Urban growth pattern identification : a case study in Siem Reap, Cambodia

The main purpose of this paper is to identify the pattern of urban growth from 1993 to 2011 in Siem reap town, Cambodia. Land use and land cover maps were generated from Landsat TM imageries from different years in order to extract the information related to urban sprawl. The settlement pattern theory, geographic pattern analysis and visualisation interpretation were used to detect the pattern of urban growth in Siem Reap. Result shows that from 1993 to 2011 the urban area grew significantly, about 102.51%. The development of core settlement areas in Siem Reap revealed to be concentrated along main roads and along the river in the past and still keeping the same trend in the present. The current pattern of urban settlement in Siem Reap was classified as clustered and linear, following the roads network

SPATIAL PATTERN ANALYSIS IN GEOSPATIAL APPROACH REFERENCE TO KADUWELA MUNICIPAL COUNCIL, SRI LANKA

Cities play a significant role in our lives, providing a place for fulfilling social, economic, and physical needs for more than half of the population in the entire world. The city is a dynamic entity with complex activities, and it faces gradual physical changes or urban growth. Urban growth occurs in a planned or unplanned way. Unplanned urban growth or urban sprawl aggravated huge urban problems in cities and the fringe. Identification of urban growth pattern is significant and measuring and predicting the urban growth in a methodical way is an essential for the decision-making process. Measuring the urban growth pattern is essential and ArcGIS 10 provides an impressive analytical tool for geographic pattern analysis that helps to understandthe geographical phenomenon using spatial autocorrelation. Spatial autocorrelation can be applied to detect the pattern of urban areas at a specific time. This study used those tools to analyse spatial pattern in the Sri Lankan urban area. Results show type of spatial pattern of the area

A proposed methodology for understanding urban growth pattern : a case study in Siem Reap, Cambodia

In this paper, the main goal is to understand the relationship between urban growth and physical factors in order to determine the potential area for future urban expansion. A methodology is suggested for understanding urban growth pattern in Siem Reap which could effectively sustain archaeological sites and to balance the land use between urban and non-urban areas in Siem Reap, Cambodia. Remote sensing technique is used to analyze land use maps of Siem Reap from 1993 to 2011. Results show that urban-built up area increased significantly which causes the forest land to reduce steadily from 1993 to 2003 in the Siem Reap archaeological sites. In addition, Geographic Information System (GIS) is applied to analyze urban growth pattern. Geo-processing and logical functions are applied to detect and quantify the land use changes, especially urban changes. Two main factors are used to analyze the urban driving growth in Siem Reap, which are distance to road networks and population density. Pearson correlation statistics is applied to justify the relationship between the factors and urban area growth

Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana'a metropolitan city, Yemen.

An effective and efficient planning of an urban growth and land use changes and its impact on the environment requires information about growth trends and patterns amongst other important information. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries however, there exist a very few studies showing the application of these models and their performances. In this study two models such as cellular automata (CA) and the SLEUTH models are applied in a geographical information system (GIS) to simulate and predict the urban growth and land use change for the City of Sana’a (Yemen) for the period 2004–2020. GIS based maps were generated for the urban growth pattern of the city which was further analyzed using geo-statistical techniques. During the models calibration process, a total of 35 years of time series dataset such as historical topographical maps, aerial photographs and satellite imageries was used to identify the parameters that influenced the urban growth. The validation result showed an overall accuracy of 99.6 %; with the producer’s accuracy of 83.3 % and the user’s accuracy 83.6 %. The SLEUTH model used the best fit growth rule parameters during the calibration to forecasting future urban growth pattern and generated various probability maps in which the individual grid cells are urbanized assuming unique “urban growth signatures”. The models generated future urban growth pattern and land use changes from the period 2004–2020. Both models proved effective in forecasting growth pattern that will be useful in planning and decision making. In comparison, the CA model growth pattern showed high density development, in which growth edges were filled and clusters were merged together to form a compact built-up area wherein less agricultural lands were included. On the contrary, the SLEUTH model growth pattern showed more urban sprawl and low-density development that included substantial areas of agricultural lands

Modeling urban growth pattern for sustainable archaeological sites : a case study in Siem Reap, Cambodia

In this paper, the main goal is to understand the relationship between urban growth and physical factors in order to determine the potential area for future urban expansion. A policy is suggested that could effectively sustain the archaeological sites and to balance the land use between urban and non-urban areas in Siem Reap, Cambodia. Remote sensing is used to analyze land use maps of Siem Reap from 1993 to 2011. Results show that urban-built up area increased significantly which causes the forest land to reduce in the Siem Reap archaeological sites. In addition, Geographic Information System (GIS) is used to analyze urban growth in potential suitable sites. Geo-processing and logical functions are applied to detect and quantify the land use changes, especially urban changes. The percentage of urban area in each year is compared with the population density and road buffers by using Pearson correlation. It is shown that the increasing in urban area is related with population density and road network factors

