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INTRODUCTION
Urban sprawl, a prominent phenomenon in the development of cities worldwide, refers to the expansive growth of urban areas into previously rural or undeveloped land. This phenomenon has significant implications for land use, environmental sustainability, and socio-economic dynamics within regions experiencing rapid urbanization. Urban sprawl mapping plays a crucial role in understanding and managing this complex process, providing valuable insights for urban planners, policymakers, researchers, and stakeholders.
The primary objective of urban sprawl mapping is to delineate, analyze, and monitor the spatial extent and patterns of urban expansion over time. By mapping urban sprawl, analysts can identify areas where urban growth is occurring, measure the rate and direction of expansion, and assess the impact on surrounding natural and agricultural landscapes. This information is essential for making informed decisions about land use planning, infrastructure development, resource allocation, and environmental conservation efforts.
Urban sprawl mapping employs a variety of methodologies and technologies, primarily relying on remote sensing, geographic information systems (GIS), and spatial analysis techniques. Satellite imagery, aerial photography, and LiDAR (Light Detection and Ranging) data are commonly used to capture high-resolution images of urban areas and their surrounding environments. These data sources allow analysts to distinguish between different land cover types, such as built-up areas, vegetation, and water bodies, and to track changes in land use patterns over time.
GIS software plays a crucial role in processing and analyzing spatial data, enabling the creation of accurate maps and the visualization of urban sprawl trends. Advanced spatial analysis techniques, including image classification, change detection, and spatial modeling, help identify urban growth hotspots, quantify land cover changes, and predict future urban expansion scenarios.
Despite technological advancements, urban sprawl mapping faces several challenges. Data availability and quality can vary significantly between regions, particularly in developing countries with limited resources for data collection and analysis. Ensuring the accuracy and reliability of mapped data is essential for generating meaningful insights and supporting evidence-based decision-making.
Additionally, urban sprawl mapping must consider socio-economic factors, such as population growth, economic development, and infrastructure investments, which influence urban expansion patterns. Understanding these dynamics is crucial for developing sustainable urban planning strategies that balance economic growth with environmental conservation and social equity.
Looking ahead, the future of urban sprawl mapping will likely involve continued advancements in remote sensing technology, including higher spatial resolution sensors and improved data processing capabilities. Integration with emerging technologies, such as artificial intelligence (AI) and machine learning, holds promise for automating data analysis tasks and enhancing the accuracy and efficiency of urban sprawl detection and monitoring.
Moreover, addressing the challenges posed by urban sprawl requires interdisciplinary collaboration among urban planners, environmental scientists, policymakers, and community stakeholders. By leveraging spatial data and technology-driven insights, cities can better manage urban growth, mitigate environmental impacts, and promote sustainable development practices for the benefit of current and future generations.
In conclusion, urban sprawl mapping serves as a vital tool for understanding the complexities of urbanization and guiding efforts to create livable, resilient, and sustainable cities. As cities continue to expand and evolve, the role of urban sprawl mapping in shaping urban landscapes and fostering inclusive growth will remain indispensable in addressing the challenges of the 21st century.
Urban sprawl refers to the uncontrolled expansion of urban areas into the surrounding rural land, leading to low-density, car-dependent development. This phenomenon often results in various socio-economic and environmental issues, including increased traffic congestion, loss of agricultural lands, and higher infrastructure costs. Understanding and mapping urban sprawl is crucial for sustainable urban planning and development, as it helps policymakers and city planners make informed decisions to manage growth, protect natural resources, and improve the quality of life for residents.
Bangalore, officially known as Bengaluru, is the capital city of the Indian state of Karnataka. Over the past few decades, Bangalore has transformed from a laid-back, pensioners' paradise into a bustling metropolis, driven by the growth of the information technology (IT) industry. From 2017 to 2024, Bangalore has experienced significant urban expansion, fueled by population growth, economic development, and increased demand for housing and infrastructure. This rapid urbanization has led to sprawling development patterns that have reshaped the city's landscape.
The purpose of this report is to map and analyze the extent and impact of urban sprawl in Bangalore from 2017 to 2024. By examining satellite imagery, census data, and other relevant datasets, this report aims to identify the key areas affected by sprawl, understand the underlying drivers, and assess the socio-economic and environmental implications of this growth. The findings will provide valuable insights for urban planners, policymakers, and stakeholders to develop strategies for sustainable urban development and manage future growth effectively.
