scholarly journals Urban Growth and its Impact on Tangail Municipal Area

2016 ◽  
Vol 8 (2) ◽  
pp. 163-166
Author(s):  
BC Sarker ◽  
SC Shutradhar ◽  
A Khan ◽  
ASM Saifullah ◽  
AB Ruma
Keyword(s):  
Population Density ◽  
Urban Development ◽  
Natural Resources ◽  
Urban Growth ◽  
Traffic Congestion ◽  
Open Space ◽  
Sharp Rise ◽  
Secondary Sources ◽  
Factual Data ◽  
Survey Questionnaires

The study has endeavored to investigate the urban development and its impacts on Tangail municipality, Tangail, Bangladesh. The factual data have been collected from secondary sources, while the perceptual data are based on survey questionnaires on the opinions of respondents. Data were collected through instant spot observation (transect survey) and in-depth consultation, and interviews. The study displays that, the population of Tangail municipality rapidly augmented after 1971. For instance, the population rose from 19.875 thousand in 1961 to 128.785 thousand in 2001. Additionally, the area of Tangail municipality was 15.50 km2 in 1981 which has expanded to 29.40 km2 in 2001. The proposed area of Tangail municipality was five km2. In 1951 the level of urbanization in Tangail municipality was 1.79% which has experienced a sharp rise of 12.99 % in 2001. The study found that, the enlarged urbanization in Tangail town has resulted in higher population density, increased demand for food, alleviation of environmental pollution, increased traffic congestion, generation of solid waste, inadequate garbage disposal, effluent disposal into rivers, crime, and disappearing green and open space in the Tangail municipality.J. Environ. Sci. & Natural Resources, 8(2): 163-166 2015

scholarly journals MODELLING URBAN GROWTH FROM MEDIUM RESOLUTION LANDSAT IMAGERIES OF AKURE, NIGERIA

2014 ◽  
Vol 2 (6) ◽  
pp. 40-50
Author(s):  
Michael Ajide Oyinloye ◽  
Julius Olubumi Fasakin
Keyword(s):  
Land Cover ◽  
Urban Growth ◽  
Rapid Growth ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Open Space ◽  
Small Towns ◽  
Gis And Remote Sensing ◽  
Medium Resolution ◽  
The City

The city of Akure has experienced rapid growth in the past 2 to 3 decades which has led to the expansion of the core urban areas of the city into adjoining rural lands. The paper analyses the urban growth of Akure using medium resolution Landsat imageries. Landsat (MSS), Landsat Thematic Mapping(TM) and Landsat Enhanced Thematic Mapper (ETM+) images for 1972, 1986 and 2002 respectively were used in a post-classification comparison analysis to map the spatial dynamic of land cover changes and identify the urbanization process in Akure. The land cover statistical results revealed a rapid growth in the built-up area of Akure from 997.2 hectares in 1972 to about 3852.70 hectares in 2002 due to increase in population of Akure within this period. Results of the prediction showed that the built-up area of the city has increased in size from 977.2 hectares in 1972 to 5863.66 hectares in 2022 corresponding to 500% at the rate of 13.1% per annum. Implications of growth include loss of open space, pressure on limited infrastructure, overcrowding, traffic congestion and poor standard of living. The study recommends regular monitoring of urban area, development of small towns around the city area to avoid overcrowding, training of planners and administrators to acquire more knowledge in the use of GIS and remote sensing to enhance efficiency.

scholarly journals Predict and Simulate Sustainable Urban Growth by Using GIS and MCE Based CA. Case of Famagusta in Northern Cyprus

2021 ◽  
Vol 13 (8) ◽  
pp. 4446
Author(s):  
Can Kara ◽  
Naciye Doratlı
Keyword(s):  
Urban Development ◽  
Environmental Protection ◽  
Urban Growth ◽  
Open Space ◽  
Planning Process ◽  
Sustainable Urban Development ◽  
Soil Productivity ◽  
Development Scenarios ◽  
Multi Criteria Evaluation ◽  
The Future

The research study utilizes Multi Criteria Evaluation (MCE) method in geographic information systems (GIS) environment and uses MCE suitability maps with Cellular Automata (CA) for predicting and simulating sustainable urban development scenarios in Famagusta City. It represents first scenario-based simulations of the future growth of Famagusta as “do-nothing” and “sustainable”. Under the do-nothing scenario, Markov Chain probability analysis with CA models is used with temporal land-use/cover datasets based on the images from 2002 and 2011. It shows that, Famagusta City is moving away from sustainable development. Future expansion of both medium-density and low-density urban zones are always located around existing built-up urban area along transportation lines. A similar model is employed by applying sustainable urban development policies by the policy driven scenario. As a main goal, sustainable urban development includes three main criteria, compactness, environmental protection, and social equity. Additionally, brownfield development, distance from center, soil characteristics, soil productivity, vegetation, environmental protection areas (EPA), distance from local services, distance from open space are used as criteria with Analytical Hierarchy Process (AHP). Having such a simulation with the combination of MCE, GIS, and CA has several advantages. Prediction of urban growth presents possible alternative development in the future; visualization of decision making easier for town planners and supports the spatial planning process; and creates more realistic results of our choices related to urban growth.

scholarly journals Population Density or Populations Size. Which Factor Determines Urban Traffic Congestion?

