Rational Urban Planning Research Articles

Impact of the Built Environment on Ageing in Place: A Systematic Overview of Reviews

Background: As the global demographic shifts towards an ageing population, the significance of the built environment in facilitating ageing in place gains prominence. This study addresses the critical question of how a built environment can support older adults’ independence and enhance their quality of life. Method: Utilising a systematic review of review papers, this research scrutinises existing literature to uncover the influence of urban planning, physical accessibility, and residential design on the older people’s physical and mental well-being. More specially, the study methodically examines existing review articles that span various aspects of the built environment related to ageing in place. Results: The analysis reveals that specific elements of the built environment, notably rational urban planning and accessible urban spaces, as well as adaptable housing designs, significantly impact ageing individuals’ health, social engagement, and overall satisfaction with life. It also identifies contradictions in the effects of environmental features on cognitive health and well-being, underscoring areas that warrant further exploration. Conclusions: The study concludes that thoughtful urban and housing designs are pivotal in creating age-friendly environments that support ageing in place. It emphasises the need for future research and policy development aimed at enhancing the living conditions of older adults within their communities.

Quantitative measurement of urban spatial vitality by integrating physical built environment and subjective perception dimensions

Urban space vitality is a critical indicator for supporting rational urban spatial planning and updating and formulating sustainable development strategies. However, in many areas (e.g., aging urban areas), there is often a mismatch between the conditions of the physical built environment and its spatial attractiveness. Traditional methods based on physical space design theory often fail to accurately measure the spatial vitality of these areas. Street view images directly reflect the actual construction situation and effectively compensate for the lack of visual, subjective, perception dimension information. This study proposes a novel method that integrates objective and subjective dimensions to measure urban vitality, which is captured by incorporating spatial data of points of interest, building outlines, road networks, and street view images. Then, taking mobile phone signaling data as a source of ground truth validation, we choose Nanjing as a case study to demonstrate that our multidimensional fusion method exhibits higher explanatory power and better alignment with actual conditions by comparing it against single-dimensional methods. The results underscore the importance of integrating subjective and perceptual dimensions in measurements of urban vitality. We believe that the localized samples of the subjective perception survey will further enhance the accuracy and generalizability of this method in the future.

The Content of Urban Planning, Design and its Relationship with Urban and Rural Planning

With the acceleration of urbanization, the impact of urban planning anddesign on urban development is becoming more and more important. A reasonable urbanplanning design not only helps to improve the quality of living environment. butalso can promote the sustainable development of urban economy. In the process ofurban planning and design in reality, there are some problems and challenges which are influenced by various factors. Therefore, the purpose of this paper is to discuss the content, key points and the relationship between urban planning and urban-rural planning, in order to achieve a deeper level of thinking and learning about rational urban planning and design.

Multi-sensor Data Analysis for Aerial Image Semantic Segmentation and Vectorization

Abstract. One of the urgent and constantly in demand problems is updating maps. Maps, representing geo-information in vector form, have undoubted advantages in compactness and ”readability” compared to aerial photographs. The issue of maps actuality is critically important for rational urban planning, precision farming, the relevance of the cadastre and other geospatial applications. Various sources of data are used for maps updating, with aerial imagery being the main and rich source of information. Automatic processing of aerial photographs makes it possible to efficiently extract vector information, providing operational monitoring and accounting for changes that have appeared. The presented study addresses the problem of multi sensor information fusion in order to obtain accurate vector information. We use aerial images as a main data source and additionally the data of laser scanning and ground survey to increase performance of automatic image semantic segmentation and vectorization. The proposed framework is demonstrated on the task of forest monitoring.

