Urban Planning Support Research Articles

Modeling urban land-use changes using a landscape-driven patch-based cellular automaton (LP-CA)

Cellular automaton (CA) is a widely-used tool for modeling land-use changes that can enhance our understanding of past and future urban development. Previous studies have demonstrated that patch-based CA models are superior to cell-based CA because the spatial homogeneity of urban growth at local scales can be considered. However, there still exists a major limitation that traditional patch-based CA did not incorporate any information about landscape pattern into land-use change modeling. To alleviate this issue, we present a novel landscape-driven patch-based CA (LP-CA) model that can simultaneously consider landscape similarity and cell-by-cell agreement. We have examined this new model by simulating and predicting the urban expansion in a fast-growing city. Results indicate that our method performs better than stand-alone traditional patch-based CA and landscape-driven cell-based CA in terms of the combined error. The capability to characterize and replicate landscape pattern is greatly important for urban planners to explore the potential influences of urban expansion under different land-use planning scenarios. Therefore, this proposed model has the potential to provide valuable support for urban land-use planning and policy-making processes.

FEATURES OF REGIONAL LAND USE IN MODERN CONDITIONS

It has been proven that modern conditions require a rethinking of approaches to ensuring the efficiency of land use at the regional level. Of particular importance is the use of modern tools for managing land relations, in particular, the formation of opportunities for the development and application of a multi-purpose cadastre, geoinformation systems, and the formation of several bases for land use monitoring. Monitoring procedures make it possible to form a basis for decision-making in the field of land relations based on modern mechanisms. Moreover, the application of national and international experience is of particular importance.
 The method of research is to identify the peculiarities of the implementation of land relations in modern conditions. To achieve the set goal, the following tasks are performed: the directions of the formation of cadastral systems are determined; proposed characteristics of monitoring.
 As a result of the study, it was established that the modern development of cadastral systems is aimed at the development and implementation of a multi-purpose real estate cadastre. Multi-purpose real estate cadastre at the regional level", which takes into account the combination of spatial, urban planning, investment and environmental support, which allowed to build a multi-level information system for the formation of several bases of real estate management at the regional level. 
 In the context of identifying the peculiarities of land relations, which allows for the monitoring of land use taking into account spatial, urban planning, socio-economic and environmental support through the use of geo-informational tools, which allowed to develop a theoretical and methodological basis for the formation and application of monitoring procedures at the regional level to increase the effectiveness of implementation . land relations.
 At the same time, spatial, urban planning, socio-economic and environmental support is singled out, which can form a multi-objective basis for the development and implementation of an integral assessment method for the formation and implementation of monitoring at the regional level.

MONITORING: LAND USE OF UNITED TERRITORIAL COMMUNITIES: DEFINITION AND FEATURES OF FORMATION

The necessity and relevance of the formation of the monitoring of the victory of the lands of the united territorial communities was brought. The method of follow-up is the formation of the monitoring of the winning of the lands of the united territorial communities. For the achievement of the set milestone, the next task is:
 
 assigned to the monitoring of winning the lands of the united territorial communities;
 сharacteristics of officials, which should be added to the formation of the monitoring of the victorious lands of the united territorial communities;
 мathematical modeling of the officials of the lands of the united territorial communities.
 
 The definition of the concept of land use monitoring of united territorial communities is proposed, a distinctive feature of which is the consideration of spatial, urban planning, socio-economic and environmental support through the use of geo-informational tools, which made it possible to develop a theoretical and methodological basis for the formation and application of monitoring procedures at the regional level to increase effectiveness of implementation of land relations in united territorial communities.
 The topological principles of determining the factors regarding the use of land of united territorial communities on the basis of spatial, urban planning, socio-economic and ecological provision are characterized, which allow to form a quantitative basis for the development and implementation of an integral assessment method for the formation and implementation of monitoring at the regional level.
 The method of integral evaluation of land use of united territorial communities is proposed as the main element of the technology of formation and implementation of monitoring, based on analytical and expert methods, which made it possible to form a systematic monitoring environment at the regional level.
 The processes of mathematical modeling of land use factors of united territorial communities are characterized by determining the dependence between spatial, urban planning, socio-economic and ecological factors and an integral indicator based on the application of correlation-regression analysis, model adequacy criteria, which provided opportunities to form the directions of their changes in the forecast periods

