Hasil untuk "City planning"

Albert Gerhards

Rapid demographic change and the ongoing process of dechurching are bringing about significant transformations in Germany’s sacred building landscape. Strategies for managing churches no longer in regular liturgical use vary considerably. In some locations, buildings are quickly disposed of, sold, or demolished, whereas in others efforts are made to reuse them in ways that remain as close as possible to their original function. This applies to both Catholic and Protestant churches. As former parishes are merged into larger pastoral units, individual buildings are often assigned specialised functions: children’s church, youth church, city church, book church, cultural church, vespers church, ecumenical church, columbarium church, to name but a few. These adaptations are sometimes accompanied by substantial architectural interventions, and sometimes not. Churches frequently combine multiple uses under a single roof. Hybrid use opens the church to the urban environment, which benefits from its prominent location. Conversely, the community gains from shared use by other organisations and groups, both financially and socially. From a theological perspective, this represents an opportunity for a new mode of being in the world in the era of the post-popular church.

Alireza Sarsangi Aliabad, Ara Toomanian, Majid Kiavarz et al.

Extended Abstract:1. IntroductionElectricity is an essential input for all production systems and a necessity for all modern families. Hence, relevant energy policies are needed to induce efficient electricity consumption in the residential sector in many countries due to the effects of global warming and security of energy supply. Forecasting electricity demand at a regional or national level is crucial for planning to ensure optimal energy management. Various factors influence household consumption patterns. Factors such as employment rate, residential area, distance from green space, etc. affect electricity consumption. The purpose of this study is to investigate the impact of various factors on electricity consumption in residential homes in Yazd city. The results of this study will be useful for making management decisions for planning to reduce electricity consumption.2. Research MethodologyThe present study was conducted in the city of Yazd, which has a hot and dry climate and is extremely hot in the summer. Data on electricity consumption of Yazd city subscribers was obtained from the provincial electricity distribution company for the years 2016 to 2019. Data related to the city's buildings, such as (current use, building height, area, building shape, and building age), as well as streets, existing street widths, and the location of parks and green spaces, were obtained from the municipality. Spatial configuration indices including: connectivity, depth, coherence and control were estimated. The urban physical parameters of the components of parcel area, building area, yard area, building height, building volume were calculated. Then, association rules were used to examine the existing relationships. Spatial Association Rules are a set of rules that describe the relationships between different features in spatial data. These rules are a capability to find unknown relationships in spatial data. Spatial association rules are rules that indicate the implication of a set of features on another set of features in a spatial database. These rules are introduced to discover the rules between products in large-scale transactional data. 3. Results and discussionResidential electricity consumption data was analyzed using Moran's spatial autocorrelation index and based on Euclidean distance. The results of the study of hot and cold spots of residential electricity consumption data in the study area showed that the distribution of electricity consumption in residential homes is asymmetrical. That is, the number of homes with very high electricity consumption is greater than the number of homes with very low electricity consumption.In total, 3.2 percent of the number of parcels in the region is made up of Low_High outliers and 4.7 percent is High_Low. In the present study, the Apriori algorithm was used. The Apriori algorithm is known as one of the main methods in data mining for discovering association rules. The results of the rule review using Apriori showed that in rule one: buildings with a height of 5 to 8 meters that are located in a new urban context are most likely (93%) to have an annual electricity consumption of more than 3,500 units. Rule two: buildings that are located in a new urban context and their control is less than 1 are most likely (87%) to have an annual electricity consumption of more than 3,500 units. Rule three: buildings that are located in parcels with an area of 150 to 250 square meters and a local connectivity of 2-3 are most likely (74%) to have an annual electricity consumption of more than 3,500 units. Rule four: buildings that are located in parcels with an area of 150 to 250 square meters and in a new urban context and with a yard area of less than 75 square meters are most likely (61%) to have an annual electricity consumption of more than 3,500 units.4. ConclusionAssociation rules are able to extract patterns that cannot be easily identified by traditional methods and provide useful information for optimizing energy consumption.One of the major challenges in using association rules in big data is the need for time-consuming and resource-intensive processing, especially when the data is complex and contains a large number of features. Association rules are usually designed for discrete data, and for numerical data, complex preprocessing such as converting the data to categorical values may be required. Also, the appropriate selection of parameters such as minimum support and confidence can be difficult and have a significant impact on the quality and applicability of the extracted results. It is suggested that in future studies, hourly electricity consumption data should be used if possible so that the effects of more factors can be examined. -