Impact of Land Use Change on the Water Environment of a Key Marsh Area in Vientiane Capital, Laos

The water environment is critical to maintaining ecosystem balance and human well-being globally. It is essential to comprehend the effects of land use change on water quantity and quality for sustainable development of the urban environment. Expansion of urban areas leads to intensified human activity and increased pollution loads in natural waterbodies. This study aimed to monitor changes in land use over a span of two decades to evaluate the condition of the water environment in That Luang Marsh (TLM). The land use and land cover (LULC) classes, including agricultural land, bare land, built-up land, vegetation, waterbody, and wetland, were categorized via Landsat images utilizing the maximum likelihood algorithm. A digital elevation model was used to estimate the water surface area and volume, and the nutrient delivery ratio model was employed to analyze nutrient distribution across the LULC classes. The results showed that from 2001 to 2020, the bare land, built-up, waterbody, and wetland areas increased by 29.92, 18.64, 0.87, and 0.16 times, respectively, while the agricultural and vegetation land decreased by 0.80 and 0.76 times, respectively. A binary logistic regression model for influential factors implies that road network expansion within the special economic zone in TLM could result in an increase in residential areas, thereby impacting the LULC classes. The increase in water volume showed a robust correlation with the expansion of built-up land, bare land, and waterbody. TLM had an average nitrate-nitrogen export of 317 tons/year with a 95% confidence interval of (56, 770) tons/year in 2020. The distribution over LULC classes affected the export, which varied dynamically. Vegetation land had the highest nitrate-nitrogen load of 0.57 tons/ha/year, probably due to poorly managed use of fertilizers. The developed land surface for an artificial lake could lead to an increase in the water volume, which could be involved in the dilution of nutrient concentration. Therefore, it is crucial to prioritize policies that aim to establish sustainable urban water environments through rational urban planning and by making LULC management a primary consideration, especially for developing countries undergoing similar processes of urbanization along the Mekong River in Southeast Asia.

Urban land suitability analysis using geospatial techniques and combined weighting approach in Gabes zone, Southeastern Tunisia

Urban Land Suitability analysis is necessary in any development project in order to ensure rational urban planning and sustainable development. In this study, a novel approach based on GIS and Combined Weighting method were used to construct a reasonable assessment model and calculate the Urban Land Suitability Index (ULSI) of Gabes area (Southeastern Tunisia). Seven conditional factors were selected: flooding susceptibility, Lithology, Topography, Seismotectonic, Water table depth, Swelling soils, Soils Aggressivity and the thematic layers were prepared in ArcMap_GIS. The resultant model following combination of the geo-spatial (GIS) and geostatistical (CRITIC-ANP) modeling show that this region is subdivided into four analyzed zones in terms of geo-hazard susceptibility and foundation excavation: flooding risk area; settlement risk zone; collapse risk area and subsidence risk zone. The ULSI is equal to 3.5. The accuracy degree of the achieved model was validated by ROC-AUC curve, it’s is around 78.4%. The ULS model developed enable assured a the assessed thorough and can well reflect an urban land suitability. The results achieved in this study assured planners, engineers, decision-makers and authorities assured a good risk prediction and management plan, could, thus, be facilitate decision-making and can serve as a guideline for all future urban planning projects in this region.

Carcinogenic risk associated with atmospheric air pollution in industrial cities of the Central Chernozem region

Introduction. Industrial cities are characterized by a significant amount of emissions of carcinogenic substances into the atmospheric air. In this regard, for the development of preventive measures, there is needed research to quantify the carcinogenic risk to health.
 The aim of the work was to quantify the carcinogenic risk associated with aerotechnogenic pollution of the cities of the Central Chernozem region including Voronezh, Lipetsk, and Belgorod.
 Materials and methods. Data on the results of monitoring laboratory studies in 2017–2022 were used as initial data. The carcinogenic risk was assessed according to G. 2.1.10.1920–04 “Guidelines for assessing the risk to public health when exposed to chemicals that pollute the environment”.
 Results. Taking into account the available objective data of laboratory control of carcinogens in the atmospheric air of the cities of the Central Chernozem region of Russia, pollutants have been identified whose exposure under standard exposure scenarios causes the level of individual carcinogenic risk to public health above the maximum permissible (1 • 10–4): in Voronezh – 1,3–butadiene (the source of emissions is the production of synthetic rubber) and chromium6+ compounds (the main source of emissions is an aviation plant); in Lipetsk – formaldehyde, at some control points – benzene (the main sources are emissions from metallurgical production and motor transport). Attention should be paid to the need to improve monitoring of the content of carcinogens in the atmospheric air of Belgorod, because in the presence of many sources of pollution, the concentrations of only two carcinogens are controlled.
 Limitations. The limitations of the study are due to the fact that the calculation of individual carcinogenic risks is always inherent in the uncertainties associated with the assessment of exposure and the use of standard formulas for calculating doses of intake into the body.
 Conclusion. To reduce the carcinogenic risk associated with air pollution, a set of measures should be implemented to reduce the intake of carcinogenic pollutants into the atmospheric air, and to implement rational urban planning decisions.