Vehicle detection using panchromatic high-resolution satellite images as a support for urban planning. Case study of Prague’s centre

Abstract The optical sensors on satellites nowadays provide images covering large areas with a resolution better than 1 meter and with a frequency of more than once a week. This opens up new opportunities to utilize satellite-based information such as periodic monitoring of transport flows and parked vehicles for better transport, urban planning and decision making. Current vehicle detection methods face issues in selection of training data, utilization of augmented data, multivariate classification or complexity of the hardware. The pilot area is located in Prague in the surroundings of the Old Town Square. The WorldView3 panchromatic image with the best available spatial resolution was processed in ENVI, CATALYST Pro and ArcGIS Pro using SVM, KNN, PCA, RT and Faster R-CNN methods. Vehicle detection was relatively successful, above all in open public places with neither shade nor vegetation. The best overall performance was provided by SVM in ENVI, for which the achieved F1 score was 74%. The PCA method provided the worst results with an F1 score of 33%. The other methods achieved F1 scores ranging from 61 to 68%. Although vehicle detection using artificial intelligence on panchromatic images is more challenging than on multispectral images, it shows promising results. The following findings contribute to better design of object-based detection of vehicles in an urban environment and applications of data augmentation.

ГЕОДЕЗІЯ, КАРТОГРАФІЯ І АЕРОФОТОЗНІМАННЯ

It has been proven that the transformational processes taking place in Ukraine are related to the deepening of crisis phenomena in the economic sphere, the slowdown of the main indicators of regional development, the impact of the consequences of the COVID-19 pandemic, and military operations. In such conditions, it is necessary to rethink approaches to ensure the efficiency of the functioning of regions by improving the system of land resources management, as the main factors of their development. At the same time, the modern European experience of land administration and information provision of the formation and use of real estate based on the application of the multi-purpose cadastre is considered. The aim of this work – to develop scientifically based recommendations for the formation of a multi-purpose cadastre at the regional level. To achieve the goal, the following tasks were completed: determination of the multi-purpose cadastre at the regional level; identification of factors affecting the formation of a multi-purpose cadastre; presentation of the results of mathematical modelling of the factors of formation of the multi-purpose cadastre; the formation of geo-information support of a multi-purpose cadastre. Method. To obtain research results, special methods are used: structural and content analysis - to form a conceptual apparatus for defining a multi-purpose cadastre at the regional level; analytical and methods of expert analysis - to determine the spatial, urban planning, investment and environmental factors of the information support of the multi-purpose cadastre; analysis of hierarchies - to determine the weighting factors characterizing the mutual influence of indicators of information provision of the multi-purpose cadastre; mathematical modelling - for the development of models that determine the impact of spatial, urban planning, investment and environmental factors on the integral indicator of information provision of the multi-purpose cadastre; correlation-regression analysis - to establish the influence of the integral indicator of information provision of the multi-purpose cadastre at the regional level on the gross regional product; of geo-information analysis - for the development of geo-information support of the multi-purpose cadastre. Scientific novelty and practical significance. An integral indicator for assessing the level of information provision of the multi-purpose cadastre is proposed, which is determined based on spatial, urban planning, investment and environmental factors, which allows forming the information basis for the development of scientifically based recommendations for the creation and implementation of the multi-purpose cadastre at the regional level. The concept of "multi-purpose cadastre at the regional level" was defined, which considers the totality of spatial, urban planning, investment and environmental support, which allowed to build a multi-level information system for the formation of a quantitative basis of real estate management at the regional level. The method of integral assessment of the level of information support of the multi-purpose cadastre at the regional level is characterized, which is based on a multi-level system of factors, methods of assessment of analytical and qualitative indicators, analysis of hierarchies, local, generalizing and integral models, which made it possible to carry out mathematical modelling of these factors, to form geo-information support for adoption reasoned decisions in the field of real estate management. The results of mathematical modelling of the processes of development of information support of a multi-purpose cadastre based on the establishment of relationships between system factors and an integral indicator by applying the method of correlation-regression analysis are presented, which makes it possible to build predictive models and establish trends in the formation and use of real estate at the regional level, taking into account the spatial, urban planning, investment and environmental support. Scientifically based recommendations for the development and implementation of a multi-purpose cadastre were proposed based on the results of their level assessment and modelling, which made it possible to single out directions for increasing the level of information provision and application of the multi-purpose cadastre for increasing the efficiency of real estate use at the regional level [Ноlovachov et al., 2022; Ноlovachov, 2022].

