Urban Growth Trends Research Articles

Monitoring Changes with Spatiotemporal Resolution in Land Surface Temperature (LST) Impact on Land Cover Around Al-Dora Refinery in Downtown Baghdad, Iraq

This study analyses the differences in temperature of the land surface across various land cover types and uses geospatial approaches to explore the changes that are taking place in the Dora refinery and its surrounding areas. Landsat 8 OLI/TIRS made use of Landsat imagery during the months of April and August in the years 2013 and 2023. ArcGIS 10.8 software was used to process the satellite images. The brightness temperature data from a satellite sensor was used to calculate the land surface temperature and the study's land cover classifications were created by applying supervised classification techniques.The aim of the study is to monitor the changes occurring in Dora refinery and its surrounding areas for periods of time 2013-2023 as a result of the influence of urban surface temperature , the growth and expansion that occurring in human activities and represented in the filtering and production of fossil energy and crude oil as well. The results of the investigation indicate an increase in the land surface temperature (LST) during the year 2023, in contrast to the year 2013, while we notice an increase in( NDVI ) in 2013 and a decrease in 2023, and a decrease in (NDBI) in 2013 and an increase in 2023. An inverse relationship was discovered between vegetated area and ( LST) between 2013 and 2023, whereas a positive relationship between (NDBI) and (LST) has been obtained suggesting an expanding surface urban heat island effect, as indicated by the correlation coefficients of statistical significance. It significantly affects how the land surface temperature varies. The main differences in the ways that land cover and use impact (LST) were also emphasized by this study during the whole duration of the inquiry, thus, methods for monitoring, examining, and assessing urban growth trends and their effects on land surface temperature can be achieved through the use of remote sensing and geographic information system tools.

A comprehensive analysis of Urban Ecosystem Services and their Valuation – a Case Study on Barasat City, India

Abstract The urban environment blends natural and artificial components, influenced by factors like culture, behavior, politics, economics, and social structures. Ecosystem services, beneficial to humans, are valued based on the cost of replication. Given urban expansion, studying urban ecosystems is increasingly crucial. This research assesses ecosystem service value (ESV) changes at a regional level from 1989 to 2020 in Barasat, West Bengal, within Kolkata’s urban area. The ESV variations are examined with the value coefficients and land use data. Barasat, an ancient town, is chosen as a case study. Land cover changes are analyzed using 1989, 2001, 2014, and 2020 imagery classified into six categories: built-up areas, water bodies, vegetation, bare soil, homesteads with plantations, and agricultural land. Nine ecosystem services are identified, with calculations made for each ecosystem’s surface area and total service value in 1989 and 2020. Barasat’s urban growth trend has transformed ecosystems into urban areas, reducing service values over time. This study underscores the importance of locally generated urban ecosystem services for city life and calls for attention in urban and environmental management practices.

The forms of neighborhood cohesion: From social contact to symbolic belonging in neoliberal Santiago de Chile

ABSTRACT The purpose of this article is to study the neighborhood social cohesion of the inhabitants of the Metropolitan Area of Santiago, Chile (MAS), considering its recent urban transformations driven by neoliberal urban policies. Using multilevel logistic regressions based on a survey of 401 inhabitants, we identify a symbolic cohesion among residents with higher incomes, which combines a high sense of belonging with low neighborhood sociability, and a relational cohesion among the vulnerable population, based on a stronger neighborhood sociability and a low sense of belonging. These results show an influence of the geographical divide between high and low income inhabitants, accentuated by the socio-spatial segregation of the metropolis in the past decades, in addition to identifying a certain relationship between neighborhood cohesion and two of its major neoliberal trends of urban growth: the densification of its center and the development of peripheral social housing. We argue that a deeper understanding of the distinction between relational and symbolic forms of neighborhood social cohesion is relevant because, as well as allowing us to analyze the MAS case by addressing its current complexity, it provides an opportunity to discuss the way in which the concept is defined and conceived in recent literature.