Study area:
Bangalore, or Bengaluru, is an excellent study area for mapping purposes due to its rapid urbanization and diverse urban landscape. Located at approximately 12.9716° N latitude and 77.5946° E longitude, the city serves as the capital of Karnataka, India. Bangalore's mix of residential, commercial, and industrial zones offers a comprehensive model for urban studies.
The city's varied topography, including plains, hills, and numerous lakes, presents a rich environment for geographical and environmental mapping. Bangalore's infrastructure, such as roads, public transport systems, and green spaces, provides valuable data for urban planning and smart city initiatives.
The result of Bangalore's urbanization is significant. Rapid growth has led to extensive development, contributing to challenges like traffic congestion, water scarcity, and pollution. These issues make Bangalore a critical case study for sustainable development and urban resilience, offering insights into managing urban growth while addressing environmental and infrastructural challenges.
Materials and Methods :-
Factors Considered Affecting Urban Sprawl:-
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Population Growth: Increases in population lead to greater demand for housing and services, often resulting in expansion into suburban and rural areas.
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Economic Factors: Economic growth and increased wealth can drive demand for larger homes and more space, pushing development outward from city centers.
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Housing Demand and Affordability: High housing costs in urban centers can drive people to seek more affordable housing in suburban or rural areas, contributing to sprawl.
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Transportation Infrastructure: The development of highways and roads can facilitate easier commuting from distant areas, encouraging suburban development.
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Land Use Policies and Zoning Regulations: Policies that favor low-density development, large lot sizes, and single-family homes can contribute to sprawl.
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Suburbanization Trends: Lifestyle preferences for suburban living, including larger homes and yards, can drive sprawl.
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Environmental Factors: Natural geography and environmental features, such as rivers, mountains, and forests, can shape the patterns of urban expansion.
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Political and Institutional Factors: Decisions made by local governments, planning authorities, and developers play a significant role in urban development patterns.
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Economic Opportunities: The location of job opportunities can influence where people choose to live, often contributing to sprawl if job centers are spread out.
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Technology and Telecommuting: Advances in technology and the ability to work remotely can reduce the need to live close to work, encouraging suburban and exurban living.
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Cultural and Social Factors: Cultural preferences for certain types of living environments, as well as social factors such as crime rates and school quality, can influence residential choices and contribute to sprawl.
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Land Availability and Cost: The availability of cheaper land on the periphery of urban areas can drive developers to build outward rather than focus on denser urban redevelopment.
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Infrastructure and Services: The availability and quality of infrastructure and services (such as water, sewer, electricity, and schools) in suburban areas can attract development.
Urban Sprawl Mapping:-
Composite Band: We first add the acquired band data of the years 2017 and 2024 on the map and then get the Composite Band image of both time periods
Extract by Mask: Then we try to get a clipped raster of Bangalore from 2017 and 2024 using the “Extract by Mask” tool.
Classification: After getting the clipped raster from both time periods, we start creating training samples for both time periods using ”Training Sample Manager” under the Classification Tool.
Image Classification Wizard: Then we go to the Image Classification Wizard to create a raster for both 2017 and 2024 in Bangalore. We do this by choosing the classification method as supervised and the classification type as Pixel Based. Then we add the existing training samples from both time periods to generate a raster based on the maximum likelihood.
Raster to Polygon: After creating classified rasters for both time periods, we will convert the rasters to polygons using the Geoprocessing tool called “Raster to Polygon.”
Dissolve: After creating a polygon raster, we need to use the Dissolve tool to get one grid code in both timelines.
Area and Class field: Then we open Dissolve Map’s Attribute Table on both time periods, then add a new field, namely, “area17” and "area24,” with “float” as its data type and “class17” and ”class24” with text as its data type. Then we calculate the geometry for the fields “area17” and ”area24” so that we can calculate the area of both time periods based on square kilometers.
Accuracy Assessment : -
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First, we add the classified raster image
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Then we create ACCURACY ASSESSMENT POINTS under SEGMENTATION AND CLASSIFICATION of SPATIAL ANALYST TOOL.
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After creating the points, we have to convert them into a KML file, which will later be opened in Google Earth to get the ground truth.