Identifying and Classifying Urban Data Sources for Machine Learning-Based Sustainable Urban Planning and Decision Support Systems Development

With the increase in the amount and variety of data that are constantly produced, collected, and exchanged between systems, the efficiency and accuracy of solutions/services that use data as input may suffer if an inappropriate or inaccurate technique, method, or tool is chosen to deal with them. This paper presents a global overview of urban data sources and structures used to train machine learning (ML) algorithms integrated into urban planning decision support systems (DSS). It contributes to a common understanding of choosing the right urban data for a given urban planning issue, i.e., their type, source and structure, for more efficient use in training ML models. For the purpose of this study, we conduct a systematic literature review (SLR) of all relevant peer-reviewed studies available in the Scopus database. More precisely, 248 papers were found to be relevant with their further analysis using a text-mining approach to determine (a) the main urban data sources used for ML modeling, (b) the most popular approaches used in relevant urban planning and urban problem-solving studies and their relationship to the type of data source used, and (c) the problems commonly encountered in their use. After classifying them, we identified the strengths and weaknesses of data sources depending on several predefined factors. We found that the data mainly come from two main categories of sources, namely (1) sensors and (2) statistical surveys, including social network data. They can be classified as (a) opportunistic or (b) non-opportunistic depending on the process of data acquisition, collection, and storage. Data sources are closely correlated with their structure and potential urban planning issues to be addressed. Almost all urban data have an indexed structure and, in particular, either attribute tables for statistical survey data and data from simple sensors (e.g., climate and pollution sensors) or vectors, mostly obtained from satellite images after large-scale spatio-temporal analysis. The paper also provides a discussion of the potential opportunities, emerging issues, and challenges that urban data sources face and should overcome to better catalyze intelligent/smart planning. This should contribute to the general understanding of the data, their sources and the challenges to be faced and overcome by those seeking data and integrating them into smart applications and urban-planning processes.

Influence of Urban Geometry on Thermal Environment of Urban Street Canyons in Hong Kong

Hong Kong is a typical high-density city in a subtropical climate region, and deep street canyons are among the main features of its urban planning. How the urban geometry influences the urban thermal environment in this city has become a hot topic these days. The height-to-width ratio (H/W) and sky view factor (SVF) are commonly used to indicate the outdoor thermal environment performance, while previous studies in Hong Kong rarely analysed the importance bias of these two influencing factors systematically in this context. To fill this research gap, in this paper, we chose four typical sites in Hong Kong as research objects. Firstly, we conducted a field investigation to calculate the main influencing factors of urban street geometry (H/W and SVF) and then used field measurements to collect climatic data, including air temperature, wind speed, and relative humidity, and finally used regression to analyse the correlation between H/W, SVF, and temperature. The results indicate the following: (1) There is a greater correlation between H/W and air temperature than between SVF and air temperature by regression analysis, and H/W is more effective at improving the thermal environment within urban street canyons. (2) After field measurements, it was found that H/W at the measurement sites was 0.60 to 6.02, with an average of 2.13. (3) In the study area, H/W of 2.31–2.48 and 3.35–3.60 had a positive correlation with air temperature, and H/W had a dominant influence on outdoor air temperature, and H/W of 2.09–2.31 and H/W > 3.60 was inversely related to air temperature. The conclusions can provide support for urban planning in Hong Kong.