The transition of urban growth in China : a case study of the Shenzhen Special Economic Zone

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1995.Includes bibliographical references (leaves 69-70).The Chinese government announced new economic reform policies in December of 1978. The announcement included an urban distribution policy that emphasized small cities and towns for rural urbanization as a means to achieve modernization in China. This distribution policy called for limited development in large metropolitan areas, selective development of only a few medium-sized cities, and more development in small cities and towns. Until now, the urbanization and development of small cities and towns have been the most dramatic changes; however, the issue is how a small city can grow in a proper way, fitting to its geographical, social and economical development requirements. Studying the urbanization and development of the Special Economic Zone (SEZ) in Shenzhen, one of the largest SEZ in China, provides a valuable model. The transformation of Shenzhen from a small town to a large commercial city involves much rural and urban development and construction. Good urban structure and urban growth pattern is essential in providing the necessary, orderly and functional physical environment. This thesis focuses on the evolution of a new kind of urban growth pattern for small cities and towns in China. It seeks to demonstrate that transition of urban growth pattern in Shenzhen is ideologically based in favor of socialistic setting in China. The specific goals of this study are to identify and describe the pattern of systematic urban growth in recent decades in Shenzhen SEZ, to explain the main factors and features in urban growth pattern for small cities and towns, and to evaluate recent policies of urban growth.by Mingzheng Gao.M.S

Predicting and simulating future land use pattern : a case study of Seremban district

As long as rapid urbanization which is a result of natural population growth and rural urban migration due to push and pull factors of social and economic conditions as well as the moving of urban populations from major city centres to urban fringe areas due to changing lifestyle which emphasized on spacious and more comfortable and environmentally friendly living environment continue to happen; towns and cities will continue to grow and expand to accommodate the growing and complex demand of the people. Experiences have shown that rapid and uncontrolled expansion of towns and cities has led to amongst others the deterioration in the quality of urban environment and sprawling of urban development onto prime agricultural and forest areas as well as cities starting to lose their identity. In order to avoid such phenomena continuing to happen, particularly in the Kuala Lumpur Conurbation Area, towns and cities need to be properly planned and managed so that their growth or expansion can be controlled and managed in a sustainable manner. One of the strategies adopted to curb sprawling development is through the delineation of urban growth or development limits (UGL). This means that the limit of towns and cities need to be studied and identified, so that urban development can be directed to areas that are identified and specified suitable for such development. One of the main tasks in the process of delineating UGL has been included as an important task in the preparation of development plans. With such policy a research study is now being carried out to develop a spatial modelling framework towards delineating UGL through the application and integration of spatial technologies and this will be a basis or framework for land use planners, managers and policy makers to formulate urban land use policies and monitor urban land use development. One of the main analysis involve in the process of performing this task is to understand past urban land development trend and to predict and identify future urban growth areas of the selected study area. This paper highlights the integration of statistical modeling technique via binary logistic regression analysis with GIS technology in understanding and predicting urban growth pattern and area as applied to District of Seremban, Negeri Sembilan. The result shows that urban land use pattern in the study area within the study period are significantly related to more than half of the predictors used in the analysis

Urban industrial relocation: The theory of edge cities

In recent years urban economists have focused their attention upon a 'newly recognized' phenomenon: edge cities. Such an urban growth pattern, although having its primary roots in the United States, can be an appropriate framework for examining European trends of urban industrial location. The objective of this study is to examine the relocation of firms from dominant industrial areas, for example, urban CBDs, to new locations at the urban outer boundaries. In this context, we develop in this paper a model based upon the theory of monopolistic competition ("Dixit and Stiglitz, 1977") that examines the economic relationships among firms at different locations. Such intra/inter relationships are examined from the point of view of complementarity. Complementarity in our case combines the two notions of firms' interaction with cumulative and reinforcing effects, and of coordination among firms in the local industrial organizations. Our interest in such a notion springs from the necessity to explain the spatial distribution of firms, particularly why firms in their location often choose to cluster. One of the explanations within the literature is that concentration in clusters is due to the need to share common infrastructures. However, this is just one of many possible explanations for this phenomenon. In our model, we will tackle this aspect of firm locations in clusters from the point of view of the elasticity of substitution. On the basis of the model we will formulate a policy framework regarding industrial suburbanization.