Analysis Of Urban Structure Research Articles

Estimating urban spatial structure based on remote sensing data

Understanding the spatial structure of a city is essential for formulating a spatial strategy for that city. In this study, we propose a method for analyzing the functional spatial structure of cities based on satellite remote sensing data. In this method, we first assume that urban functions consist of residential and central functions, and that these functions are measured by trip attraction by purpose. Next, we develop a model to explain trip attraction using remote sensing data, and estimate trip attraction on a grid basis. Using the estimated trip attraction, we created a contour tree to identify the spatial extent of the city and the hierarchical structure of the central functions of the city. As a result of applying this method to the Tokyo metropolitan area, we found that (1) our method reproduced 84% of urban areas and 94% of non-urban areas defined by the government, (2) our method extracted 848 urban centers, and their size distribution followed a Pareto distribution, and (3) the top-ranking urban centers were consistent with the districts defined in the master plans for the metropolitan area. Based on the results, we discussed the applicability of our method to urban structure analysis.

Analytical assessment of street-level tree canopy in Austrian cities: Identification of re-naturalisation potentials of the urban fabric

Climate change-related impacts such as heat stress, extreme weather events, and their consequences are particularly felt within densely built-up urban areas. Urban re-naturalisation is recognised as a promising cost-effective strategy for improving urban resilience to these environmental and societal issues. In this respect, the present contribution focuses on a comprehensive city-wide assessment of street-level urban tree canopy to detect the existing vegetation gaps and identify re-naturalisation potentials within the urban fabric for the three largest cities in Austria (Vienna, Graz, and Linz). The study relies on QGIS and R software environments to carry out spatial data analytics on georeferenced tree cadastre data and the global map of Local Climate Zones (LCZ) to compute spatial density maps and urban structure parameters. The results suggest a rather random distribution of tree clusters and highly fragmented instances within the city. This fragmentation is predominantly observed within central densely built urban fabric for all three cities, with the absence of street trees in peripheral urbanised areas being more prominent in Graz and Linz. The computed percentage of potentially disconnected areas in terms of the tree canopy for Vienna, Graz, and Linz amounts to 45%, 54%, and 37%, respectively. The analysis of urban structure revealed a homogeneous densely built-up character over central districts and a dominantly heterogeneous character across non-central and peripheral districts with a more openly built fabric (this heterogeneity is, generally more prominent in the case of Graz and Linz). In general, there are numerous opportunities for urban re-naturalisation, focusing on urban trees within such openly arranged buildings. Due to the evident physical constraints of the urban space within central districts, the consideration of building-level greening (e.g. green roofs, green facades) may be a better approach to urban re-naturalisation in these cases. Given the further constraints imposed by the abundance of historic buildings, such measures may not be feasible in every event. Hence, this calls for consideration of novel, innovative and emerging greening systems with the proposition of movable vertical green screens and vertical gardens.

Analyzing the Structure of Residence–Leisure Network in Shenyang City

Leisure is an important part of the daily activities of urban residents. A relatively dense flow of people will be generated between residential areas and supermarkets, as well as between residential areas and highly popular park facilities. These flows of people can reflect the characteristics of residents’ leisure activities and the spatial characteristics of urban residence–leisure functions, as opposed to static leisure facilities and places; it is a new perspective for the study of urban spatial structure. Network studies on the relationship between residential and leisure functions within cities are rarely seen. In this study, from the flow space perspective, based on the questionnaire data, points of interest data, and mobile phone signaling data, the actual leisure travel flows of residents with different travel purposes can be identified, including residence–shopping leisure flows and residence–park leisure flows, and the corresponding urban networks can be constructed from them. With the help of complex network analysis, this paper discusses different types of residence–leisure network structures and their influencing factors in terms of network characteristics, node strength, and QAP analysis. It deepens the understanding of the urban spatial structure and provides the theoretical basis and technical support for urban structure analysis, urban layout optimization, and urban planning and management. The results show that: ① Both residence–shopping leisure and residence–park leisure networks have the small-world characteristics and scale-free properties of complex networks. ② The characteristics of the nodes of the residence–leisure network for different leisure travel purposes indicate that residents go more to Taiyuan Street and the New North Station business circle for shopping activities, and the parks that attract residents to go out for walks are concentrated in the central part of the city. ③ Different types of network structures have a strong correlation with the number of residential functions and leisure facilities but have a weak correlation with the difference in the number of inhabitants and leisure travel distance. This study enriches the research cases of the urban residence–leisure network structure to a certain extent. Shenyang City has the same background of rapid expansion as other large cities in China, and this study has an important role in planning and inspiration for solving urban diseases and achieving the orderly and rational development of large cities.