Spatial–temporal characteristics of surface thermal environment and its effect on Lake surface water temperature in Dianchi Lake basin

The surface thermal environment plays an important role in urban sustainable development and ecological environment protection. Existing researches mainly focus on the formation process and mechanism of the surface thermal environment and lack the analysis of its effect on the lake ecological environment under the influence of human activities. Therefore, based on the analysis of the variations in land surface temperature (LST) and lake surface water temperature (LSWT) of Dianchi Lake at multiple spatio-temporal scales, this study evaluated the response of LSWT by using the methods of spatial influence, the center of gravity migration trajectory, trend analysis, and correlation analysis. The results show that: (1) Urbanization has a greater warming effect on LSWT than on LST, and the warming effect at night is greater than that at daytime. From 2001 to 2018, the warming trend of LSWT in daytime and night was 0.01°C/a and 0.02°C/a, respectively, while the cooling trend of LST in daytime was −0.03°C/a and the warming trend of LST in night was 0.01°C/a. (2) Areas with high human activity are warming faster, both in the eastern and northern coastal areas of lake and the heavily urbanized sub-basins. (3) The spatial influence of LST and LSWT are highly correlated, and the response of the outer buffer in the range of 2 km is obvious, and the direction of gravity center migration trajectory is consistent. The results are of great significance for the control and improvement of urban heat island and ecological environment protection of Dianchi Lake in Kunming and can provide data support and decision support for urban planning, promoting the construction of the ecological civilization city in Kunming, and reducing the accumulation of urban surface heat.

DEVELOPMENT OF THE METHOD OF INTEGRAL ASSESSMENT OF LAND USE OF UNITED TERRITORIAL COMMUNITIES

It has been proven that modern conditions are characterized by instability, which is due to the impact of the consequences of military operations, the COVID-19 pandemic, the growth of socio-economic disparities, and the disruption of intra-economic ties. The implementation of the local self-government reform is aimed at the development of united territorial communities (UTH), as an important direction of decentralization implemented in Ukraine. The functioning of the OTG is characterized by the formation of new relations between the state and local communities, where the latter have significant powers for the formation and use of land. The purpose of the study is to form a quantitative basis for the development and implementation of monitoring of the use of land of the OTG by applying the integral method. To achieve the set goal, the following tasks were completed: – development of directions for the development of an integral method for determining the level of land use of united territorial communities; – assessment of the level of land use of the OTG based on the integral method. Thus, as a result of the study, it was determined that different aspects are observed in the context of the use of the lands of the OTG in the regions of Ukraine. In particular, in the Zhytomyr, Mykolaiv, Sumy, and Kherson regions, a high level of land use of united territorial communities is observed. The following regions are defined at a sufficient level: Vinnytsia, Volyn, Dnipropetrovsk, Zaporizhzhya, Lviv, Poltava, Rivne, Ternopil, Khmelnytsky, Chernivtsi, Chernihiv. Along with this, in some regions there is an insufficient or weak level of use of the lands of the OTG (Transcarpathian, Cherkasy). In general, we note that in recent years there have been positive changes in the use of land of united territorial communities by region in terms of comprehensive consideration of spatial, urban planning, socio-economic and ecological support. However, it should be noted that at the regional level there is a need to implement measures to increase the level of land use based on the development and implementation of scientifically based recommendations regarding the implementation of monitoring procedures. The method of integral assessment of land use of united territorial communities was developed as the main element of the technology of forming and implementing monitoring, based on analytical and expert methods, which made it possible to form a systematic monitoring environment at the regional level. Keywords: the method of integral assessment, land use, spatial, urban planning, socio-economic, ecological factors, united territorial communities.