Statistical-based spatial analysis on urban water management under changing environments: a case study of Hawassa, Ethiopia

Hawassa characterizes a typical developing city in Ethiopia, owning to rapid urban growth and demographic trends. The combined effect of climate change and urban expansion is increasing the challenge to the environment and the services it provides. Relating changing environments with urban water management (UWM) is required to build resilience in the urban environment. This research analyzed local climate change and urban growth and linked it to UWM. The historical period 1990–2021 of daily rainfall, temperature variables, four satellite imageries, and DEM were analyzed. Changes in rainfall (annual and daily maximum) and temperature (maximum and minimum) trends are detected and projected to 2051 using a statistical-based model. With geospatial techniques sub-watersheds are delineated, and the urban cover change is quantified. The trend detection result implies an upward trend of annual and daily maximum rainfalls however a significance is insufficient (p > 0.05) to associate it with climate change during the study period. Maximum and minimum temperatures change indicate a positive and significant trend. The forecasting result suggests an increment of both temperatures (0.5 °C–1.5 °C) to the projected period compared to historical scenario. The land cover analysis results show the built-up area changed from 11.6 km2 (7.2%) to 42.5 km2 (26.5%) during the historical period, where the rate varies spatially. The surface runoff increased by 30.7% in the urban watersheds. With a growth rate of 8.9% built-up, the urban area will cover 73.6 km2 (45.9%) for the predicted period. The research finding justifies the potential to reorganize the relationship between the spatial effect of climate change and urban growth on UWM. Considering distinct characteristics of urban watershed, exposure to flooding risk, access to water demand and resilient to climate change have spatial variation. Thus, a local-specific planning approach will support effective UWM and climate adaptation for sustainable city development.

The impact of land expropriation on changing livelihoods: The case of displaced peri-urban farmers in Kon and Gashena towns, Ethiopia

The research examines how urban growth and land expropriation have affected farming communities in the towns of Gashena and Kon over the past twenty years. The study used a case study approach, utilizing methods such as open-ended interview checklists, structured questionnaires, and focus group discussions. It reveals a significant reduction in available farmland due to horizontal urban growth, leading to the displacement of numerous farm holdings and disruption of agricultural practices. By analyzing municipal data and employing simple regression modeling, the research anticipates further expansion, underscoring persistent urban growth trends. Economic displacement emerges as a pressing issue, as farmers grapple with finding alternative sources of income, exacerbating food insecurity within affected communities. Moreover, the study unveils diverse impacts on displaced farm holdings, including shifts away from agriculture in livelihoods and substantial income losses. The loss of land assets poses a threat to agricultural productivity and community sustainability. Despite assurances from municipal authorities, the lack of support, guidance, and training contributes to community dissatisfaction. The research underscores the interconnectedness of land, food, culture, and identity, emphasizing the necessity for comprehensive strategies to address the multifaceted impacts of land expropriation. Recommendations include policy interventions, support for transitioning farmers, promotion of sustainable land use practices, and fulfillment of promises regarding support and infrastructure development. Providing training and guidance services for displaced individuals is also crucial for addressing the challenges of land expropriation effectively.

Temporal analysis of land degradation and urban expansion in central Yunnan Province using remote sensing for supporting sustainable development goals 11/15

Monitoring land degradation and urban expansion is crucial for sustainable development and environmental stewardship. It helps protect arable land, ensure food security, mitigate climate change impacts, and guide urban growth while minimizing environmental harm, thus advancing the Sustainable Development Goals (SDG).This study focuses on the application of the Trends.Earth tool, following the UN-SDG indicator framework, to assess land changes, urban expansion, and drought vulnerability in the central east region of Yunnan Province, China, during the period 2000 to 2020.The analysis reveals significant trends in land transformation and urban growth. Notably, the central Yunnan region demonstrated a positive trajectory, with 69.58% experiencing land improvement and 8.55% undergoing degradation. Urban areas expanded dramatically, with Kunming City growing threefold from 2000 to 2015 raising concerns about sustainable land management. Drought vulnerability assessments unveil the temporal variation and the extent of impact on the population.This research underscores the importance of remote sensing and its role in achieving the SDGs. By providing a comprehensive assessment of land dynamics, urbanization patterns, and environmental vulnerability. As Yunnan Province grapples with both developmental aspirations and ecological conservation imperatives, this study serves as a foundation for informed decision-making to balance economic growth and environmental protection.