Analysis of urban structures in a company town. Beginning, development, and decline of the “New Camp” case, Chuquicamata

This research addresses the analysis of the different historical periods of Chuquicamata’s “New Camp”, in the Region of Antofagasta, looking closely at the evolution of its urban structure from the inception, development, and decline of the copper camp. Its purpose is to analyze the mutations of the built urban space, characterizing the interactions and meeting places of the Company Town residents , with the characterization of the different historical periods of Chuquicamata. For this, a literature review is carried out, and urban planimetric material is developed and collected from the different historical stages. Among the main conclusions, the process of decline is illustrated by comparing the mutations of the urban space in the different historical stages of the copper camp, analyzing the prioritization phenomenon of a production system, and the economic growth at the expense of residential well-being and living conditions.

Modelling the interdependence of spatial scales in urban systems

The multitude of interwoven spatial scales and their relevance for urban systems has been of interest to the complexity science of cities since its conception. Today, we are well aware that urban environments are being simultaneously shaped and organised through actions at all levels. However, the fundamental question of how to reveal and quantify the interdependence of processes in between various spatial and temporal scales is less often addressed. Deepening our theoretical understanding of the multiscale spatiotemporal complexity of urban systems demands a transdisciplinary framework and the deployment of novel and advanced mathematical models. This article performs a multiscale analysis of urban structures using a large dataset of rent price values in the Ruhr area, Germany. We argue that, due to their many interacting degrees of freedom, urban systems exhibit similar features as other strongly correlated systems, for example, turbulent flows, notably the occurrence of extreme small-scale fluctuations. This analogy between urban and turbulent systems, which we support by empirical evidence, allows for the modelling of spatial structures on the basis of concepts and methods from turbulence theory. We demonstrate how by identifying the main turbulence-borrowed characteristics of an arbitrary two-dimensional urban field, it can be fully reproduced with a small number of prescribed points. Our findings have theoretical implications in the way we quantify and analyse scales in urban systems, model small-scale urban structures as well as potential policy relevance on understanding the evolution and spatial organisation of cities.

MULTIPLE ENDMEMBER SPECTRAL MIXTURE ANALYSIS OF DESIS IMAGE TO IDENTIFY ROOFTOPS IN KIGALI

Abstract. The development and increase of multi and hyperspectral sensors in the recent years have significantly improved urban structure analysis and interpretation. The current study is the first to investigate the potential of DESIS hyperspectral images for the detection or identification of urban roof materials. After field campaigns in 2014, 2015 and 2018 to collect ground truth points and rooftops radiometric properties; a linear spectral mixture, implemented using a non-negative least squares (NNLS) regression based on the sequential coordinate-wise algorithm (SCA) was applied on a DESIS image from 2020 of Kigali city to identify the different rooftops material and color. Although results show that most endmembers were predicted with a very low probability, the study proved that the combination of spectral mixture and hyperspectral data such as DESIS have great potential in the detection of rootops material. The presented study also highlghted a number of challenges resulting from the choice of spectral mixture algorithm and colinearity between materials.