Natalia G. Fedotova

The article presents the results of a study on the cultural code of the city, using Saint Petersburg as a case study. The author conceptualizes the city as a symbolic space saturated with meanings that can be encoded and decoded. Accordingly, the study employs the category of the ‘cultural code’ as a relatively stable system for organizing cultural meanings mentally rooted in the collective representations of the city and determining how the city is perceived by its residents. The cultural code reflects the city’s uniqueness and its distinction from other urban environments; it is interpreted through images transmitted from one generation to the next and preserved in the city’s cultural memory. However, studies that examine the city’s cultural code through the analysis of residents’ perceptions—those who serve as its carriers and transmitters—and that address their mental attitudes and subjective modes of imagining the city remain relatively scarce. This article, therefore, presents the results of an empirical study of the cultural code of Saint Petersburg. The research was conducted through structured interviews with residents of Saint Petersburg and was based on Lynch’s mental mapping methodology. This method was adapted to use verbal data collection techniques, with an emphasis on identifying the value foundations underlying citizens’ perceptions of the city across the following thematic blocks: a) natural and climatic characteristics; b) memorable historical events and places of memory; c) spatial characteristics; d) prominent figures; e) dominant images and symbols of the city. The sample consisted of 50 respondents selected according to age, gender, occupation, length of residence, and district of residence. The empirical cross-section of residents’ opinions was obtained through qualitative research methods, which made it possible to reveal their deep-seated mental attitudes and identify the most significant elements of the city’s cultural code. The findings have practical relevance, as the knowledge gained can serve as a valuable resource for the city’s development, both in shaping its external image and in informing cultural policy and urban planning.

Andrea Tiranti, Francesco Wanderlingh, Enrico Simetti et al.

Accurate tracking of underwater acoustic sources is critical for a variety of marine applications, yet remains a challenging task due to communication constraints and environmental uncertainties. In this regard, this paper addresses the problem of underwater acoustic source tracking using a team of autonomous underwater vehicles (AUVs). The core idea is to optimize the guidance of each agent to achieve coordinated motion planning that leads to optimal geometric configurations with respect to the target, thereby enhancing tracking performance. To tackle this, we propose a Distributed Model Predictive Control (DMPC) framework to improve performance and robustness. The control problem is formulated as a multi-objective optimization task, incorporating geometric observability, proximity to the target, and communication connectivity. A Receding Horizon Control (RHC) approach, coupled with an Unscented Transform (UT)-based prediction scheme, is employed to ensure longterm tracking accuracy while accounting for uncertainties. The optimization is distributed using the sequential multi-agent decision-making framework, combined with the Time-Division Multiple Access (TDMA) communication protocol. The proposed methodology is implemented in a simulation environment that accounts for the constraints of acoustic communication. The approach is compared with existing methods such as decentralized MPC and Particle Swarm Optimization (PSO).

Francesco Marzolla, Matteo Bruno, Hygor P. M. Melo et al.

In the quest for more environmentally sustainable urban areas, the concept of the 15-minute city has been proposed to encourage active mobility, primarily through walking and cycling. An urban area is considered a ``15-minute city" if every resident can access essential services within a 15-minute walk or bike ride from their home. However, there is an ongoing debate about the effectiveness of this model in reducing car usage and carbon emissions. In this study, we conduct a large-scale data-driven analysis to evaluate the impact of service proximity to homes on CO$_2$ emissions. By examining nearly 400 cities worldwide, we discover that, within the same city, areas with services located closer to residents produce less CO$_2$ emissions per capita from transportation. We establish a clear relationship between the proximity of services and CO$_2$ emissions for each city. Additionally, we quantify the potential reduction in emissions for 30 cities if they optimise the location of their services. This optimisation maintains each city's total number of services while redistributing them to ensure equal accessibility throughout the entire urban area. Our findings indicate that improving the proximity of services can significantly reduce expected urban emissions related to transportation.

Aysan Mokhtarimousavi, Michael Kleiss, Mostafa Alani et al.