Evaluating the effect of building patterns on urban flooding based on a boosted regression tree: A case study of Beijing, China

AbstractRapid urbanization and global climate change are likely to exacerbate urban flooding intensity, frequency and uncertainty. Thus, it is fundamental and crucial to investigate the dominant influencing factors for the mitigation of urban flooding. However, knowledge about the influence of building patterns on urban flooding remains limited. Taking Beijing, a typical megacity, as a case study area, we quantified the importance of building patterns and their interaction effect at the subwatershed scale using the boosted regression tree and geographical detector model. The results indicated that (1) the landscape shape index, slope, green space ratio and waterbody ratio were the most important influencing factors determining urban flooding, with a total relative contribution of 67.23%; (2) building metrics had a certain impact on urban flooding, and the sum of the relative contribution reached 21.03%; (3) the landscape shape index, slope, and green space ratio exhibited a combination of negative and positive correlations with urban flooding density; and (4) an enhancement effect existed between building metrics, especially the building congestion degree and building density. These findings provide quantitative insights on rational urban morphology planning which could be applied to improve stormwater management and promote urban sustainability in megacities.

The Green Dimension of a Compact City: Temperature Changes in the Urban Area of Banja Luka

Responsible and rational urban planning is reflected in an integral and multidimensional approach to city development. Contemporary theories of sustainable and resilient urban planning support a clear vision and strategy for city development, emphasizing its identity, specifics, and values. Through its vision and action plans, the city of Banja Luka protects its default identity as a green city while recognizing the current development trend toward a compact city. The paper deals with two theories: green and compact cities, both motivated by ecological and energy planning. The paper aims to show the importance of the green dimension of a compact city and the adoption of the principles of compactness in the green city in order to examine its contribution through synergistic action. Through the comparative analysis of the green structure change toward a compact urban area and temperature rise in the last fifty years and on different scales, it is possible to question the set green goals and effects of environmental urban (non) planning.

Research on Spatial and Temporal Patterns of Heat Island Variability and Influencing Factors in Urban Center Areas: A Case Study of Beijing’s Central Area

Studying the urban heat island effect and actively exploring effective measures for its mitigation and alleviation can provide important parameters for urban ecological environment monitoring and propose rational strategies to address environmental degradation. This article, with the background of urban renewal projects in Beijing, focuses on the central area of Beijing as the research object. Landsat ETM+/OLI_ TIRS data from 2000 to 2020 are used as the main remote sensing imagery source, combined with functional information data and spatial attribute data of open spaces in the central area. Based on the mono-window (MW) algorithm, this study first quantitatively retrieves and categorizes the summer land surface temperature in Beijing’s central area and analyzes its spatiotemporal characteristics using the direction distribution method, revealing regular patterns in the temporal and spatial dimensions. The results show a gradual decrease in the size of the persistent high-temperature concentration area over time. Subsequently, the seasonal autoregressive integrated moving average (SARIMA) model is employed to predict the changing trends of the urban heat island and the occurrence time of the strongest and weakest heat islands. Higher land surface temperature (LST) years are projected for 2025 and 2035, with the lowest year being 2030. Lastly, the correlation coefficient and Moran’s index are used to analyze the correlation between the urban heat island and its corresponding influencing factors in different years. The results indicate that population density, nighttime light, and gross domestic product (GDP) have significant positive effects on the heat island intensity from a temporal perspective. Normalized difference vegetation index (NDVI) shows a significant negative relationship with the heat island intensity when analyzed over time. The research findings provide important reference for rational urban planning, layout, and construction, and hold significance for advancing urban renewal efforts.

