scholarly journals Urban Sprawl Analysis using GIS Application of Bhagur City

2021 ◽  
Vol 9 (9) ◽  
pp. 861-868
Author(s):  
Keyur Rai
Keyword(s):  
Remote Sensing ◽  
Urban Sprawl ◽  
Urban Growth ◽  
Growth Pattern ◽  
Agricultural Land ◽  
Urban Housing ◽  
Shannon’S Entropy ◽  
Shannon's Entropy ◽  
Landcover Change ◽  
The City

Abstract: The word “Urban Sprawl” means growth is more than the normal and the criteria that makes it different from urban growth is this excessive nature. Cities grow continuously and planned growth is achieved when there is a right balance between urban growth and urbanization. But when growth is above normal its pressure on the region and the city will face major new challenges. Urban sprawl is unrestricted growth in many urban housing areas, business development and roads in large parts of the world, without worrying about urban planning. Urban Sprawl are of three types i.e., linear growth, cluster growth and leapfrog growth. This paper inspect the use of Remote Sensing and GIS in mapping of urban sprawl (1990-2021) and landuse/ landcover change detection to detect changes that has been taken place between these periods in Bhagur city. The paper helps to study the software such as ArcGIS, used to classify between built up and agricultural land using temporal signatures obtained from satellite images. To numerically understand the growth pattern Shannon’s entropy is used. Shannon’s entropy is used as an index to quantify the degree of dispersion or concentration of built-up areas. Entropy approach shows concentration growth pattern in Bhagur city. Keywords: Urban Sprawl, GIS, Remote sensing, Land use/ Land cover, Shannon’s entropy.

scholarly journals Urban Sprawl Patterns and Processes in Delhi from 1977 to 2014 Based on Remote Sensing and Spatial Metrics Approaches

2016 ◽  
Vol 20 (14) ◽  
pp. 1-29 ◽  
Author(s):  
Madhavi Jain ◽  
A. P. Dimri ◽  
D. Niyogi
Keyword(s):  
Remote Sensing ◽  
Urban Sprawl ◽  
Shannon’S Entropy ◽  
Weighted Mean ◽  
Spatial Metrics ◽  
Shannon's Entropy ◽  
Urban Patterns ◽  
Patterns And Processes ◽  
The City ◽  
Compactness Index

Abstract Recent decades have witnessed rapid urbanization and urban population growth resulting in urban sprawl of cities. This paper analyzes the spatiotemporal dynamics of the urbanization process (using remote sensing and spatial metrics) that has occurred in Delhi, the capital city of India, which is divided into nine districts. The urban patterns and processes within the nine administrative districts of the city based on raw satellite data have been taken into consideration. Area, population, patch, edge, and shape metrics along with Pearson’s chi statistics and Shannon’s entropy have been calculated. Three types of urban patterns exist in the city: 1) highly sprawled districts, namely, West, North, North East, and East; 2) medium sprawled districts, namely, North West, South, and South West; and 3) least sprawled districts—Central and New Delhi. Relative entropy, which scales Shannon’s entropy values from 0 to 1, is calculated for the districts and time spans. Its values are 0.80, 0.92, and 0.50 from 1977 to 1993, 1993 to 2006, and 2006 to 2014, respectively, indicating a high degree of urban sprawl. Parametric and nonparametric correlation tests suggest the existence of associations between built-up density and population density, area-weighted mean patch fractal dimension (AWMPFD) and area-weighted mean shape index (AWMSI), compactness index and edge density, normalized compactness index and number of patches, and AWMPFD and built-up density.

scholarly journals Analyzing Urban Growth Pattern and Driving Factors Using Remote Sensing and GIS: A Case Study of Banepa Municipality, Nepal

2020 ◽  
Vol 20 (1) ◽  
pp. 9-18
Author(s):  
Rabina Twayana ◽  
Sijan Bhandari ◽  
Reshma Shrestha
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Growth ◽  
Growth Pattern ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Urban Land ◽  
Driving Factors ◽  
Rapid Urbanization ◽  
The Impact