Analysis of Urban Structure and Healthy City: Ede Metropolitan City In Perspective

Analysis of Urban Structure and Healthy City: Ede Metropolitan City In Perspective

Liquid Spaces: Understanding of Urban Spatial Networks through the Human Data

Today’s cities are changing faster than ever before, mainly because they have ability to produce spaces for everyone, but only when they are produced by everyone [1]. This phenomenon was even multiplied with enhanced informatisation and digitalisation. It would be wrong to perceive Smart City only as plain product of technological innovations. New markets are rising and new types of behaviour are emerging hand in hand with technological innovations [2]. Therefore technological innovations, mainly than enhanced communication and digitalisation change the habits of analogue civilisation towards more liquid spaces. Cities are forced to adapt to those changes in order to stay competitive. Therefore it seems that traditional planning reaches its limits and can’t fully address challenges produced by such change, which makes it unsustainable approach on the long term perspective. Project aims to develop set of tools and approaches towards creation of more liveable and resilient cities of 21. century by combining modern technologies, and humanocentric approach. Focus should be put on the research of relationship between the technological innovations (namely digitalisation and enhanced communication) and societal changes that transforms into material (urbanised) environment [3]. Understanding of urban spatial structures via gathering and analysing a new type of information about the city – the data – plays a key role in the research. As such, focus will be put on the analysis of urban structures through the online and offline participatory platform (Emotional maps), spatial footprint of the city (Master plan and field research), and segment analysis of the city’s structure (Space Syntax).

Discovering Frequent Movement Paths From Taxi Trajectory Data Using Spatially Embedded Networks and Association Rules

In view of the complex traffic flows, spatial interactions within a city exhibit the properties of dynamics, connectivity, and repeatability. This paper aims at mining spatial–temporal movement patterns from massive taxi trajectory data for discovering the inherent travel flow information within the urban system. Similar to the role of ocean circulation in a marine system, identifying the frequent paths and cycles of the travel flows within a city would be critical for understanding the principles behind the travel flow surfaces. Thus, we propose a multi-level method for the discovery of movement paths by incorporating the techniques of network analysis and association rules. Specifically, the proposed method begins by constructing a directed network on the subdivision of the study region, in which the node with geolocation represents the corresponding cell and the edge with weight represents the travel flow between neighboring cells. The method then adopts an extended label propagation clustering algorithm to identify frequent paths and cycles on the flow network within a specific time interval. Finally, to extract frequent paths during the whole time period, we also develop an association rules mining algorithm by modeling the edges as items and the paths in each time span as transactions. Experiment results demonstrate that our framework is able to effectively mine movement patterns in taxi trajectory data. Our results are expected to provide an avenue for further research, such as transportation planning and urban structure analysis.

Analysis of Urban Structure made by Creative Class Part 2

Analysis of Urban Structure made by Creative Class Part 2

Analysis of Urban Structure made by Creative Class

Analysis of Urban Structure made by Creative Class

Urban Social Media Inequality

Social media content shared today in cities, such as Instagram images, their tags and descriptions, is the key form of contemporary city life. It tells people where activities and locations that interest them are and it allows them to share their urban experiences and self-representations.
 Therefore, any analysis of urban structures and cultures needs to consider social media activity. In our paper, we introduce the novel concept of social media inequality. This concept allows us to quantitatively compare pattern in social media activities between parts of a city, a number of cities, or any other spatial areas. We define this concept using an analogy with the concept of economic inequality. Economic inequality indicates how some economic characteristics or material resources, such as income, wealth or consumption are distributed in a city, country or between countries. Accordingly, we can define social media inequality as the measures of distribution of characteristics of social media content shared in a particular geographic area or between areas. An example of such characteristics is the number of photos shared by all users of a social network such as Instagram in a given city or city area, or the content of these photos.
 We propose that the standard inequality measures used in other disciplines, such as the Gini coefficient, can also be used to characterize social media inequality. To test our ideas, we use a dataset of 7,442,454 public geo-coded Instagram images shared in Manhattan during five months (March — July) in 2014, and also selected data for 287 Census tracts in Manhattan. We compare patterns in Instagram sharing for locals and for visitors for all tracts, and also for hours in a 24 hour cycle. We also look at relations between social media inequality and socio-economic inequality using selected indicators for Census tracts. The inequality of Instagram images shared in Manhattan turns out to be bigger than inequalities in levels of income, rent, and unemployment.