ROADS TO RENEWAL: INVESTIGATING THE SOCIO-ECONOMIC INFLUENCE OF THE YAMUNA EXPRESSWAY ON ALIGARH-JEWAR REGION

Infrastructure projects often claim to transform the communities through which they cross. This study investigates the social and economic implications of the Yamuna Expressway in Indias Aligarh-Jewar region. Through the utilization of a combination of methods, the research examines the impact of this extensive infrastructure project on local job opportunities, trends in urban growth, and alterations in peoples means of living. The highway has greatly decreased commute times and has facilitated economic and social changes throughout the area. The results indicate that despite significant economic growth and infrastructure improvements, issues like environmental damage and social inequities also emerge. This study adds to the knowledge of how transport infrastructure affects regional development, providing important information for decision-makers and those involved in similar projects. It also examines the role of policy in managing these outcomes, emphasizing the need for sustainable practices and inclusive growth strategies. This paper contributes to understanding the dualistic impact of transport infrastructure on regional development, offering insights that are vital for policymakers and stakeholders engaged in similar infrastructure projects. KEYWORDS: Regional development, social dynamics, urbanization effects, socio-economic impact, environmental implications, government policies, road development, infrastructure development

Investigating the Key Aspects of a Smart City through Topic Modeling and Thematic Analysis

In recent years, the emergence of the smart city concept has garnered attention as a promising innovation aimed at addressing the multifactorial challenges arising from the concurrent trends of urban population growth and the climate crisis. In this study, we delve into the multifaceted dimensions of the smart city paradigm to unveil its underlying structure, employing a combination of quantitative and qualitative techniques. To achieve this, we collected textual data from three sources: scientific publication abstracts, news blog posts, and social media entries. For the analysis of this textual data, we introduce an innovative semi-automated methodology that integrates topic modeling and thematic analysis. Our findings highlight the intricate nature of the smart city domain, which necessitates examination from three perspectives: applications, technology, and socio-economic perspective. Through our analysis, we identified ten distinct aspects of the smart city paradigm, encompassing mobility, energy, infrastructure, environment, IoT, data, business, planning and administration, security, and people. When comparing the outcomes across the three diverse datasets, we noted a relative lack of attention within the scientific community towards certain aspects, notably in the realm of business, as well as themes relevant to citizens’ everyday lives, such as food, shopping, and green spaces. This work reveals the underlying thematic structure of the smart city concept to help researchers, practitioners, and public administrators participate effectively in smart city transformation initiatives. Furthermore, it introduces a novel data-driven method for conducting thematic analysis on large text datasets.

Urban Growth Monitoring and Prediction Using Remote Sensing Urban Monitoring Indices Approach and Integrating CA-Markov Model: A Case Study of Lagos City, Nigeria

