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The 'mega-cities' of the developing world are home to over 10 million people each and even smaller cities are experiencing unprecedented population surges. The problems surrounding this influx of people - slums, poverty, unemployment and lack of governance - have been well-documented. This book provides ways on how to deal with these challenges.

Land-use and land-cover (LULC) is an important component for sustainable natural resource management, and there are considerable impacts of the rapid anthropogenic LULC changes on environment, ecosystem services, and land surface processes. One of the significant adverse implications of the rapidly changing urban LULC is the increase in the Land Surface Temperature (LST) resulting in the urban heat island effect. In this study, we used a time series of Landsat satellite images from 1992 to 2020 in the Srinagar city of the Kashmir valley, North-western Himalaya, India to understand the linkages between LULC dynamics and LST, derived from the archived images using the Google Earth Engine (GEE). Furthermore, the relationship between LST, urban heat island (UHI), and biophysical indices, i.e., Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI), was also analysed. LULC change detection analysis from 1992 to 2020 revealed that the built-up area has increased significantly from 12% in 1992 to 40% in 2020, while the extent of water bodies has decreased from 6% in 1992 to 4% in 2020. The area under plantations has decreased from 26% in 1992 to 17% in 2020, and forests have decreased from 4 to 2% during the same period. Urban sprawl of Srinagar city has resulted in the depletion of natural land covers, modification of natural drainage, and loss of green and blue spaces over the past four decades. The study revealed that the maximum LST in the city has increased by 11°C between 1992 and 2020. During the same period of time, the minimum LST in the city has increased by 5°C, indicating the impact of urbanization on the city environment, which is reflected by the observed changes in various environmental indices. UHI impact in the city is quite evident with the maximum LST at the city centre having increased from 13.03°C in 1992 to 22.01°C in 2020. The findings shall serve as a vital source of knowledge for urban planners and decision-makers in developing sustainable urban environmental management strategies for Srinagar city.

Urbanization, particularly in peri-urban areas, often results in critically transforming the regional land use and land cover (LULC). The increased built-up in peri-urban areas affects the regional accessibility of residents of urban clusters to requisite amenities and severely affects the regional environment, as observed in the case of Jammu district situated in the foothills of the Indian Himalayas. The present study is aimed at assessing the rise of urban sprawls in Jammu district over the past two decades and how the urbanization has affected the lag in the number of amenities corresponding to the urban growth based on qualitative parameters. Further, a parameterization scheme is developed to assess the amenities quality. A comparison is made with Indore, a planned smart city, to assess the status of urbanization and residential quality based on an amenity index. The study also investigates the indifferences observed in some of the climate variables in the urban and sub-urban settings of the Jammu district. The investigation is conducted through a multi-ring buffer analysis approach utilizing the land use land cover (LULC) products based on Landsat 8/7 satellite imagery of 2002, 2013, and 2021. The indifferences in the settings are analyzed using MODIS aerosol optical depth (AOD) and land surface temperature (LST) products. The analysis leads to determination of critical urban parameters including the urban area, density, and growth rate, revealing significant urbanization at 25–27 km from the city center. Significant indifferences are observed in urban and sub-urban areas indicating higher rise in LST and AOD, particularly in the recent decade. These investigations provide critical information to urban and climate solution authorities for planning and management, particularly in critically endangered areas.

Rapid changes in land use and land cover (LULC) have ecological and environmental effects in metropolitan areas. Since the 1990s, Saudi Arabia’s cities have undergone tremendous urban growth, causing urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, etc. This study evaluates the variance and heterogeneity in land surface temperature (LST) because of LULC changes in Abha-Khamis Mushyet, Saudi Arabia, from 1990 to 2020. The research aims to determine the impact of urban biophysical parameters on the High–High (H–H) LST cluster using geospatial, statistical, and machine learning techniques. The support vector machine (SVM) was used to map LULC. The land surface temperature (LST) has been derived using the mono-window algorithm (MWA). The local indicator of spatial associations (LISA) model was implemented on the spatiotemporal LST maps to identify LST clusters. Also, the parallel coordinate plot (PCP) approach was employed to examine the relationship between LST clusters and urban biophysical variables as a proxy of LULC. LULC maps show that urban areas rose by > 330% between 1990 and 2020. Built-up areas had an 83.6% transitional probability between 1990 and 2020. In addition, vegetation and agricultural land have been transformed into built-up areas by 17.9% and 21.8% respectively between 1990 and 2020. Uneven LULC changes in terms of built-up areas lead to increased LST hotspots. High normalized difference built-up index (NDBI) was linked to LST hotspots but not normalized difference water index (NDWI) or normalized difference vegetation index (NDVI). This research could help policymakers develop mitigation strategies for urban heat islands.