Land use contribution to spatiotemporal stream water and ecological quality: Implications for water resources management in peri-urban catchments

• Seasonal variability confounds land-use source contribution in peri -urban streams. • No robust ecological improvement despite implementation of Nature-based solution. • Nematode-based stress index reveals impacts and benefits of wastewater effluents. • Contaminant-bound particles and other chemicals stressors may be overlooked. Climate change and intensifying agricultural production and urbanization are central factors driving the global freshwater biodiversity decline. To design sustainable green transition schemes and support urban planning, a deeper understanding of the numerous interacting physicochemical and biogeochemical processes and their relation to ecological quality becomes essential. This study thus aims to explore links between hydrological regimes and patterns evident for key water quality parameters and benthic invertebrate indicators in a peri -urban catchment that has undergone several stream restoration projects. Results indicate significant seasonal variability in discharge and physico-chemical parameters confounding the identification of sources behind detrimental impacts on ecological quality, which may lead to the implementation of inappropriate mitigation strategies. Notably, sampling at the sub-catchment level underlined the dynamic contributions of both agricultural and urban-like areas for nitrogen and phosphorus, while non-volatile carbon was mainly exported from agricultural lands. Multivariate statistical methods were used to classify benthic macro- and meioinvertebrate (specifically nematode) taxa showing poor-to-moderate and poor-to-good ecological quality, respectively. Poor ecological quality was mostly found in the upstream part of the catchment, driven by a combination of low habitat quality and periodically impaired physico-chemical conditions (e.g. dissolved oxygen, temperature, and suspended solids). In addition, the nematode-based stress index NemaSPEAR[%] (expressing the proportion of species-at-risk within a sample and specifically sensitive to the chemical contamination), indicated a TSS-related transport of contaminants to the sediment. It could also reveal both the negative impacts of different urban features (low ecological quality just downstream of combined sewer overflows), as well as the potential benefits of wastewater effluents (i.e. good ecological quality, via well-treated flow contributions and limited fine sediment accumulation especially in summer) on the stream ecosystem. Our results highlight that the use of this indicator, in combination with high frequency monitoring are promising techniques to better link the dynamic impacts of land use and spatiotemporal changes in ecological quality.

Effect of Landscape Structure on Land Surface Temperature in Different Essential Urban Land Use Categories: A Case Study in Jiaozuo, China

Understanding the relationship between different essential urban land use categories and the urban thermal environment is essential for urban planning, resource allocation and decision support. However, most of the spatiotemporal correlations between land use types and LST are focused on industrial land use and urban green space, and there are fewer discussions on the totality of urban land use types. Here, using multi-source remote sensing images, correlation analysis and the stepwise regression method, we elaborate the relationship between landscape structure and land surface temperature (LST) across the different seasons of 850 planning management units in Jiaozuo, China. Our results show that the degree of explanation of surface temperature by landscape structure increased with a fine division of land use. The imprint of urban–rural gradients on LST was largely masked by the land use categories at the regional scales. Moreover, the tridimensional structure of buildings significantly affected the LST of residential regions, and the large number of low-rise buildings in urban planning practice contributes to high LSTs. This study provides a comprehensive analysis of the effects of each land use type and landscape structure on surface temperature in urban space and also provides strategies and methods for urban planning in rapidly developing regions of the country.

Combining Deep Semantic Edge and Object Segmentation for Large-Scale Roof-Part Polygon Extraction from Ultrahigh-Resolution Aerial Imagery