As one of the swiftly advancing megacities globally, Lagos faces significant challenges in managing its urban expansion. Mainly, this study focuses on monitoring and predicting urban growth using a comprehensive approach incorporating Global Land 30 (GL30), satellite-based nighttime light observations, and built-up and population density data. The application of remote sensing techniques, combined with utilizing the GL30 dataset, provides an effective means to monitor and predict urban growth trends and patterns. The major patterns occurred from 2000 to 2020, including increased cultivated land; reductions in grasslands, shrublands, and wetlands; and major urbanization. Predictive models indicate that urbanization will continue. Furthermore, employing the Cellular Automata (CA) Markov model in land-use and land-cover (LULC) change prediction. The findings revealed significant changes in LULC over the two decades. Particularly, the percentage of artificial terrain increased from 17.016% to 25.208%, and the area under cultivation increased significantly, rising from 46,771 km2 (1.238%) in 2000 to 75,283 km2 (1.993%) in 2020. Grasslands fell from 7.839% to 1.875%, while forest cover somewhat increased, climbing from 39.319% to 43.081%. Additionally, marshes fell from 9.788% to 5.646%, while shrublands decreased from 4.421% to 2.640%. Surprisingly, bare ground decreased sharply from 0.677% to 0.003%. To forecast future LULC changes, the study also used a Markov Chain Transition Matrix. According to the data, there is a 3.54% chance that agricultural land will become urban, converting it from being used for agriculture to urban development. On the other hand, just 1.05% of forested regions were likely to become municipal areas. This study offers foundations for the upcoming research to enhance urban growth models and sustainability strategies in the face of rising urbanization and environmental concerns in the region, as well as laying the groundwork for informed decision-making in the region.

Spatio-temporal analysis of land use land cover change and its impact on land surface temperature of Sialkot City, Pakistan

The dynamic interplay between urbanization and its impacts on climate is a subject of recent concern, particularly in rapidly urbanizing cities of Pakistan. This research investigated the spatio-temporal effects of urban growth in terms of Land Use Land Cover changes on the thermal environment (Land Surface Temperature) of the Sialkot city, Pakistan using satellite data spanning four distinct time periods (1989, 2000, 2009 and 2020) and predicted changes for year 2030 by employing Cellular Automata Markov Chain Model. Satellite imagery (Landsat 5, 7 and 8) was processed, and maximum likelihood supervised classification was done to generate LULC maps for each of the aforementioned years. In addition to LULC classification, thermal bands of satellite data (for summer and winter) were processed to compute Land Surface Temperature (LST) of the city. The prediction of LULC changes and LST was done for year 2030 using Cellular Automata Markov Chain Model. The accuracy of classified and prediction maps was checked using Kappa Index. The LULC analysis revealed 4.14% increase in the built-up area and 3.43% decrease in vegetation cover of the city during 1989 to 2020. Both land covers are expected to change in the future (year 2030) by + 1.31% (built-up) and − 1.1% (vegetation). Furthermore, a declining trend in the barren land and water bodies was also observed over time. These LULC changes were found affecting the LST of study area. The transformation of vegetation cover into built-up area resulted in an increase in LST over time. A notable rise of 4.5 °C (summer) and 5.7 °C (winter) in the mean LST of Sialkot was observed during 1989 to 2020 and further increases are anticipated in year 2030. This study calls for attention of the policy makers to reduce human impact on the local climate of the city. The study will also help city developers in analyzing the urban population growth trend, finding suitable location to built new infrastructure by governmental authorities and how the rising temperature can affect energy demand and agriculture production of the city in future.

Examining the informal urban growth trends in a Port city

Rapid urban developmental growth is a heated debate worldwide due to environmental challenges. This research has examined the spatiotemporal trend of informal built-up growth in Karachi city. Using a geo-information system, the past twenty years (2000–2020) trends of informal built-up growth are examined. For attaining the research objectives, geo-referenced high-resolution maps and satellite images are used for accuracy based spatial data. Karachi is divided into five different land use and land cover (LULC): formal built-up, informal built-up, vacant, water bodies, and green spaces. Spatial data of informal built-up growth change of five different years, 2000, 2005, 2010, 2015, and 2020 are generated through acquired maps digitization using ArcMap. Subsequently, the gains and transfers of Karachi's informal built-up growth based on five years 2000–2005, 2005–2010, 2010–2015, and 2015–2020 are analyzed using the Land Change Modeler (LCM) in IDRISI software. Also, land use land cover changes (LULCC) are predicted for the next 40 years (2020–2060) using the integrated Cellular Automata Markov (CA-Markov) simulation model in IDRISI. The results revealed that Karachi's built-up is expanding rapidly. Land conversion into the informal built-up area is alarming, as it has changed from 144.31 km2 to 217.19 km2 with 72.88 km2 in the past twenty years (2000–2020) and has occupied green and agricultural land. Most informal built-up areas have transitioned from vacant (71.01 km2) land use land cover (LULC). The informal built-up area could expand from 217.19 km2 to 317.63 km2, with about 100.44 km2 up to 2060. The planned and unplanned development will be towards the city's East (E) direction and will convert and ruin agriculture and vacant land. The present study provides suggestions to urban planners, administrative authorities, and policymakers to control informal growth and achieve sustainable development goals in developing countries.