Key indicators of high-quality urbanization affecting eco-environmental quality in emerging urban agglomerations: Accounting for the importance variation and spatiotemporal heterogeneity

As the basis of social sustainable development, eco-environmental quality (EEQ) plays an essential role in the process of high-quality urbanization (HQU). Therefore, evaluating the response mechanism of EEQ in the context of HQU will provide effective guidance for promoting sustainable development. Based on the requirements of high-quality development and the component elements of urbanization and eco-environment, the appropriate variables were selected to construct an evaluation index system between HQU and EEQ of the Shandong Peninsula urban agglomeration (SPUA) in north China. This study employed the improved coupling coordination degree (CCD) model and Moran's I to explore the dynamic mechanism and spatiotemporal distribution of coupling coordination between HQU and EEQ of the SPUA from 2001 to 2020. Meanwhile, the random forest model and the geographically and temporally weighted regression model were used to further investigate the variation in importance and spatiotemporal heterogeneity of the HQU indicators affecting EEQ. This study found that the CCD between HQU and EEQ followed a continuous upward trend in the SPUA from 2001 to 2020, which was much higher in eastern developed cities with a spatial dependency of high-high clustering. Due to the irreplaceability of energy in residents' lives, per capita energy consumption was found to be the most important impact indicator on EEQ. Population density achieved the fastest growth in importance over the study period, and the spatial indicators exhibited greater importance in the west of the SPUA. Furthermore, significant spatiotemporal differences were identified in the effects of HQU indicators on EEQ. HQU was more conducive to an improvement of EEQ in the eastern coastal SPUA. These findings could provide guidance for policy makers to adopt scientific measures in rational urban planning and ecological management of urban agglomerations in developing countries.

Vectorized dataset of roadside noise barriers in China using street view imagery

Abstract. Roadside noise barriers (RNBs) are important urban infrastructures to ensure that cities remain liveable. However, the absence of accurate and large-scale geospatial data on RNBs has impeded the increasing progress of rational urban planning, sustainable cities, and healthy environments. To address this problem, this study creates a vectorized RNB dataset in China using street view imagery and a geospatial artificial intelligence framework. First, intensive sampling is performed on the road network of each city based on OpenStreetMap, which is used as the georeference for downloading 6×106 Baidu Street View (BSV) images. Furthermore, considering the prior geographic knowledge contained in street view images, convolutional neural networks incorporating image context information (IC-CNNs) based on an ensemble learning strategy are developed to detect RNBs from the BSV images. The RNB dataset presented by polylines is generated based on the identified RNB locations, with a total length of 2667.02 km in 222 cities. Last, the quality of the RNB dataset is evaluated from two perspectives, i.e., the detection accuracy and the completeness and positional accuracy. Specifically, based on a set of randomly selected samples containing 10 000 BSV images, four quantitative metrics are calculated, with an overall accuracy of 98.61 %, recall of 87.14 %, precision of 76.44 %, and F1 score of 81.44 %. A total length of 254.45 km of roads in different cities are manually surveyed using BSV images to evaluate the mileage deviation and overlap level between the generated and surveyed RNBs. The root mean squared error for the mileage deviation is 0.08 km, and the intersection over union for overlay level is 88.08 % ± 2.95 %. The evaluation results suggest that the generated RNB dataset is of high quality and can be applied as an accurate and reliable dataset for a variety of large-scale urban studies, such as estimating the regional solar photovoltaic potential, developing 3D urban models, and designing rational urban layouts. Besides that, the benchmark dataset of the labeled BSV images can also support more work on RNB detection, such as developing more advanced deep learning algorithms, fine-tuning the existing computer vision models, and analyzing geospatial scenes in BSV. The generated vectorized RNB dataset and the benchmark dataset of labeled BSV imagery are publicly available at https://doi.org/10.11888/Others.tpdc.271914 (Chen, 2021).

Seasonal Differences in Land Surface Temperature under Different Land Use/Land Cover Types from the Perspective of Different Climate Zones

The process of urbanization is accelerating, and land surface temperature (LST) is increasing, seriously threatening human health. Therefore, it is crucial to explore the differences in LST of different land use/land cover (LULC) types. Using MOD11A2 and MCD12Q1 data, this study explored the seasonal differences in LST of each LULC type from the perspective of different climate zones. The results showed that the maximum and minimum LSTs during the day were higher than those at night. During the day, the LSTs of urban and built-up and barren lands were higher than those of forests, grasslands, and water bodies; at night, the LSTs of urban and built-up lands decreased but remained high, while barren lands showed a significant decrease to LSTs even lower than those of water bodies. In addition, the difference in daytime LST of the LU16 type (barren lands) in different climatic zones was the most obvious and was much higher than that of other LULC types in the middle temperate and south temperate zones, but much lower than those in the middle subtropical and north subtropical zones. This comparison of the LST differences of each LULC type under different climate backgrounds provides an important reference for rational urban planning.