This paper presents a study of computation and morphology of Louis Kahn City Tower project. The City Tower is an unbuilt design by Louis I. Kahn and Anne Tyng that integrates form and structure using 3D space triangular geometries. Although never built, the City Tower geometrical framework anticipated later developments in design of space-frame structures. Initially envisioned in the 1950s, the City Tower project is a skyscraper structure based on a tetrahedral and octahedral space frame called Octet-Truss. The aim of this study is to analyze the geometry of the City Tower structure and how it can be used to develop modular and adaptable architectural forms. The study is based on an analytical shape grammar that is used to recreate the original structure, and later to generate new structural configurations based on the City Tower's morphology. This study also investigates the potential applications of these findings in architecture and reveals the possibilities of using tetrahedrons and octahedrons as fundamental geometries for creating scalable and modular designs and presents initial findings.

Jianwei Sun, Qingsong He, Haofeng Wang

Cellular Automaton (CA) is widely used because of its ability to simulate complex spatiotemporal dynamic processes through applying simple rules. The basis of the CA model is the definition of transformation rules. During a simulation process, the rules determine the change of the cell state. However, existing processing methods calculate the driving factors based on single-point time (start time or end time), making it difficult to reflect the fact that numerous driving factors affecting the cell conversion dynamically change with time. Based on the time dynamics perspective and the data set of multiple time series, this paper designs a method of dynamic adjustment of driving factors of urban expansion on the local cell-scale. It uses linear, exponential, logarithmic, and polynomial fitting to develop a CA model of dynamic adjustment that conforms to the characteristics of local spatial evolution. The main conclusions of the paper are as follows: (1) The polynomial fitting has the highest average R2, indicating that the driving factors experiences large fluctuations over time; (2) Secondly, the simulation result kappa obtained by the four fitting methods is between 0.781–0.810, which is higher than the simulation accuracy obtained by using only a single time point. In other words, the factor does not dynamically fit with time and (3) The fitting accuracy of road density is a key indicator of correct and incorrect simulation parts of construction land. Our results demonstrate that the precision of the CA model may be significantly improved by capturing the time development law of environmental variables affecting urban development at the micro-scale.

Luis Sanchez, Luis Muñoz, Jose Antonio Galache et al.

This paper describes the deployment and experimentation architecture of the Internet of Things experimentation facility being deployed at Santander city. The facility is implemented within the SmartSantander project, one of the projects of the Future Internet Research and Experimentation initiative of the European Commission and represents a unique in the world city-scale experimental research facility. Additionally, this facility supports typical applications and services of a smart city. Tangible results are expected to influence the definition and specification of Future Internet architecture design from viewpoints of Internet of Things and Internet of Services. The facility comprises a large number of Internet of Things devices deployed in several urban scenarios which will be federated into a single testbed. In this paper the deployment being carried out at the main location, namely Santander city, is described. Besides presenting the current deployment, in this article the main insights in terms of the architectural design of a large-scale IoT testbed are presented as well. Furthermore, solutions adopted for implementation of the different components addressing the required testbed functionalities are also sketched out. The IoT experimentation facility described in this paper is conceived to provide a suitable platform for large scale experimentation and evaluation of IoT concepts under real-life conditions.

Li Yang, Zhipeng Luo, Shiming Zhang et al.

With the digitization of modern cities, large data volumes and powerful computational resources facilitate the rapid update of intelligent models deployed in smart cities. Continual learning (CL) is a novel machine learning paradigm that constantly updates models to adapt to changing environments, where the learning tasks, data, and distributions can vary over time. Our survey provides a comprehensive review of continual learning methods that are widely used in smart city development. The content consists of three parts: 1) Methodology-wise. We categorize a large number of basic CL methods and advanced CL frameworks in combination with other learning paradigms including graph learning, spatial-temporal learning, multi-modal learning, and federated learning. 2) Application-wise. We present numerous CL applications covering transportation, environment, public health, safety, networks, and associated datasets related to urban computing. 3) Challenges. We discuss current problems and challenges and envision several promising research directions. We believe this survey can help relevant researchers quickly familiarize themselves with the current state of continual learning research used in smart city development and direct them to future research trends.