Spatio-Temporal Analysis on Land Use/Land Cover Change in Banda Aceh: A Preliminary Study of Disaster Resilience

The devastating tsunami that struck Banda Aceh resulted in profound destruction to both its built environment and natural areas. The city’s urban infrastructure suffered extensive damage, with essential zone being severely affected. Despite these challenges, the population of this tsunami-prone city has continued to increase steadily over time. This research examines the land use/land cover (LULC) in Banda Aceh following the 2004 Indian Ocean Tsunami through spatio-temporal analysis, with a particular focus on investigating urban growth trends through the examination of built-up areas. The study seeks to discern the evolving patterns of land use and land cover transitions over this period, shedding light on the transformative processes associated with urbanization and its consequent impact on the landscape. The insights obtained from this research can inform urban planners, policymakers, and disaster management authorities in devising effective strategies for urban growth in coastal front cities that vulnerable to tsunami.

An assessment of spatial pattern of urban sprawl in JOS metropolis of plateau state, Nigeria: Using remote sensing and GIS techniques

In Jos metropolis, urban sprawl debate has closely paralleled on urban growth trends over the past few decades. These studies indicate that it is the pattern, types, density and rate of new urban growth that creates the appearance of sprawl. Population dynamics are often cited as a driving force behind urban sprawl. This paper uses Geographic Information Systems (GIS) mapping and land cover change analysis, neighbourhood statistics, cross change detection techniques, field work on Urban sprawl areas in Jos metropolis. The paper also highlights the characteristics, types, rates, pattern and density of sprawl to examine the spatial pattern of sprawl in Jos North and Jos South. Linear sprawl pattern can only be visually seen by the road, the roads in Jos play important role in linear pattern of urban sprawl formation through road data, it helped to visualize clearly the areas of linear sprawl in Jos metropolis. An example can be visually seen in Naraguta area, part of a large high residential development of Jos north. Cluster types of urban sprawl settlement development in Jos metropolis. From the map, it shows that cluster types of sprawls in study area are found in the core city of Jos metropolis like Jos city and Bukuru in the study area. Cluster type of urban sprawl also appeared to grow out of what was once a leapfrog pattern of development in some area in the study area. Leapfrog patterns of urban sprawl appeared to be somewhat disconnected from other areas of existing developed settlement land. Leapfrog types of urban sprawl in Jos metropolis can be seen in Kuru North, Dan Miangu, Barakin Kuru and Kuru Hills.After the map of the densities urban sprawl for new growth areas has been created. The study reveals that settlement area has increase from 125.45 to 208.16 sq.km between 2002-2022 in twenty years period. It also revealed that water bodies have also drastically reduced by 3.33 sq.km and open space land use contributed about 127.57 km2 land converted to settlement within the time under study. Further analysis reveals that the urban settlement land of the area increased approximately 82.71 km2 in the twenty years’ time period of the study (2002 to 2022). Next, the patterns of urban expansions were analyzed by using mapping capabilities within the GIS and neighborhood statistics in order to show the density and connectivity of patches of new growth. Based on the density and connectivity of new growth areas, the patterns of growth were classified as: linear along highways, cluster, and leapfrog. The threshold densities are; 0 to 2000 as 30-meter pixels per km2 for low density, 2000 to 25000 for medium density, and 25000 to 130000 for high density. The results indicate that Jos metropolis did experience an increase in urban growth from 2002 to 2022 and that urban growth in the study area can be classified as urban sprawl. The density of new development is more in Jos North, but the pattern and character with which development has occurred in Jos North is synonymous with sprawl in Jos South. the type, rate and patterns of urban expansions were analyzed by using mapping capabilities within the GIS and neighborhood statistics in order to show the density and connectivity of patches of new growth in the study area.