Nepal is considered one of the rapidly urbanizing countries in south Asia. Most of the urbanization is dominated in large and medium cities i.e., metropolitan, sub-metropolitan, and municipalities. Remote Sensing and Geographic Information System (GIS) technologies in the sector of urban land governance are growing day by day due to their capability of mapping, analyzing, detecting changes, etc. The main aim of this paper is to analyze the urban growth pattern in Banepa Municipality during three decades (1992-2020) using freely available Landsat imageries and explore driving factors for change in the urban landscape using the AHP model. The Banepa municipality is taken as a study area as it is one of the growing urban municipalities in the context of Nepal. The supervised image classification was applied to classify the acquired satellite image data. The generated results from this study illustrate that urbanization is gradually increasing from 1992 to 2012 while, majority of the urban expansion happened during 2012-2020, and it is still growing rapidly along the major roads in a concentric pattern. This study also demonstrates the responsible driving factors for continuous urban growth during the study period. Analytical Hierarchy Process (AHP) was adopted to analyze the impact of drivers which reveals that, Internal migration (57%) is major drivers for change in urban dynamics whereas, commercialization (25%), population density (16%), and real estate business (5%) are other respective drivers for alteration of urban land inside the municipality. To prevent rapid urbanization in this municipality, the concerned authorities must take initiative for proper land use planning and its implementation on time. Recently, Nepal Government has endorsed Land Use Act 2019 for preventing the conversion of agricultural land into haphazard urban growth.

scholarly journals URBAN SPRAWL PATTERN AND EFFECTIVE FACTORS ON THEM: THE CASE OF URMIA CITY, IRAN

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Jamal MOHAMMADI ◽  
Asghar ZARABI ◽  
Omid MOBARAK
Keyword(s):  
Developing Countries ◽  
Urban Sprawl ◽  
Urban Growth ◽  
Large Scale ◽  
Agricultural Land ◽  
Land Uses ◽  
Effective Factors ◽  
Substitution Process ◽  
Urban Contexts ◽  
The City

Urban sprawl has become a remarkable characteristic of urban development worldwide in the last decades. Urban sprawl refers to the extent of urbanization, which is a global phenomenon mainly driven by population growth and large scale migration. In developing countries like Iran, urban sprawl is taking its toll on the natural resources at an alarming pace. The purpose of this paper is to study urban growth and effective factors on them in the city of Urmia, Iran. We used quantitive data of the study area from the period between 1989 and 2007, and population censuses of Urmia. To measure the model of urban growth, Holderness and Shannon’s entropy were employed. The Urmia case is interesting for several reasons: first, it is a case of very fast urban growth even for a developing country; second, it illustrates how the fastest rates of urban sprawl may correspond to middle size cities rather than to large centers. Third, it portrays a land substitution process in which agricultural land is not the primary provider of urban land which is relatively rare in urban contexts, and fourth, it also illustrates how urban sprawl may also hide important internal land uses such as the presence of agricultural plots within urban boundaries.

Urban Sprawl Monitoring Using Remote Sensing and GIS Techniques of the City Jaipur, India

2019 ◽  
pp. 1444-1456
Author(s):  
Pushpendra Singh Sisodia ◽  
Vivekananda Tiwari ◽  
Anil Kumar Dahiya
Keyword(s):  
Remote Sensing ◽  
Urban Sprawl ◽  
Rural Areas ◽  
Agricultural Land ◽  
Small Towns ◽  
Remote Sensing And Gis ◽  
Entropy Model ◽  
Metropolitan Cities ◽  
Employment Education ◽  
The City

The rapid increase in population of India forced people to migrate from rural areas and small towns to metropolitan cities for better employment, education, and, good lifestyle. Major cities of India were industrialized and required more work force in metropolitan cities, leading to uncoordinated and unplanned growth, often termed as urban sprawl. Urban sprawl destroyed the natural resources such as open green space, agricultural land, open water bodies and ground water. In this paper, an attempt has been made to monitor urban sprawl using Shannon's Entropy model, Remote Sensing, and GIS for city Jaipur, India. The changed entropy value during the years 1972–2013 proves more dispersed growth in the city. The built-up area of Jaipur has increased from 40 km2 in 1972 to 400 km2 in 2013. Land use percentage of urban settlement is doubled as compared to the urban population of Jaipur during 1972–2013. This study shows remarkable urban sprawl in fringe areas of Jaipur city in the last 41 years.

scholarly journals LAND USE AND LAND COVER CHANGES AND URBAN SPRAWL IN RIYADH, SAUDI ARABIA: AN ANALYSIS USING MULTI-TEMPORAL LANDSAT DATA AND SHANNON'S ENTROPY INDEX

2016 ◽  
Vol XLI-B8 ◽  
pp. 1017-1021 ◽  
Author(s):  
M. T. Rahman
Keyword(s):  
Saudi Arabia ◽  
Urban Sprawl ◽  
Urban Expansion ◽  
Shannon’S Entropy ◽  
Capital City ◽  
Landsat Data ◽  
Environmental Consequences ◽  
Shannon's Entropy ◽  
The Past ◽  
The City

