finlayson, and organisations such as Amuri Oy. Finlayson's role was particularly significant in terms of housing policy. While the renovation was characterised as technocratic and lacked a cultural and social dimension, the interview material used in this article provided insight into the role of residents as creators of desired modernity.
Neeraj Pandey, Abhineet Agarwal, Raju Roychowdhury
et al.
Analysis of the urban population fraction data for sixteen populous countries over the last fifty years reveals a universal increase in urbanization, exhibiting four qualitatively distinct temporal patterns: (i) continuously accelerating growth, (ii) continuously decelerating growth, (iii) two-phase growth transitioning from acceleration to deceleration, and (iv) two-phase growth transitioning from deceleration to acceleration. To understand the origin of these diverse urbanization trajectories, we develop a simple coarse-grained model in which a country is segregated into two regions, a rural and an urban region. Population in each region evolves due to natural (sexual) growth and migration from rural to urban areas, with the migration rate governed by economic inequality, quantified through the difference in GDP per capita between the two regions. The GDP per capita of both regions is assumed to grow exponentially with distinct rates. We demonstrate that this minimal model, involving four dynamical variables and a small number of demographic and economic parameters, is capable of reproducing all four empirically observed urbanization patterns. Assuming demographic and economic parameters remain approximately constant over a 50-year timescale, we estimate coarse-grained parameters for the United States using empirical data and obtain optimized values that accurately reproduce its observed urbanization trajectory. Our results highlight how simple demographic-economic interactions can generate rich and diverse urbanization dynamics.
Analyzing and modeling the mobility process with tour behavior is fundamental to understanding a wide range of complex systems, including animal foraging, human mobility and freight transportation. However, despite their importance, the distribution of tour length has long been neglected in individual human mobility models. To fill this gap, we analyze Foursquare users' check-in data and find that the distribution of urban tour length follows a truncated power-law distribution. To reproduce the universal scaling law for human mobility in urban areas, we introduce a tour terminate-continue model. Our model reproduces not only the urban tour length distribution but also Heaps' law, Zipf's lawand the distribution of the radius of gyration, providing a new perspective for characterizing individual human mobility.
Urban region representation is essential for various applications such as urban planning, resource allocation, and policy development. Traditional methods rely on fixed, predefined region boundaries, which fail to capture the dynamic and complex nature of real-world urban areas. In this paper, we propose the Boundary Prompting Urban Region Representation Framework (BPURF), a novel approach that allows for elastic urban region definitions. BPURF comprises two key components: (1) A spatial token dictionary, where urban entities are treated as tokens and integrated into a unified token graph, and (2) a region token set representation model which utilize token aggregation and a multi-channel model to embed token sets corresponding to region boundaries. Additionally, we propose fast token set extraction strategy to enable online token set extraction during training and prompting. This framework enables the definition of urban regions through boundary prompting, supporting varying region boundaries and adapting to different tasks. Extensive experiments demonstrate the effectiveness of BPURF in capturing the complex characteristics of urban regions.
Oladiran Johnson Abimbola, Taiwo Adewumi, Musa Abubakar
As the global climate changes, urban heat island (UHI) is a critical factor in ever expanding urban landscape, studying and mitigating the UHI is important for remediating climate change and providing for the human and ecosystem health within the urban area. This study has aimed to study the UHI in Lafia, a tropical city in Nigeria and its other impacted factors such as the land surface temperature (LST) and normalized difference vegetation index (NDVI), with the aim of mitigating the UHI effect. Landsat 4, 5, 7 and 8 together with Sentinel data has been used for this study, through the public archive of the Google Earth Engine data catalog, used also is the ERA5 data from the same data catalog. The result showed that the expanding city of Lafia is experiencing significant UHI with increase in temperatures in the city and adjoining areas, it was found that the vegetation cover in Lafia city is rapidly disappearing as a result of urbanization leading to more UHI and greater discomfort to the inhabitant of the city. Several remediation steps were suggested to mitigate the UHI effect in Lafia.
Oluwafemi Kehinde AKANDE, Lilian Chioma OBI-GEORGE, Jonam Jacob LEMBI
et al.
