scholarly journals Urban morphology as a tool for exploring the land use in residential areas: Example of New Belgrade

Spatium ◽  
2015 ◽  
pp. 76-83
Author(s):  
Ranka Gajic
Keyword(s):  
Land Use ◽  
Urban Morphology ◽  
Urban Land Use ◽  
Land Policy ◽  
Residential Areas ◽  
Private Interests ◽  
Research Findings ◽  
Morphogenetic Analysis ◽  
Morphological Patterns

The paper presents findings of research about the classification of New Belgrade?s super-blocks using the typomorphology approach and the morphogenetic analysis of urban morphology in relation to land use. The example of New Belgrade is particularly interesting given the fact that the morphological patterns of land use within its superblocks were created during the period of non-market economy in Socialism, and now it is possible to review the effect that the socio-political transition into Capitalism, which started in the 1990s, has had on its land use. As a result, a data base with the typology of residential super-blocks of New Belgrade is created: from the perspective of urban land use there are four main morphological types (with the subtypes) taking into account the morphology of the position of the buildings on the terrain, and traffic (cars-pedestrian) flows. The morphogenetic analysis reveals that after the 1990s there are processes pointing to powerful influence of land policy driven by private interests. Research findings suggest that nowadays there are negative trends of using the land in super-blocks in New Belgrade - e.g. percentage of land occupancy by buildings is getting bigger and almost 100% of the un-built soil in the newly developed super-blocks is covered /paved.

Expert system classification of urban land use/cover for Delhi, India

2008 ◽  
Vol 29 (15) ◽  
pp. 4405-4427 ◽  
Author(s):  
Elizabeth A. Wentz ◽  
David Nelson ◽  
Atiqur Rahman ◽  
William L. Stefanov ◽  
Shoursaseni Sen Roy
Keyword(s):  
Land Use ◽  
Expert System ◽  
Urban Land ◽  
Urban Land Use

scholarly journals Social Sensing for Urban Land Use Identification

2020 ◽  
Vol 9 (9) ◽  
pp. 550
Author(s):  
Adindha Anugraha ◽  
Hone-Jay Chu ◽  
Muhammad Ali
Keyword(s):  
Land Use ◽  
Accuracy Assessment ◽  
Urban Land ◽  
Demographic Characteristics ◽  
Urban Land Use ◽  
Land Uses ◽  
Land Use Classification ◽  
Residential Areas ◽  
Social Sensing ◽  
Land Use Maps

The utilization of urban land use maps can reveal the patterns of human behavior through the extraction of the socioeconomic and demographic characteristics of urban land use. Remote sensing that holds detailed and abundant information on spectral, textual, contextual, and spatial configurations is crucial to obtaining land use maps that reveal changes in the urban environment. However, social sensing is essential to revealing the socioeconomic and demographic characteristics of urban land use. This data mining approach is related to data cleaning/outlier removal and machine learning, and is used to achieve land use classification from remote and social sensing data. In bicycle and taxi density maps, the daytime destination and nighttime origin density reflects work-related land uses, including commercial and industrial areas. By contrast, the nighttime destination and daytime origin density pattern captures the pattern of residential areas. The accuracy assessment of land use classified maps shows that the integration of remote and social sensing, using the decision tree and random forest methods, yields accuracies of 83% and 86%, respectively. Thus, this approach facilitates an accurate urban land use classification. Urban land use identification can aid policy makers in linking human activities to the socioeconomic consequences of different urban land uses.

scholarly journals Machine Learning Algorithms for Urban Land Use Planning: A Review

Urban Science ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 68
Author(s):  
Vineet Chaturvedi ◽  
Walter T. de Vries
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Land Use Change ◽  
Urban Growth ◽  
Land Use Planning ◽  
Pattern Analysis ◽  
Urban Land ◽  
Earth Observation ◽  
Urban Land Use

Urbanization is persistent globally and has increasingly significant spatial and environmental consequences. It is especially challenging in developing countries due to the increasing pressure on the limited resources, and damage to the bio-physical environment. Traditional analytical methods of studying the urban land use dynamics associated with urbanization are static and tend to rely on top-down approaches, such as linear and mathematical modeling. These traditional approaches do not capture the nonlinear properties of land use change. New technologies, such as artificial intelligence (AI) and machine learning (ML) have made it possible to model and predict the nonlinear aspects of urban land dynamics. AI and ML are programmed to recognize patterns and carry out predictions, decision making and perform operations with speed and accuracy. Classification, analysis and modeling using earth observation-based data forms the basis for the geospatial support for land use planning. In the process of achieving higher accuracies in the classification of spatial data, ML algorithms are being developed and being improved to enhance the decision-making process. The purpose of the research is to bring out the various ML algorithms and statistical models that have been applied to study aspects of land use planning using earth observation-based data (EO). It intends to review their performance, functional requirements, interoperability requirements and for which research problems can they be applied best. The literature review revealed that random forest (RF), deep learning like convolutional neural network (CNN) and support vector machine (SVM) algorithms are best suited for classification and pattern analysis of earth observation-based data. GANs (generative adversarial networks) have been used to simulate urban patterns. Algorithms like cellular automata, spatial logistic regression and agent-based modeling have been used for studying urban growth, land use change and settlement pattern analysis. Most of the papers reviewed applied ML algorithms for classification of EO data and to study urban growth and land use change. It is observed that hybrid approaches have better performance in terms of accuracies, efficiency and computational cost.