Urban growth trend analysis of proposed Greater Silchar City, India, using landscape metrics and Shannon entropy model

Urban growth trend analysis of proposed Greater Silchar City, India, using landscape metrics and Shannon entropy model

Measurement of Sprawl Effect Based on Urban Growth Trends and Prediction in Kedungkandang District, Malang City

Urban development generally produces a specific type of urban growth that can be identified by looking at the pattern formed by the growth of occuring built-up area. Urban growth in some theories has three types of growth, namely infill, leapfrog and sprawl. Each type has logical consequences for environmental sustainability, such as leapfrog and sprawl which can lead to inefficient use of resources. This study focuses on measuring sprawl intensity based on urban growth trends or built-up area in Kedungkandang District from 2012 to 2020 and based on the results of urban growth or built-up area predictions from 2021 to 2036. Urban growth predictions are carried out using the Cellular Automata method, that there will be 975 hectares built-up land growth from 2016 to 2036. Then to measure the intensity of sprawl as a result of urban growth, the Shannon’s Entropy method is used with the result that the urban growth process in Kedungkandang District within 24 years tends to decrease in sprawl intensity by 50%. The results of this study are expected to provide insight and future views for the Government in dealing with urban growth in Kedungkandang District in the future.

Urban growth, changing relationship between biophysical factors and surface thermal characteristics: A geospatial analysis of Agra city, India

The kind of urbanization occurred in the last few decades has caused a massive reduction of urban green space raising the land surface temperature, drastic land use and land cover changes, and hampering environmental sustainability in Agra city. Examining urban growth trends and its significant impacts on surface and vegetation cover of Agra helps in assessing nature of spatial development process. The present study examines urban growth, bio-physical factors and surface thermal characteristics in the city. Study uses multiple geospatial techniques to analyse changes. To obtain spatio-temporal landscape dynamics multi-temporal Landsat TM/OLI satellite images were used for years 1991, 2001, 2011 and 2021 to classify LULC classes using maximum likelihood supervised classification algorithm. Based on the spatial drivers and LULC of 2001 and 2011; multi perception based artificial neural network model is applied to predict the urban areas in 2031. Study reports that the greatest loss was found for vegetation cover (VC); a total of 17.89 sq. km. (13.06%) green space lost during the study periods (1991–2021). A remarkable increased in urban area was noticed at a rate of 11.20% during 1991–2001 and 7.97% during 2001–2011. The study has much to offer to urban and environmental planning and sustainable urbanization.

TYPOLOGY OF PUBLIC OPEN SPACE IN PERI-URBAN UNPLANNED SETTLEMENT. CASE STUDY: KAMPONG OF KALIPATEN, TANGERANG, INDONESIA

The growth of the Tangerang area reflects the urban growth trend which leads to a wider growth pattern to the area around the Major City. One indication of the growth is the character changed of settlements that previously had a rural character into urban character, especially in building density. The growth in the number of houses as residences has resulted in changes in the type of open space and its use. Aim: This research aims to identify the type and character of open spaces in unplanned settlements that are growth very quickly because of the area directly adjacent to the Gading Serpong new town. Methodology and Results: The method used is descriptive qualitative. The type of open space is measured by the criteria of location, form, function, and land status. The character of open space is studied by connecting the existence of open space with the social interaction of the residents of the settlement. Conclusion, significance, and impact of study: The findings that have been obtained from this research are that open spaces have five types with a very prominent spatial character, namely open spaces that arise through natural social processes, are not specially designed and have a very important role in bonding the social interaction of their inhabitants.