The roofscape plays a vital role in the support of sustainable urban planning and development. However, availability of detailed and up-to-date information on the level of individual roof-part topology remains a bottleneck for reliable assessment of its present status and future potential. Motivated by the need for automation, the current state-of-the-art focuses on applying deep learning techniques for roof-plane segmentation from light-detection-and-ranging (LiDAR) point clouds, but fails to deliver on criteria such as scalability, spatial predictive continuity, and vectorization for use in geographic information systems (GISs). Therefore, this paper proposes a fully automated end-to-end workflow capable of extracting large-scale continuous polygon maps of roof-part instances from ultra-high-resolution (UHR) aerial imagery. In summary, the workflow consists of three main steps: (1) use a multitask fully convolutional network (FCN) to infer semantic roof-part edges and objects, (2) extract distinct closed shapes given the edges and objects, and (3) vectorize to obtain roof-part polygons. The methodology is trained and tested on a challenging dataset comprising of UHR aerial RGB orthoimagery (0.03 m GSD) and LiDAR-derived digital elevation models (DEMs) (0.25 m GSD) of three Belgian urban areas (including the famous touristic city of Bruges). We argue that UHR optical imagery may provide a competing alternative for this task over classically used LiDAR data, and investigate the added value of combining these two data sources. Further, we conduct an ablation study to optimize various components of the workflow, reaching a final panoptic quality of 54.8% (segmentation quality = 87.7%, recognition quality = 62.6%). In combination with human validation, our methodology can provide automated support for the efficient and detailed mapping of roofscapes.

Информационное обеспечение градостроительной деятельности в России

Issues of digitalization and information support of urban planning activities are now becoming particularly relevant against the background of introducing the new innovation economy in all territorial governmental levels. To date, the processes of state information systems implementing for urban planning activities (ISUPA) in the regions of Russia continue, but the conceptual model of the systems in question, which can serve as a basis for developers, has not been formed. The aim of the research is to create a conceptual model of information support for urban planning in the Russian Federation by identifying directions of its transformation. The goal was achieved in the process of retrospective analysis and determining the directions of domestic ISUPA transformation. The authors carried out a retrospective critical analysis of information provision of urban planning activity in Russia (ISUP), as a result of which patterns and trends of development were identified. The directions of ISUP transformation were determined. We formulated the basic principles of construction and functioning of state information systems to ensure urban development (SISUPA). A conceptual model of modern SISUPA was constructed. A set of functional capabilities of the system is defined. The proposed conceptual model of SISUPA and the principles of its construction and operation can be used in the process of SISUPA further improvement in any region of the Russian Federation. The studies show that although digitalization in Russia in the field of urban planning goes steadily, there are problems with the implementation of measures to create a comprehensive ISUP in due time.

Vital triangle: A new concept to evaluate urban vitality

Urban vitality is a driving force of urban sustainable development and influences the well-being of its residents. To better understand and evaluate it, we defined urban vitality from the perspective of the urban organism and proposed the “vital triangle” conceptual framework linked to the three aspects of growth, diversity, and mobility. We designed an evaluation index system that includes the six dimensions of population, economy, society, government, environment, and external links by integrating multiple sets of heterogeneous data, and applied it to cities in the Yangtze River Delta. The results show that Shanghai, Nanjing, Suzhou, and Hangzhou have the highest vitality levels but are weak regarding their eco-environments. Cities with high vitality are distributed on the Z-shaped key development belt of the Yangtze River Delta urban agglomeration planning. Regional differences in external links and population vitality are significant, and these two dimensions pose weaknesses to many cities. The interregional differences linked to social vitality are the smallest. Vitality not only comes from within the urban system, but also greatly depends on the external environment. The concept “vital triangle” and relevant evaluation framework are intended to serve as a basis for future research, and the case study could provide some key decision-making support for urban planning and management.

Measuring City-Level Transit Accessibility Based on the Weight of Residential Land Area: A Case of Nanning City, China

A large body of research on transit accessibility emphasizes the importance of methods to simulating the real-world travel process. Few efforts have been made to conduct empirical research and comparative analysis of overall city-level transit accessibility. In addition, most of literatures utilize census tracts combined with the buffer method to estimate transit travel demand or available service areas, failing to take into account the reality that different land-uses have their own population. This research aims to develop an overall index of city-level transit accessibility based on the weight of residential land area. We integrated five types of destinations and the coverage of residential area within the transit stop service area to evaluate the overall structural problems of land use and public transportation in the process of urban development. Based on a case study on Nanning City, it was found that the weighted average travel distance is increased by 5.42 km, but the overall weighted travel time of the city is shortened by 7.65 min. In addition, an increase in coverage within the stop threshold and a decrease in the number of residential communities outside the threshold indicate that transit accessibility facilitates urban expansion. The empirical results show that the overall transit accessibility index can provide a reasonable measure criterion for the compact spatial structure and support urban strategic planning and address the problem of land use and public transport in the process of urban development.