George K. Fordjour, Alfred J. Kalyanapu

Ashland City, Tennessee, located within the Lower Cumberland Sycamore watershed, is highly susceptible to flooding due to increased upstream water levels. This study aimed to develop a robust flood prediction model for the city, utilizing water level data at 30-minute intervals from ten USGS gauge stations within the watershed. A Gated Recurrent Unit (GRU) network, known for its ability to effectively process sequential time-series data, was used. The model was trained, validated, and tested using a year-long dataset (January 2021-January 2022), and its performance was evaluated using statistical metrics including Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE), Percent Bias (PBIAS), Mean Absolute Error (MAE), and Coefficient of Determination (R^2). The results demonstrated a high level of accuracy, with the model explaining 98.2% of the variance in the data. Despite minor discrepancies between predicted and observed values, the GRU model proved to be an effective tool for flood prediction in Ashland City, with potential applications for enhancing disaster preparedness and response efforts in Ashland City.

Mizgin Gökçe Salık, F. Demet Aykal

Genetic algorithm (GA) are based on the continuation of fitter ones’ lives considering the natural evolution. Data are coded as genes in the genetic algorithms. Optimal solutions can be achieved through the methods of crossing and mutation performed on these coded genes. Facade elements of the buildings with an architectural design in this study are independent of sustainability-related concerns, suggesting a great issue for the new buildings to be constructed in the traditional pattern. Accordingly, using the genetic algorithm method, proposals were presented for the new door and window typologies with genetic fitness for the architectural designing process of the buildings to be constructed in Suriçi Region, Diyarbakır, Turkey. Shape grammar, fractal and genetic algorithm, three generative designing systems, were used as the methods. Utilizing the genetic algorithm method, a field study was performed for the proposal of new door and window typologies with the fitness value. The field study was assessed through the plans and facade analyses regarding six Diyarbakır traditional houses with U plan type in Suriçi region of Diyarbakır. An identity card was created for the plan and facade data of the buildings and transferred to the table. Then, the door and window typologies of the exterior facade elements of each examined building were crossed within themselves with the GA method. As a result of the crossover, alternative joinery typologies with a total of 31 windows and 53 different door typologies with compatibility values were produced. Thus, the sustainability of the data of traditional joinery typologies for use in contemporary houses has been ensured. In conclusion, optimal alternative typologies were presented in regard to every chopping typology assessed with the genetic algorithm method. It is thought that this study should be a method that can be used in the production of exterior joinery typologies of contemporary houses to be built in many different cities of our country, especially in the historical texture. Thus, by using the GA method for the production of exterior joinery typologies of contemporary houses to be built in the region, different designers will be able to obtain various designs compatible with the traditional architectural texture while preserving their originality.

Qiwei Zhao, Xin Teng, Panpan Zhang et al.

In the context of carbon peaking and carbon neutrality (“double carbon”), it is urgent to clarify the effect of marine spatial planning (MSP) on carbon sink increases and emission reductions, since such planning acts as a spatial governance tool for the earth’s largest carbon pool. In this paper, a linkage model between marine spatial functional zones and carbon distribution is established. To explore the relationship between marine spatial functional zones and carbon, the study analyzed the carbon increase or reduction role of sea-use activities in each zone and considered the carbon sequestration function of the marine ecosystem itself. A marine spatial pattern of “Two Spaces and Four Carbon Areas” is proposed to present the linkage. A carbon distribution pattern in marine space is delimited using the linkage model and the current MSP in the case study of the city of Tangshan, Hebei, China. Some measures have been taken or planned to be taken in Tangshan to improve the carbon sink function of the ecosystem and the marine space. The supporting role of MSP in achieving the “double carbon” goal is studied, and the paths and suggestions for integrating the “double carbon” goal into MSP are explored.

Carsten Wiecher, Philipp Tendyra, Carsten Wolff

Various stakeholders with different backgrounds are involved in Smart City projects. These stakeholders define the project goals, e.g., based on participative approaches, market research or innovation management processes. To realize these goals often complex technical solutions must be designed and implemented. In practice, however, it is difficult to synchronize the technical design and implementation phase with the definition of moving Smart City goals. We hypothesize that this is due to a lack of a common language for the different stakeholder groups and the technical disciplines. We address this problem with scenario-based requirements engineering techniques. In particular, we use scenarios at different levels of abstraction and formalization that are connected end-to-end by appropriate methods and tools. This enables fast feedback loops to iteratively align technical requirements, stakeholder expectations, and Smart City goals. We demonstrate the applicability of our approach in a case study with different industry partners.