scholarly journals Assessing the Accuracy of the Pixel-Based Algorithms in Classifying the Urban Land Use, Using the Multi Spectral Image of the IKONOS Satellite (Case Study, Uromia City)

2014 ◽  
Vol 11 ◽  
pp. 40-56 ◽  
Author(s):  
Esmaeel Safaralizade ◽  
Robab Husseinzade ◽  
Gholamhussein Pashazade ◽  
Bakhtiar Khosravi
Keyword(s):  
Land Use ◽  
Maximum Likelihood ◽  
Minimum Distance ◽  
Urban Land ◽  
Urban Land Use ◽  
Error Matrix ◽  
Sensing Technology ◽  
Method Of Maximum Likelihood

With the development of urbanization and expansion of urban land use, the need to up to date maps, has drawn the attention of the urban planners. With the advancement of the remote sensing technology and accessibility to images with high resolution powers, the classification of these land uses could be executed in different ways. In the current research, different algorithms for classifying the pixel-based were tested on the land use of the city of Urmia, using the multi spectral images of the IKONOS satellite. Here, in this method, the algorithms of the supervised classification of the maximum likelihood, minimum distance to mean and parallel piped were executed on seven land use classes. Results obtained using the error matrix indicated that the algorithm for classifying the maximum likelihood has an overall accuracy of 88/93 % and the Kappa coefficient of 0/86 while for the algorithms of minimum distance to mean and parallel piped , the overall accuracy are 05/79 % and 40/70 % respectively. Also, the accuracy of the producer and that of the user in most land use classes in the method of maximum likelihood are higher compared to the other algorithms.

scholarly journals CLASSIFICATION OF LITHUANIAN TOWNS AND DEFINITION OF THEIR FUNCTIONAL STRUCTURE USED FOR URBAN PLANNING PURPOSES

2006 ◽  
Vol 30 (4) ◽  
pp. 181-191
Author(s):  
Zigmas Jonas Daunora
Keyword(s):  
Land Use ◽  
Urban Planning ◽  
Public Transportation ◽  
Urban System ◽  
The Other ◽  
Functional Structure ◽  
Residential Areas ◽  
Urban Structures ◽  
Ecological Requirements

Comprehensive planning of towns and townships takes a wider scale in the country. Therefore, there appears an urgent need to revise or review some conceptions of planning methodology that should be accepted after various alternatives consideration. According to our opinion: a) classification of centres of a settlement system (towns and townships) requires self-determination and equal understanding which, from one side, should reflect more precisely the existing diversity of development between the centres and their functions and, from the other side, the rank granted to these centres should meet the EU criteria; b) the functional structure of towns and townships, reflected by diversity in the purpose of their territory use and its indefinite character during the process of residential area modernization which takes place under market conditions, forces to give upa detailed setting of plot purpose and look for a more universal model of land- use purpose specification which could be applicable not only for planning of rural agricultural territories but for urban planning of residential areas as well. Proposals presented in the paper (Tables 1 and 2) respect the systematic conception of settlement network, accepted in Lithuania and in the other EU countries and based on the hierarchy of elements and development dependency allowing application of sustainability and balance principles for the system element development. They are prepared taking into account new urban planning conceptions and reflecting the following factors: changing business and production conditions as well as growing qualitative safety, service and ecological requirements for a residential environment; increasing importance of economic factors and resulting need for a more rational land use and broader urban internal integration when developing public transportation and urban system for a common space use; respect to stable urban structural elements of residential areas (urban framework) as well as to local cultural identity and historically formed compositional peculiarities; advantages of the functional and social diversity and polycentric character of urban structures.

scholarly journals Multiscale Based Characterization and Classification of Urban Land-Use

2019 ◽  
Author(s):  
Jacob Arndt ◽  
Dalton Lunga ◽  
Jeanette Weaver ◽  
St. Thomas LeDoux ◽  
Sarah Tennille
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use

Public Spaces and Concentrations of Child Labourers in Ibadan Municipality, Nigeria

2021 ◽  
pp. 002190962098874
Author(s):  
Amos Oluwole Taiwo ◽  
Adewumi Israel Badiora ◽  
Temitope Muyiwa Adebara
Keyword(s):  
Land Use ◽  
Public Spaces ◽  
Urban Land ◽  
Child Labour ◽  
Urban Land Use ◽  
Descriptive Statistics ◽  
Residential Areas ◽  
Direct Counting ◽  
The Relationship

Against the background of the solution-defying incidence of child labourers in Nigerian cities, this study examined the relationship between public spaces and incidence of child labourers in Ibadan Municipality, Nigeria. Data were obtained through direct counting of child labourers and cursory observation of the physical and environmental compositions of their places of operation. The direct counting was conducted for seven days of the week in the morning, afternoon and evening within defined activity-nuclei purposively selected across three densities of residential areas of the municipality: high, medium and low. The data collected were subjected to descriptive statistics. Findings showed that the incidence and categories of child labourers varied with public spaces and density of residential areas, and also followed the concentric, sector and multiple nuclei theories of urban land use. The study, therefore, recommended that urban planners and government have roles to play in offering lasting solution to the menace of child labour.

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