2021 ◽  
Vol 13 (8) ◽  
pp. 4280
Author(s):  
Yu Sang Chang ◽  
Sung Jun Jo ◽  
Yoo-Taek Lee ◽  
Yoonji Lee
Keyword(s):  
Population Density ◽  
Population Size ◽  
Traffic Congestion ◽  
Critical Role ◽  
Small Population ◽  
High Density ◽  
Urban Traffic ◽  
Contradictory Result ◽  
Low Density

A large number of articles have documented that as population density of cities increases, car use declines and public transit use rises. These articles had a significant impact of promoting high-density compact urban development to mitigate traffic congestion. Another approach followed by other researchers used the urban scaling model to indicate that traffic congestion increases as population size of cities increases, thus generating a possible contradictory result. Therefore, this study examines the role of both density and population size on traffic congestion in 164 global cities by the use of Stochastic Impacts by Regression on Population, Affluence and Technology model. We divide 164 cities into the two subgroups of 66 low density cities and 98 high density cities for analysis. The findings from the subgroups analysis indicated a clear-cut difference on the critical role of density in low-density cities and the exclusive role of population size in high-density cities. Furthermore, using threshold regression model, 164 cities are divided into the two regions of large and small population cities to determine population scale advantage of traffic congestion. Our findings highlight the importance of including analysis of subgroups based on density and/or population size in future studies of traffic congestion.

scholarly journals Urban Growth: From pixel to reality

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Shyamantha Subasinghe
Keyword(s):  
Pattern Recognition ◽  
Urban Growth ◽  
Growth Pattern ◽  
Open Space ◽  
Spatial Configuration ◽  
Urban Land ◽  
Growth Patterns ◽  
Zone Model ◽  
Spatial Pattern Analysis ◽  
Ancillary Data

<p><strong>Abstract.</strong> Urban growth is a complex process created through the interaction of human and environmental conditions. The spatial configuration and dynamic process of urban growth is an important topic in contemporary geographical studies (Thapa and Murayama, 2010). However, urban growth pattern recognition is a challengeable task and it has become one of the major fields in Cartography. Since classical era of cartography, several methods have been employed in modelling and urban growth pattern recognition. It shows that there is no agreement among cartographer or any other spatial scientists on how to map the diverse patterns of urban growth.</p><p>Typical urban theories such as von Thünen’s (1826) bid-rent theory, Burgess’s (1925) concentric zone model, Christaller’s (1933) central place theory, and Hoyt’s (1939) sector model explain the urban structure in different manner. Most of them do not contribute to visualize the urban growth pattern spatiotemporally. Recently, by addressing this limitations, several sophisticated methods are used in urban growth visualization. Among them, morphological spatial pattern analysis (MSPA) is one of emerging raster data analysis methods which allows us to integrate neighbourhood interaction rules in urban growth pattern recognition and visualization. Angel et al. (2010) developed urban land classification (urban, suburban, rural, fringe open space, exterior open space, and rural open space) based on built and non-built land categories and detected three major types of urban growth (infill, extension, and leapfrog). However, developing urban land classifications using binary land use type and recognising only three types of urban growth pattern may be insufficient due to the existence of a higher complexity of urban growth. In such context, the present study introduce a geovisualization approach to map spatial patterns of urban growth using multiple land categories and develops three sub-levels of urban growth pattern for each major urban growth pattern.</p><p>The entire process of urban growth pattern recognition developed in this study can be summarized into three steps (Figure 1): (1) urban land mapping &amp;ndash; Landsat imageries representing two time points (2001 and 2017) were classified into two land categories (built and non-built) and developed into multiple classes using ancillary data, (2) recognizing three major patterns of urban growth (infill, extension, and leapfrog) &amp;ndash; the raster overlay method based on neighbourhood interaction rules, (3) development of sublevels of urban growth &amp;ndash; major three patterns were further developed and visualized nine urban growth patterns, namely low infill (LI), moderate infill (MI), high infill (HI), low extension (LE), moderate extension (ME), high extension (HE), low leapfrog (LL), moderate leapfrog (ML), and high leapfrog (HL). The developed procedure of this study in urban growth pattern recognition was tested using a case study of Colombo metropolitan area, Sri Lanka.</p>

The Worst of All Worlds

2005 ◽  
Vol 1902 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Eric Eidlin
Keyword(s):  
Los Angeles ◽  
Population Density ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Population Distribution ◽  
Housing Prices ◽  
The United States ◽  
Urban Life ◽  
Apparent Paradox ◽  
Gini Coefficients