Role of Housing Reconstruction Between Years 2000 - 2014 in Merging of Urban Structure of The North East Wrocław / Rola Zabudowy Mieszkaniowej z Lat 2000-2014 w Scalaniu Struktury Urbanistycznej Północno-Wschodniego Wrocławia

The article presents the urban structure of the North-East of Wroclaw, where in the vicinity of the historic buildings and residential buildings from the 70s of the last century, and between, in the last 20 years there were built new buildings, as binding material of the urban structure. The new multifamily housing development of years 2000-2014 of Psie Pole as a housing development in Wroclaw, closes the gap between the historic district residential buildings in the old Psie Pole and the buildings of large slabs of the 70s of the twentieth century. The contemporary residential development uses the existing social infrastructure centre of the old Psie Pole district, and also the social infrastructure of the housing development of 70s of the twentieth century. The authors analyze, in the first part, the spatial development of these areas on the basis of historical materials. In the following, based on an analysis of urban structure created in the last 15 years of development, analyze existing conditions, context and value (in terms of urban planning - the wealth of social infrastructure), the contemporary housing development of Psie Pole.

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas.

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction.

Compact development and energy consumption: Scenario analysis of urban structures based on behavior simulation

This study investigates the relationship between compact development and energy consumption by simulating individual consumption behaviors in monocentric and polycentric urban structures in Kumamoto in 2030. A model is developed to estimate individual consumption behaviors and demand of mobility goods and non-mobility goods at micro level. By considering the economic factor of income, the energy consumption is calculated based on demand of goods under Business as usual scenario, Central Core City scenario, and Multi-pole structure scenario. Results indicate the urban structure influences individual consumption behaviors and energy consumption. Increased consumption of the non-mobility goods and mass transit trips is shown in Central Core City scenario and the Multi-pole structure scenario. Monocentric urban structures as shown in Central Core City scenario show less effect on energy consumption than the polycentric urban structure in Multi-pole structure scenario. The findings suggest that the multi-pole urban structure is a better choice for compact development in Kumamoto based on less energy consumption. The method in this study provides a new approach to analyze the influence of urban structure on energy consumption at micro level. Findings give good suggestions for planning policy making regarding to compact development in Kumamoto.

Combining smart card data and household travel survey to analyze jobs–housing relationships in Beijing

Location Based Services (LBS) provide a new perspective for spatiotemporally analyzing dynamic urban systems. Research has investigated urban dynamics using LBS. However, less attention has been paid to the analysis of urban structure (especially commuting pattern) using smart card data (SCD), which are widely available in most large cities in China, and even in the world. This paper combines bus SCD for a one-week period with a oneday household travel survey, as well as a parcel-level land use map to identify job–housing locations and commuting trip routes in Beijing. Two data forms are proposed, one for jobs–housing identification and the other for commuting trip route identification. The results of the identification are aggregated in the bus stop and traffic analysis zone (TAZ) scales, respectively. Particularly, commuting trips from three typical residential communities to six main business zones are mapped and compared to analyze commuting patterns in Beijing. The identified commuting trips are validated by comparison with those from the survey in terms of commuting time and distance, and the positive validation results prove the applicability of our approach. Our experiment, as a first step toward enriching LBS data using conventional survey and urban GIS data, can obtain solid identification results based on rules extracted from existing surveys or censuses.