Effective Screening and Texture Segmentation of Green Vegetation Cover Based on UAV Images

As an important part of the ecosystem, green vegetation coverage is crucial to people’s sensory and mental health. Using reliable data sets to classify and identify the green vegetation cover on the land surface and explore its spatial distribution law can provide important reference for the work of regional ecosystem managers and urban planners. The optimization of effective screening methods for green vegetation coverage areas is an important requirement to measure the surface vegetation status. UAV aerial images feature high definition, large scale, small area and high up-to-dateness. However, at present, there are few studies based on the reliable UAV aerial image system to identify green vegetation cover and further explore its spatial changes. In this study, 701 residential neighborhoods in Beijing were taken as the research objects, and the green vegetation of 7,695 sample points was identified by UAV. The green vegetation coverage was measured, and the spatial distribution pattern of green vegetation in different land surface areas was quantitatively compared. The results show that the image processing method proposed in this paper can effectively detect the boundary of green vegetation cover area from UAV aerial images, the correlation of texture segmentation is good, and the segmentation performance is better than other methods. The distribution of green vegetation cover in the research target area is uneven, with 63.79% of the research area having relatively low (Level 2) and medium (Level 3) green vegetation coverage, which indicates that the green vegetation coverage area in the research area is insufficient to meet the needs of regional ecosystem development. The characteristics of green vegetation cover in 16 districts in the study area are different, showing different spatial distribution patterns; except Xicheng District, there are 211 points without landscape in the area covered by green vegetation in 15 districts. The results can provide support for urban land surface planning and management.

DEFINITION OF REAL ESTATE: THEORETICAL ASPECTS

It has been proven that modern emergency conditions require a rethinking of approaches to the use of real estate as an important factor affecting regional development. Unfortunately, problematic issues related to socio-economic disparities, a decrease in the efficiency of land relations, and the possibilities of using modern information technologies are deepening. In addition, it is necessary to take into account the modern European experience of land administration and information provision of the formation and use of real estate based on the use of a multi-purpose cadastre. The issue of defining real estate as a complex concept that takes into account spatial, urban planning, investment and environmental support is ignored.
 The purpose of the study is a comprehensive definition of real estate, taking into account the influence of spatial, urban planning, investment, environmental factors at the regional level. To achieve the set goal, the following tasks were completed:
 - formation of a theoretical basis for the definition of real estate;
 - characteristics of regulatory legal support regarding the definition of real estate.
 For the formation and implementation of a multi-purpose cadastre, real estate is defined as a set of real estate objects, land, and other structures that are affected by various signs and characteristics (spatial, urban planning, investment, environmental), the use of which creates conditions and ensures the territorial development of regions.
 Based on the proposed definition of real estate, scientifically based recommendations for the development and implementation of the multi-purpose cadastre were characterized based on the results of their level assessment and modeling, which made it possible to single out directions for increasing the level of information provision and application of the multi-purpose cadastre for increasing the efficiency of real estate use at the regional level.