Confusion Matrix: After the Ground truthing is done for both timelines, we will compute the CONFUSION MATRIX under the SEGMENTATION and CLASSIFICATION toolbox for both timelines.
Intersect: Now, to know the difference between both time periods, we have to use a tool called Intersect.
Areachange and Class Change: Now we open the Attribute Table of the intersect map to check the area of both timelines. Next, we add a field called CLASS CHANGE and AREACHANGE . Now we calculate AREA CHANGE with geometry, with area units as square kilometers and also calculate the CLASS CHANGE with the expression,
Expression: !CLASS_17! + ‘-’ + !CLASS_2024!
Change Assessment: Now to calculate the change, we will use POLYGON TO RASTER from the conversion tools, where, the input feature is intersect map, value field can be AREACHANGE or CLASS CHANGE
Demographic Profile of the District for the year 2024:
Urban Map by the Karnataka Government:
Overall Analysis of Urban Change by 2024:
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Increased Urbanization and Population Growth:
Cities worldwide continue to experience significant population growth, with more people moving to urban areas in search of better opportunities. This trend is driven by economic opportunities, better living standards, and improved access to services and amenities. -
Expansion of Megacities:
The number of megacities (urban areas with populations exceeding 10 million) has increased. Cities like Lagos, Mumbai, and Beijing have seen substantial growth, leading to challenges in infrastructure, housing, and services. -
Smart Cities and Technology Integration:
The concept of smart cities has gained momentum, with increased integration of technology in urban planning and management. This includes the use of IoT (Internet of Things), AI, and data analytics to improve efficiency in transportation, energy use, waste management, and public safety. -
Sustainability and Green Initiatives:
There is a stronger focus on sustainability in urban development. Green buildings, renewable energy sources, urban green spaces, and sustainable public transportation systems have become more common. Cities are increasingly adopting policies to reduce carbon footprints and enhance environmental resilience. -
Urban Sprawl and Land Use Changes:
Despite efforts to promote sustainable urban development, urban sprawl remains an issue, particularly in developing countries. Unplanned expansion into peri-urban and rural areas continues, leading to challenges such as habitat loss, increased commuting times, and greater demand for infrastructure. -
Improved Public Transportation:
Many cities have invested in improving public transportation systems to reduce traffic congestion and pollution. This includes expanding metro, bus rapid transit (BRT), and cycling networks, making cities more accessible, and reducing reliance on private vehicles. -
Affordable Housing and Urban Inequality:
Affordable housing remains a critical issue. While some cities have made strides in providing low-cost housing options, urban inequality persists, with significant disparities in access to housing, services, and economic opportunities between different social and economic groups. -
Resilience to Climate Change:
Urban areas are increasingly focusing on building resilience to climate change impacts such as flooding, heatwaves, and rising sea levels. This includes implementing flood management systems, creating heat action plans, and developing resilient infrastructure. -
Impact of Remote Work:
The shift towards remote work, accelerated by the COVID-19 pandemic, has influenced urban change. There is a trend towards decentralization, with some people moving away from city centers to suburban or rural areas, leading to changes in housing demand and urban development patterns. -
Health and Well-Being:
The focus on health and well-being in urban planning has increased. This includes designing cities that promote active lifestyles, access to healthcare, and mental well-being through better urban design, green spaces, and recreational facilities.
Conclusion
By 2024, urban areas will have continued to evolve, driven by population growth, technological advancements, and a stronger emphasis on sustainability and resilience. While significant progress has been made in creating smarter, greener, and more livable cities, challenges such as urban sprawl, affordable housing, and urban inequality remain. Effective urban planning and policy-making are crucial to addressing these issues and ensuring sustainable and inclusive urban development.
Reference:
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"Urban sprawl analysis using multi-temporal satellite images" by Bhatta, B., Saraswati, S., and Bandyopadhyay, D. (2010)
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"Spatio-temporal analysis of urban sprawl and its contributions to climate and environment of megacity Mumbai, India" by D. Roy, S. Dwivedi, and A. Sharma (2020)
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"Monitoring urban sprawl and sustainable urban development using the integrated approach of remote sensing and GIS: A case study of Kolkata, India" by Sudhira, H.S., Ramachandra, T.V., and Jagadish, K.S. (2004)
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Census of India, 1981. “District Census Handbook – Dakshina Kannada District,” Series -9, Karnataka, Directorate of Census Operations.
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