Karina Meneses-Cime, Bilin Aksun-Guvenc, Levent Guvenc

This paper proposes the use of an on-demand, ride hailed and ride-Shared Autonomous Vehicle (SAV) service as a feasible solution to serve the mobility needs of a small city where fixed route, circulator type public transportation may be too expensive to operate. The presented work builds upon our earlier work that modeled the city of Marysville, Ohio as an example of such a city, with realistic traffic behavior, and trip requests. A simple SAV dispatcher is implemented to model the behavior of the proposed on-demand mobility service. The goal of the service is to optimally distribute SAVs along the network to allocate passengers and shared rides. The pickup and drop-off locations are strategically placed along the network to provide mobility from affordable housing, which are also transit deserts, to locations corresponding to jobs and other opportunities. The study is carried out by varying the behaviors of the SAV driving system from cautious to aggressive along with the size of the SAV fleet and analyzing their corresponding performance. It is found that the size of the network and behavior of AV driving system behavior results in an optimal number of SAVs after which increasing the number of SAVs does not improve overall mobility. For the Marysville network, which is a 9 mile by 8 mile network, this happens at the mark of a fleet of 8 deployed SAVs. The results show that the introduction of the proposed SAV service with a simple optimal shared scheme can provide access to services and jobs to hundreds of people in a small sized city.

Alessandro Venerandi, Luca Maria Aiello, Sergio Porta

The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century's England with the emergence of public health and urban planning disciplines. While popularly linked, evidence suggests that such relationship cannot be generally assumed. Furthermore, urban density has been investigated in a spatially coarse manner (predominantly at city level) and never contextualised with other descriptors of urban form. In this work, we explore COVID-19 and urban form in Greater London, relating a comprehensive set of morphometric descriptors (including built-up density) to COVID-19 deaths and cases, while controlling for socioeconomic, ethnicity, age, and co-morbidity. We describe urban form at individual building level and then aggregate information for official neighbourhoods, allowing for a detailed intra-urban representation. Results show that: i) control variables significantly explain more variance of both COVID-19 cases and deaths than the morphometric descriptors; ii) of what the latter can explain, built-up density is indeed the most associated, though inversely. The typical London neighbourhood with high levels of COVID-19 infections and deaths resembles a suburb, featuring a low-density urban fabric dotted by larger free-standing buildings and framed by a poorly inter-connected street network.

David Mitchell

M. Riechers, Jan Barkmann, T. Tscharntke

Abstract Global environmental and social changes will have great impact on the development of cities in the coming decades. Impacts of climate change, demographic shifts and conservation of biodiversity should be incorporated into urban green space planning to balance for the increasing development pressure of cities. Urban green spaces provide multiple ecosystem service benefits to diverse social groups. In this paper, we analyzed inhabitant perceptions of cultural ecosystem services provided by urban green spaces in the city of Berlin based on a face-to-face questionnaire (n = 558). As analysis tool, we used proportionate cluster sampling and focused on non-monetary statements on the perceived importance of a broad spectrum of cultural ecosystem services. Results show that cultural ecosystem services can be perceived through bundles and that those bundles may have negative influence on each other. The perceived importance of cultural ecosystem services was influenced by spatial and social factors: Older inhabitants living in periurban areas preferred cultural ecosystem services related to nature experiences. Younger inner city dwellers tended to prefer cultural ecosystem services facilitating social interactions. Those diverging perceptions should to be taken into account through urban development strategies to create a socially just and sustainable city planning in the face of global environmental changes. The ecosystem service framework can be one tool to facilitate a more participatory planning process to find solutions for urban sustainability challenges.

S. Praharaj, J. Han, S. Hawken

Max Nathan, Henry Overman

José Mario Mayorga Henao, Laura Milena Hernández, María Camila Lozano

El artículo tiene como objetivos identificar los patrones de distribución de la pobreza multidimensional en las principales aglomeraciones urbanas del Sistema de Ciudades colombiano y estimar la magnitud de la segregación residencial entre la población pobre y no pobre asentada en estos territorios. A partir de una reflexión conceptual sobre la pobreza y la segregación, se plantea un estudio comparativo para establecer cómo este fenómeno se presenta en el Sistema de Ciudades, mediante la implementación de múltiples métodos de análisis espacial y estadístico que permiten construir índices a diferentes escalas. Lo anterior, permite concluir que el fenómeno de la segregación residencial presenta particularidades en sus patrones de distribución geográfica al interior de cada aglomeración urbana.