Can visibility predict location? Visibility graph of food and drink facilities in the city

The spatial arrangement of socio-economic facilities in the city is shaped by the interaction of many individuals in the context of a particular physical structure. The urban physical environment displays characteristics of networks (graphs) where nodes and edges are embedded in space. For decades, the analysis of urban network structure represents an attractive model for describing urban phenomena. This paper presents novel means of understanding how socio-economic activities are distributed in urban environment, what forces influence their spatial patterns and how urban structure and functions are mutually dependent. We investigate the functional aspect of urban spatial networks; specifically we study the spatial distribution of food and drink public facilities in the historical district of Tel Aviv-Yafo Israel. These places, cafés, coffee shops, restaurants and others are known as ‘third place’ in urban sociology and play an important role in establishing a sense of place. We propose a novel graph analytic framework in which the third places are incorporated by means of visual accessibility. The development of this framework emerged from the concept of Integrative Visibility Graph (IVG), a quantitative method, based on visibility analysis of urban structure and its functioning. Several centrality measures from complex network theory are applied to the proposed graphs in order to evaluate structural position of third place locations in the urban network. Our findings illustrate a strong correlation between street centrality values and third place distribution.

Determination of Ventilation Channels In Urban Area: A Case Study of Wrocław (Poland)

Urban areas are among the roughest landscapes in the Earth and its aerodynamical properties are responsible for a lot of processes and phenomena of urban climate, such as surface drag and pollutant dispersion. These properties can be quantitatively expressed by various parameters, with zero plane displacement height (z d) and roughness length (z 0) as the most frequently applied. Based on remotely gathered (LIDAR scan) height data and morphometric methods of roughness calculations, the comprehensive procedure to determine ventilation channels in urban area is proposed and implemented on the example from Wroclaw, Poland. Morphometric analysis of urban structure allowed establishing a proper database of aerodynamic parameters of the city. Then a series of maps of the city showing the distribution of two roughness parameters were prepared. GIS tools were used to carry out the analysis of roughness data, assuming various directions of wind flow. It enabled to determine the locations of potential ventilation paths in the city which, if combined, form large ventilation channels. They may have a significant role in improving air quality and be a valuable source of information for local government responsible for the appropriate development of the city.

Exposure Estimation from Multi-Resolution Optical Satellite Imagery for Seismic Risk Assessment

Given high urbanization rates and increasing spatio-temporal variability in many present-day cities, exposure information is often out-of-date, highly aggregated or spatially fragmented, increasing the uncertainties associated with seismic risk assessments. This work therefore aims at using space-based technologies to estimate, complement and extend exposure data at multiple scales, over large areas and at a comparatively low cost for the case of the city of Bishkek, Kyrgyzstan. At a neighborhood scale, an analysis of urban structures using medium-resolution optical satellite images is performed. Applying image classification and change-detection analysis to a time-series of Landsat images, the urban environment can be delineated into areas of relatively homogeneous urban structure types, which can provide a first estimate of an exposed building stock (e.g., approximate age of structures, composition and distribution of predominant building types). At a building-by-building scale, a more detailed analysis of the exposed building stock is carried out using a high-resolution Quickbird image. Furthermore, the multi-resolution datasets are combined with census data to disaggregate population statistics. The tools used within this study are being developed on a free- and open-source basis and aim at being transparent, usable and transferable.

Diferenciación residencial de los aglomerados mayores de la región centro de Argentina

Investigaciones sobre la heterogeneidad intraurbana han dado lugar al estudio de las dimensiones intervinientes en ella y del análisis de la estructura urbana. En este contexto, el artículo identifica y analiza la distribución espacial de los factores comunes subyacentes a la diferenciación socioespacial de los aglomerados mayores de la región centro de Argentina a partir de aspectos demográficos, económicosy sociales. Empleando técnicas de análisis multivariante se discriminaron diecinueve variables, con base en estas se identificaron cuatro factores subyacentes a la diferenciación residencial de la población residente en los aglomerados, asimismo, se analizó la adecuación de la estructura de los aglomerados a los modelos de ciudad latinoamericana a partir de la representación espacial de laspuntuaciones de dichos factores.