Research on Architectural Planning and Landscape Design of Smart City Based on Computational Intelligence.

City brain is a complex system, including online center, server network, and system with given algorithm. The core of the city brain is the intelligent system. After putting the urban brain into the intelligent nerve center, on the basis of not changing its original data structure, combining its own characteristics for design and then integrating into application, it can intelligently change the urban management mode. Urban planning leads the development of smart cities on a certain meaning, and smart city planning must have scientific and rational urban planning. The intelligent model is used to make urban planning form a more modern, convenient, and reasonable urban architectural planning. Some influential books on classical architectural theory are the theoretical basis of intelligent urban planning and even the trend and implementation blueprint of how smart cities will develop in the future. In this paper, four algorithms, ant colony algorithm, particle swarm optimization algorithm, genetic algorithm, and improved ant colony algorithm, are proposed to optimize the characteristics of urban architectural planning and landscape design; especially the security research of architecture and landscape characteristics is very important. The improved ant colony algorithm has the shortcoming of insufficient optimization ability in the face of complex path selection. By improving the influencing factors, a new ant colony algorithm is created. The improved ant colony algorithm achieves the best in security features, so it is advocated to use this algorithm for planning and design. The urban form in smart city aims to create a beautiful and comfortable urban environment, improve the competitiveness of cities in the rapid urbanization process, improve the living standards of the public, and shape the image of this beautiful city.

Food Retail Network Spatial Matching and Urban Planning Policy Implications: The Case of Beijing, China

Food is the core of urban daily life and socio-economic activities but is rarely the focus of urban planning. The spatial layout of food retail outlets is important for optimizing the urban food system, improving land resource allocation, and encouraging healthy food consumption. Based on food retail POI data, this study employed kernel density estimation, road network centrality, spatial autocorrelation analysis, and locational entropy to analyze the spatial characteristics of supermarkets, produce markets, and small stores in an urban center in Beijing, and explored street coupling and supply-demand matching. The results indicated that within the study area: (1) supermarkets had an obvious “core-periphery” distribution, produce markets had a polycentric distribution, and small stores had a relatively uniform distribution; (2) road network centrality indices revealed a differentiated multi-core-edge distribution; (3) streets with high locational entropy values for supermarkets and produce markets were mostly concentrated in the central area, whereas the matching distribution of small stores was relatively balanced. From the perspective of urban planning, policy implications are proposed based on spatial and social equity, urban-rural differences, population structure and distribution status, and a resilient supply chain. The study findings have practical significance for guiding the development of urban food systems in a healthy, just, and sustainable direction, as well as rational urban land planning.

РОЛЬ ТЕОРІЙ ПРОСТОРУ У ФОРМУВАННІ СУЧАСНОЇ ІНФРАСТРУКТУРИ

In the current conditions of economic globalization, there are interesting transformations of the role and place of individual industries in the economic complex. Infrastructure plays a very important role in these processes. The article is devoted to the study of the characteristics of modern regional space. The article provides a historical digression of the influence of space theories on the formation of the modern concept of "infrastructure". The definition, which came into scientific circulation in the XIX century, today plays a crucial role - the unification of all production, economic, social, economic processes in the world. Beginning its path of formation in the seventeenth century, thanks to the emergence of new opportunities in the Enlightenment, humanity was able to start from the problems of solving the supply of agricultural products to cities to achieve global economic development. Deepening knowledge of "distance" and "time", the need for theoretical approaches in the implementation of optimal urban planning, rapid industrialization led to the emergence of objects that were grouped in the future by areas of application, outlining the types of infrastructure - industrial, social, transport, information, etc. Space theories by such scholars as A. Smith, R. Cantillon and P. Stewart, von Tunen and W. Launhardt, and others. were the primary sources of deepening knowledge in solving problems of rational urban planning, which as a result of globalization of socio - economic processes has had far - reaching consequences, where modern infrastructure is the key to viability. A comparative analysis of industrial and post-industrial paradigms of regional development is carried out, which allows to substantiate the laws of evolution of economic space. Relationships between the development of "space theory" and the modern formation of the concept of infrastructure have been established. The evolution of the theory of features of spatial systems functioning is analyzed. It is concluded that the concept of "infrastructure" serves to ensure the effective functioning of society.