Los Angeles, California, is generally considered the archetypal sprawling metropolis. Yet traditional measures equate sprawl with low population density, and Los Angeles is among the densest and thereby the least sprawling cities in the United States. How can this apparent paradox be explained? This paper argues that the answer lies in the fact that Los Angeles exhibits a comparatively even distribution of population throughout its urbanized area. As a result, the city suffers from many consequences of high population density, including extreme traffic congestion, poor air quality, and high housing prices, while offering its residents few benefits that typically accompany this density, including fast and effective public transit, vibrant street life, and tightly knit urban neighborhoods. The city's unique combination of high average population density with little differentiation in the distribution of population might best be characterized as dense sprawl, a condition that embodies the worst of urban and suburban worlds. This paper uses Gini coefficients to illustrate variation in population density and then considers a number of indicators–-most relating either to the provision of transportation infrastructure or to travel behavior–-that demonstrate the effects of low-variation population distribution on the quality of urban life in Los Angeles. This approach offers researchers, practitioners, and policy makers in Los Angeles and in smaller cities that are evolving in similar ways a useful and user-friendly tool for identifying, explaining, measuring, and addressing the most problematic aspects of sprawl.

“Green Infrastructure” Concept as an Effective Medium to Manipulating Sustainable Urban Development

2012 ◽  
pp. 1358-1377 ◽  
Author(s):  
Adnan Kaplan
Keyword(s):  
Urban Development ◽  
Social Services ◽  
Green Infrastructure ◽  
Social Life ◽  
Open Space ◽  
Sustainable Urban Development ◽  
Planning History ◽  
Urban Open Space ◽  
Urban Core ◽  
Metropolitan Cities

This chapter aims at exploring and conceptualizing green infrastructure (GI) as a comprehensive system in planning schemes of metropolitan cities such as Melbourne (Australia) and Izmir (Türkiye). Urban open space network(s) and its further step, “GI,” stretches out from the urban core through its periphery. This requires investigation of the planning hierarchy between metropolitan planning and urban design with a focus on connectivity and urban sustainability. Supporting and managing physical development, modes of transportation, and social life, GI provides ecological and social services to cities in pursuit of sustainable development. Following the scrutiny of Melbourne’s GI and its relevance to the planning history, this work undertakes a comparative analysis between Melbourne and Izmir in order to address the development of a metropolitan GI system for these cities. Such an approach would support policies and strategies relating to sustainable urban development.

Natural Resources Conservation in the Influence Areas of Cities

2011 ◽  
pp. 255-273
Author(s):  
Mihai Nita ◽  
Mihaita Iulian Niculae ◽  
Diana Onose ◽  
Maria Patroescu ◽  
Gabriel Ovidiu Vânau ◽  
...  
Keyword(s):  
Urban Planning ◽  
Urban Development ◽  
Natural Resources ◽  
Protected Areas ◽  
Sustainable Use ◽  
Ease Of Use ◽  
Gis Techniques ◽  
Resources Conservation ◽  
Green Belts

As urban development has become an increasing problem, urban planning is required to integrate social and economical needs with the sustainable use of natural resources. Lately planners have been using GIS techniques, based on international and local databases, in finding the most probable scenarios and the best available solutions. Four models of natural resources conservation have proved effective in the influence areas of cities: protected areas, yellow-green belts, regional parks, and oxygen generating surfaces. The establishment and management of these can be better realised by GIS techniques, because of their efficiency and ease of use, and the suitability and general availability of data.

“Green Infrastructure” Concept as an Effective Medium to Manipulating Sustainable Urban Development

2011 ◽  
pp. 234-254 ◽  
Author(s):  
Adnan Kaplan
Keyword(s):  
Urban Development ◽  
Social Services ◽  
Green Infrastructure ◽  
Social Life ◽  
Open Space ◽  
Sustainable Urban Development ◽  
Planning History ◽  
Urban Open Space ◽  
Urban Core ◽  
Metropolitan Cities

This chapter aims at exploring and conceptualizing green infrastructure (GI) as a comprehensive system in planning schemes of metropolitan cities such as Melbourne (Australia) and Izmir (Türkiye). Urban open space network(s) and its further step, “GI,” stretches out from the urban core through its periphery. This requires investigation of the planning hierarchy between metropolitan planning and urban design with a focus on connectivity and urban sustainability. Supporting and managing physical development, modes of transportation, and social life, GI provides ecological and social services to cities in pursuit of sustainable development. Following the scrutiny of Melbourne’s GI and its relevance to the planning history, this work undertakes a comparative analysis between Melbourne and Izmir in order to address the development of a metropolitan GI system for these cities. Such an approach would support policies and strategies relating to sustainable urban development.

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