The city of Riyadh, Saudi Arabia has experienced rapid population growth and urban expansion over the past several decades. Due to such growth, the capital city faces many short and long-term social and environmental consequences. In order to monitor and mitigate some of these consequences, it is essential to examine the past changes and historical growth of the city. It is also essential to measure its urban sprawl over the past few decades. The objective of this study is to fulfil these goals. It does so by first examining the historical growth of the city of Riyadh. To do so, Landsat data over the past two and half decades are classified using a combination of supervised and unsupervised classification techniques. Based on the classification results, the study then uses Shannon’s Entropy to measure the urban sprawl in the city. The results show that from 1990-2009, the urban built-up area of the city has increased by 90% in the western, south-eastern, and northern parts. The Shannon’s entropy values show that the city is dispersing towards the outskirts of the city. The results from this study will assist city planners and government officials to plan, reduce, and perhaps mitigate some of the social and environmental consequences and enable the growth of the city in a sustainable manner in the near future.

Urban Sprawl Monitoring Using Remote Sensing and GIS Techniques of the City Jaipur, India

2018 ◽  
pp. 716-728
Author(s):  
Pushpendra Singh Sisodia ◽  
Vivekananda Tiwari ◽  
Anil Kumar Dahiya
Keyword(s):  
Remote Sensing ◽  
Urban Sprawl ◽  
Rural Areas ◽  
Agricultural Land ◽  
Small Towns ◽  
Remote Sensing And Gis ◽  
Entropy Model ◽  
Metropolitan Cities ◽  
Employment Education ◽  
The City

The rapid increase in population of India forced people to migrate from rural areas and small towns to metropolitan cities for better employment, education, and, good lifestyle. Major cities of India were industrialized and required more work force in metropolitan cities, leading to uncoordinated and unplanned growth, often termed as urban sprawl. Urban sprawl destroyed the natural resources such as open green space, agricultural land, open water bodies and ground water. In this paper, an attempt has been made to monitor urban sprawl using Shannon's Entropy model, Remote Sensing, and GIS for city Jaipur, India. The changed entropy value during the years 1972–2013 proves more dispersed growth in the city. The built-up area of Jaipur has increased from 40 km2 in 1972 to 400 km2 in 2013. Land use percentage of urban settlement is doubled as compared to the urban population of Jaipur during 1972–2013. This study shows remarkable urban sprawl in fringe areas of Jaipur city in the last 41 years.

scholarly journals MANAGING URBAN SPRAWL USING REMOTE SENSING AND GIS

2020 ◽  
Vol XLII-3/W11 ◽  
pp. 59-66
Author(s):  
K. S. Krishnaveni ◽  
P. P. Anilkumar
Keyword(s):  
Remote Sensing ◽  
Urban Sprawl ◽  
Vegetation Index ◽  
City Planning ◽  
Integrated Approach ◽  
Developed Countries ◽  
Remote Sensing And Gis ◽  
Shannon’S Entropy ◽  
Shannon's Entropy ◽  
Gis Techniques

Abstract. Indian cities, like several other developing cities around the world, are urbanizing at an alarming rate. This unprecedented and uncontrolled urbanization may result in urban sprawl, which is characterized by low-density impervious surfaces, often clumsy, extends along the fringes of metropolitan areas with unbelievable pace, disperse, auto-dependent with environmentally and socially impacting characteristics. The ill-effects of urban sprawl in developing countries scenario is a bit complicated compared to that of developed countries because of uncontrolled population growth and haphazard urbanization. This paper attempts to investigate the capabilities of remote sensing and GIS techniques in understanding the urban sprawl phenomenon in a better way compared to time- consuming conventional methods. An overview of the enormous potential of remote sensing and GIS techniques in mapping and monitoring the Spatio-temporal patterns urban sprawl is dealt with here. The spatial pattern and dynamics of the urban sprawl of Kozhikode Metropolitan Area (KMA, Kerala, India) during the period from 1991 to 2018 using the integrated approach of remote sensing and GIS are attempted here. Index derived Built-up Index (IDBI) which is a thematic index-based index (combination of Normalized Difference Built-up Index (NDBI), Modified Normalized Difference Water Index (MNDWI) and Soil Adjusted Vegetation Index (SAVI)) is used for the rapid and automated extraction of built-up features from the time series satellite imageries. The extracted built-up areas of each year are then used for Shannon’s entropy calculations, which is a method for the quantification of urban sprawl. The results of IDBI and Shannon’s entropy analysis highlight the fact that there occurs an alarming increase in the built-up areal extent from 1991 to 2018. The urban planning authorities can make use of these techniques of built-up area extraction and urban sprawl analysis for effective city planning and sprawl control.

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