The outbreak of COVID-19 and its consequences have altered people's perceptions of the availability of high-quality housing. Nigeria, the most populous country in sub-Saharan Africa, has taken many initiatives to address its growing population's housing demands. However, considerable focus has been placed only on housing quantity at the expense of housing quality. This study aims to investigate the interplay of factors affecting the provision of high-quality public housing projects in Nigeria. The objective is to identify the factors that significantly influence project success and failure in the delivery of quality public housing projects. A descriptive survey design with 351 randomly selected households and built environment experts (BEPs) was used. A self-developed structured questionnaire was used to collect data from households, buildings, and professionals over the course of three months. The findings indicate that in several buildings, the indoor air temperature and relative humidity extend acceptable limits (for example, 28 °C and 70% RH), which can have an effect on indoor air quality. Meanwhile, responses from the BEPs revealed that in order to develop high-quality housing, adequate project financing, evaluation of suitable building materials, and project management expertise were required. The study's conclusion emphasises that considering only the number of houses required to accommodate Nigeria's growing urban population is insufficient; rather, other factors such as appropriate design for improved air quality, high-quality and appropriate building materials, adequate project financing, and project management expertise would result in the quality delivery of livable public housing in Nigeria.
The revitalization and renewal of existing urban space is a primary objective in the redevelopment of high-density transit-oriented development (TOD) areas. In this context, offering incentive zoning bonuses is a critical tool for optimizing urban space. However, in some subway-adjacent plots with high building densities, traditional incentive zoning methods face limitations due to insufficient horizontal space. These areas increasingly rely on multi-ground public spaces to balance density with public services. This study investigates new methods of incentive zoning between commercial areas and public spaces in multi-ground public spaces within subway-adjacent plots, using 33 rail transit complexes in Shanghai, China, as the research subject. The findings are presented in the form of visual guidelines to provide guidance on architectural control, with the goal of enhancing the quality of urban public spaces. In this research, a multiple linear regression model is employed, using GNCS_AR (the ratio of ground non-commercial stay to area), which captures both efficiency and equity in public space quality, as the dependent variable. A model is developed in SPSS, incorporating independent variables such as TCA (total commercial area), POS (public open space area), PIS (public indoor space area), and MGZFs (multi-ground zoned floors). This model provides a framework for developers to manage and control public space in multi-ground settings within rail transit complexes. Research has found that MGZFs alone cannot be included as the independent variable in the model, as their absence leaves the model unable to explain three-dimensional spaces. However, incorporating the ratio of RIOPS (the ratio of indoor to outdoor public space) to MGZFs significantly improves the model’s correlation and explanatory capacity. The resulting model demonstrates that, under different POS and MGZF tiers, the influence of PIS and TCA on public space quality varies. Using a typological approach, the study categorizes these complexes into five tiers based on POS and MGZFs. Within the same tier, changes in PIS and TCA types lead to variations in public space quality. The empirical results are translated into diagrams that link data, forms, and indicators to guide the development of three-dimensional spaces. These diagrams, which can be named visual guidelines, provide practical guidelines for optimizing public spaces in these subway-adjacent plots.
Urban Building Exteriors are increasingly important in urban analytics, driven by advancements in Street View Imagery and its integration with urban research. Multimodal Large Language Models (LLMs) offer powerful tools for urban annotation, enabling deeper insights into urban environments. However, challenges remain in creating accurate and detailed urban building exterior databases, identifying critical indicators for energy efficiency, environmental sustainability, and human-centric design, and systematically organizing these indicators. To address these challenges, we propose BuildingView, a novel approach that integrates high-resolution visual data from Google Street View with spatial information from OpenStreetMap via the Overpass API. This research improves the accuracy of urban building exterior data, identifies key sustainability and design indicators, and develops a framework for their extraction and categorization. Our methodology includes a systematic literature review, building and Street View sampling, and annotation using the ChatGPT-4O API. The resulting database, validated with data from New York City, Amsterdam, and Singapore, provides a comprehensive tool for urban studies, supporting informed decision-making in urban planning, architectural design, and environmental policy. The code for BuildingView is available at https://github.com/Jasper0122/BuildingView.
Estimating the economic risks of climate shocks and climate stressors on spatially heterogeneous cities over time remains highly challenging. The purpose of this paper is to present a practical methodology to assess the economic risks of climate change in middle-income cities to inform municipal climate response strategies. Building on a capital-based framework (CBF), spatially disaggregated baseline and future scenario scores for economic wealth and its exposure to climate change are developed for six different classes of capital across 77 major suburbs in Cape Town, South Africa. Capital-at-risk was calculated by combining relative exposure and capital scores across different scenarios, with population impacted for major suburbs and the city’s eight main planning districts. The economic risk assessment presented here provides a generic approach to assist city managers through an enhanced understanding of the relative levels of capital endowment across the city vis-à-vis relative levels of exposure to climate-related hazards over time.