A hierarchical approach for fine-grained urban villages recognition fusing remote and social sensing data

Timely and accurate maps of fine-grained urban villages (UVs) are essential for rational urban planning, which highlights the importance for automatic recognition methods as alternative to labor-intensive land survey, especially for large cities with high-density urban areas where UV maps cannot be updated frequently. However, it is challenging to simultaneously achieve accurate and fine-grained recognition of UVs from remote sensing images in high-density cities, due to the problem of low discrimination of remote sensing features showed in UVs. To address this issue, in this paper, we have proposed a hierarchical recognition framework which can integrate remote and social sensing data to recognize fine-grained UVs. The hierarchical framework follows the human cognition processes and has explicit geographical meaning for each step, which ensures its interpretability. Besides, remote and social sensing data can be fused easily in this framework so that the abstract concept of UV can be sufficiently characterized in both coarse and fine scales. To validate the effectiveness of the proposed approach, extensive experiments in Shenzhen, a typical high-density megacity in China with complicated UVs, have been conducted and a fine-grained map with spatial resolution of 2.5 m was obtained. The results show that the proposed approach achieved an impressive performance, with overall accuracy and Kappa of 96.23% and 0.920 respectively. Furthermore, comparative assessments and ablation studies were performed to demonstrate the effectiveness of the hierarchical recognition framework as well as the fusion of remote and social sensing data.

Split 2 Housing Developments Planned from 1957 to 1968

Split 2 is a significant part of urban and architectural heritage in Split and Croatia. This arises from the scope and reach of the rational urban planning and use of space, inventive architectural design focused on construction technologies, operations and materials which were mainly organized in concentric construction sites of housing developments and areas which predominantly featured standardized residential buildings and residential high-rises in the period from 1957 to 1968.

Systèmes d’information Géographique (SIG), Développement et compétitivité territoriale : Quelle Articulation ? - Cas de la Ville De Marrakech -

"Geographical Information Systems (GIS), Development and Territorial Competitiveness: What Connection? The Case of the City of Marrakech. Marrakech is a city in search of an urban balance in social, economic and environmental terms. This balance traces the reflection of a political and economic ideal of a new and smart city, which essentially instrumentalizes a well-studied basic urban policy, inspiring confidence. The birth of a new urban concept for Marrakech is initiated by an urban will, as part of a vision of sustainable and equitable territorial development. The GIS, as a means of territorial management and decision-making in terms of spatial planning and control, has emerged in urban management strategies, following the evolution of the territory and the changes that occurred, in addition to the current circumstances regarding climate change, urban transformations and globalization. GIS is therefore a consequence of this evolution, which is also experienced by the city of Marrakech. The connection between GIS and territory leads to relevant results for spatial organization, given the ingrained adoption of information techniques at the level of municipalities and between municipalities. In this context, this paper approaches the insertion of new technologies to assist the decision-making process by territorial actors and the digitization of spatial data for a rational urban planning. Keywords: GIS, territorial management, smart city, digitization of data. "

Performing São Paulo: Flávio de Carvalho and the Experimental City, 1928–1931

In the 1920s and early 1930s, Brazil’s urbanists and intellectuals recognized fundamental tensions between world-making by modernist artists and architects and interventions in urban space by undisciplined urban crowds.1 In the burgeoning megalopolis of Sao Paulo, simultaneously center and periphery for a Brazil increasingly embedded within international economic and cultural circuits, civil engineer Flavio de Carvalho created fantastical architectural designs and performative disruptions of city life. Yet, rather than understanding his works as exemplifying avant-garde radicality, this essay argues that Carvalho’s designs and interventions expressed anxiety about the declining power of older Brazilian elites and the rise of quasi-populistdemagoguery with Brazil’s Revolution of 1930. In rapidly changing Sao Paulo, Carvalho remained poised between faith in the modernization of Brazil’s cities governed by rational urban planning and a desire to experience urbanity as an exhilarating immersion in disorderly crowds.