Identification of Embodied Environmental Attributes of Construction in Metropolitan and Growth Region of Melbourne, Australia to Support Urban Planning

As growth regions evolve to accommodate the increasing population, they need to develop a wider variety of residential properties to accommodate the varying needs of the residents. As a result, the new accommodation is denser which involves higher embodied water carbon and energy. This research compares the construction differences in metropolitan and growth regions of Melbourne to identify embodied carbon, water, and energy. Representative areas of 25 km2 are selected from both regions. The growth region has 80% of the built area comprised of 2nd generation low-rise residential buildings whereas the prolific construction type in the Metropolitan region is mixed purpose industrial with 30% of the built area comprising of this type. The methodology implies open-source satellite imagery to build a spatial dataset in QGIS. The visual identification of the constructions in the study areas enables to identity the materials used in their construction. The total embodied carbon, water, and energy for the Metropolitan region are 32,895 tonnes, 4192 mL, and 3,694,412 GJ, respectively, whereas in the growth region, the totals are 179,376 tonnes carbon, 2533 mL water, and 2,243,571 GJ. Whilst Metropolitan has a significantly higher overall footprint when this is compared to the population of each region, it is shown that the growth region with its current construction type has a higher embodied carbon, water, and energy per head. The total per head for Metropolitan is 226.7 GJ energy, 257 kL water, and 20 tonnes carbon, whereas in the growth region, the embodied energy, water, and carbon, respectively, per head is 287.4 GJ, 324.6 kL, and 22 tonnes. The current performance per head of the growth region is considerably lower than that of Metropolitan. Using diverse residential construction types and efficient materials can serve the demanding needs of denser populated areas.

Revealing Taxi Interaction Network of Urban Functional Area Units in Shenzhen, China

Characterizing the taxi travel network is of fundamental importance to our understanding of urban mobility, and could provide intellectual support for urban planning, traffic congestion, and even the spread of diseases. However, the research on the interaction network between urban functional area (UFA) units are limited and worthy of notice. Therefore, this study has applied the taxi big data to construct a travel flow network for the exploration of spatial interaction relationships between different UFA units in Shenzhen, China. Our results suggested that taxi travel behavior was more active in UFA units dominated by functions, including residential, commercial, scenic, and greenspace during weekends, while more active in UFA units dominated by industrial function during weekdays. In terms of daily average volume, the characteristics of spatial interaction between the various UFA types during weekdays and weekends were similar. During the morning peak period, the sink areas were mainly distributed in Futian District and Nanshan District, while during the evening peak period, the sink areas were mainly distributed in the southern part of Yantian District, the southwestern part of Longgang District, and the eastern part of Luohu District. The average daily taxi mobility network during weekdays showed a spatial pattern of “dense in the west and north, sparse in the south and east”, exhibiting significant spatial unevenness. Compared with weekdays, the daily taxi mobility network during weekends was more dispersed and the differences in node sizes decreased, indicating that taxi travel destinations were more diverse. The pattern of communities was more consistent with the administrative division during weekdays, indicating that taxi trips are predominantly within the districts. Compared with weekdays, the community pattern of network during weekends was clearly different and more in line with the characteristics of a small world network. The findings can provide a better understanding of urban mobility characteristics in Shenzhen, and provide a reference for urban transportation planning and management.

Prediction of network public opinion features in urban planning based on geographical case-based reasoning

ABSTRACT As a significant part of sustainable urban development proposed by the United Nations, urban planning is related to the ecological environment and transportation, especially affecting quality of life and social well-being. In the process of urban planning, the public express their opinions on open network platforms, resulting in large quantities of network public opinion data, which has important implications for evaluating urban planning. Based on the idea of geographical case-based reasoning (CBR), this paper constructs an expression framework for urban planning cases in the form of a ‘case problem–case attribute–case result’ triad. On this basis, this paper proposes a similarity calculation method of urban planning cases that integrates case attribute. Finally, based on an improvement to the traditional k-nearest neighbors method, the proposed public opinion feature calculation model considers similarity weights, which allow us to predict network public opinion features, including viewpoint-level emotional tendency and concerned groups of urban planning cases. The experimental result shows similarity weights (SWs) model could effectively improve the prediction accuracy, where the average MIC-F1 score reached more than 74%. Based on CBR, the proposed method can predict the development trends of public opinion in future planning cases, and provide scientific and reasonable decision support for urban planning.