Spatiotemporal Monitoring of Urban Sprawl in a Coastal City Using GIS-Based Markov Chain and Artificial Neural Network (ANN)

Over the last two decades, globally coastal areas have urbanized rapidly due to various socioeconomic and demographic driving forces. However, urban expansion in towns and cities of the developing world has been characterized by entangled structures and trends exacerbating numerous negative consequences such as pollution, ecological degradation, loss of agricultural land and green areas, and deprived settlements. Substantially, spatial simulation of urban growth and their consequences on coastal areas particularly in Egypt is still very rare. Geospatial modelling coastal urban growth is crucial and has enormous potential for coastal land use transformation and urban sustainability. The key aim of this study was to analyze spatiotemporal changes (2010–2020) and simulate future dynamics (2030 to 2050) of land use/land cover (LULC) in Alexandria Governorate, Egypt. Artificial Neural Network–Multiple Layer Perceptron (ANN-MLP) and Markov Chain techniques were employed within the GIS platform to assess processes of land transitions and predict urban growth trends, patterns and dimensions. The forecasting process was based on three maps of LULC derived from classified Landsat images of 2000, 2010 and 2020. In addition, topographical, demographic, accessibility, proximity factors were generated and developed in the form of raster spatial parameters of urbanization driving forces. The findings revealed that the observed expansion of the built-up area during one decade (2010–2020) was 12,477.51 ha, with a decline in agricultural area (7440.39 ha) and bare land (4904.91 ha). The projected change was forecasted to be 71,544 ha by 2030 and 81,983 ha in 2040 with a total of 35,998 ha increase in the built-up area and residential expansion by 2050. Despite this expected pattern of rapid changes, urban growth will be shaped by the key drivers of proximity to coastline and agricultural land transformation. The analysis indicates that the vertical urban growth will be most likely dominant along the coastal zone due to the lack of vacant lands, whereas the horizontal urban expansion will primarily take place towards the east-northeastern and south-southeastern directions of the city. The present work provides a holistic framework for establishing initial coastal land use plans not only for planners and urban administrators in Alexandria but also for policymakers and coastal municipalities in developing nations.

URBAN GROWTH AND SOCIO-ECONOMIC DEVELOPMENT IN GUJRANWALA, PAKISTAN: A GEOGRAPHICAL ANALYSIS

Cities all over the world, particularly in developing countries like Pakistan, areexperiencing rapid urban growth and changing socio-economic profile. Present study was conducted toinvestigate the trends of urban growth and socio-economic development in Gujranwala, the prominentindustrial city, 5th largest city of the Punjab and 7th amongst the big populous cities of Pakistan. Bymaking comparison of its structure with overall socio-economic structure of the Punjab Province,selected indicators were considered viz. population size, housing facilities and urban growth patterns.Data was obtained from various sources and efforts were made in order to realize the behavior of urbangrowth and socio-economic development. Results revealed that city had better place regarding itseducational, health, housing and human development scenarios. But noticeably, a small proportion ofpopulation could have access to safe drinking water, sanitation etc. The urban growth patternssuggested the increasing urban population due to migration and natural increase of population, thoughoverall growth rate was declining. Resultantly, city was spatially expanding in north, west and eastdirections since 1947 to present.

Framework and Use Case for a Web-Based Interactive Analysis Tool to Investigate Urban Expansion and Sustainable Development Goal Indicators

Land cover changes have been mapped for decades to investigate urban expansion patterns. Under the UN Sustainable Development Goals (SDGs), several indices are employed to interpret urban growth trends quantitatively and comprehensively. However, landowners and the interested public usually have limited insights into these types of information as access to data and software is limited. Static maps and the inability to access special file formats increase the difficulty of viewing and investigating the data. This contribution presents a dedicated, interactive, web-based analysis tool for integrating land cover and land use maps as well as urban expansion indices. The tool’s concept, development and functionality are presented, and its general design is reviewed based on an actual implementation case. The setup allows integrating land use and land cover (LULC) change data alongside SDG indicators. The tool’s design aims to enhance user accessibility to information on urban expansion indices and LULC. We demonstrate that such a tool can be used to help disseminate results and to improve communication with the public in the context of other use cases.