For the past several decades, Tumkur has been one of the fastest-developing cities in Karnataka. Hence, an assessment concerning the identification of LULC mutations and their intensity and urban sprawl in Tumkur City has been employed using cutting-edge Geospatial techniques. In this study, multi-temporal satellite imagery such as Landsat 5 (2000), Resourcesat-1 (2005, 2009 & 2012), and Sentinel-2A (2015 & 2020) were utilized to monitor historical LULC changes, land transformation, direction of urban growth and sprawl. The outcome of the change detection demonstrates that between 2000 and 2020, the built-up area expanded significantly, from 24.94 km2 to 60.59 km2. Consequently, the land transformation matrix analysis shows that substantial modifications in LULC have occurred over the period, with a rise in built-up areas and plantations and a decline in agricultural land, water bodies, and scrubland. Further, urban expansion analysis using UEII (Urban Expansion Intensity Index) revealed that most of the area is in the fast-paced stage of urban expansion. Moreover, two well-known indices; the Annual Urban Spatial Expansion Index (AUSEI) and the Annual Built-up Change Index (ABCI), show a significant positive correlation between them (R2 = 0.69) justifying the increased urban growth in the study area. Whereas, built-up density and the Annual Urban Spatial Expansion Index (AUSEI) show a negative correlation (R2 = 0.55) indicating the presence of compactness of the core of the city. Apart from the above analysis, urban sprawl was effectively interpreted using zones formed using Shannon entropy; NNE, ESE, and SSW have high urban sprawl due to National Highways, growth of Industries, and infrastructure activities developed by the government. Further, the present study’s findings will contribute to understanding land use dynamics, urban sprawl, urban growth analysis, and future projections, as well as provide crucial information for decision-making and urban planning processes, to the urban planner to support acceptable land use management and guiding plan for appropriate growth of urban areas.

Reconstructing modernity assesses the character of approaches to rebuilding British cities during the decades after the Second World War. It explores the strategies of spatial governance that sought to restructure society and looks at the cast of characters who shaped these processes. It challenges traditional views of urban modernism and sheds new light on the importance of the immediate post-war for the trajectory of planned urban renewal in twentieth century. It examines plans and policies designed to produce and govern lived spaces- shopping centers, housing estates, parks, schools and homes - and shows how and why they succeeded or failed. It demonstrates how the material space of the city and how people used and experienced it was crucial in understanding historical change in urban contexts. The book is aimed at those interested in urban modernism, the use of space in town planning, the urban histories of post-war Britain and of social housing.

Most cities in the world suffer from excessive population and unplanned urban growth. The objective of the present study was to investigate the spatiotemporal changes of built-up areas and their growth in the proposed Greater Silchar City (GSC) (Assam, India). The obtained LANDSAT satellite data from 1991 to 2021 for the GSC have divided into non-built-up and built-up land use categories, and recode tools in Erdas Imagine 2014 software have been used to improve the accuracy of the output. The study area has been classified into 8 spatial directions and 11 concentric circles with radial distances of 1 km and resulted from intersected areas consisting of 60 gradient zones. The study used Shannon entropy model for detailed urban sprawl study of every nook and corner. FRAGSTATS v4.2 tools have been used to analyse landscape metrics in respective spatial directions. The built-up area growth of the city was 15.18 km 2 during the mentioned period. The landscape metrics and LU/LC results show the maximum built-up growth has taken place in South to South-West direction (3243.87 ha) and the area within a 2–3-km radius (221.85 ha) of the central business district, which is the periphery of the existing Silchar municipal limits. The entropy values indicated that the GSC has compacted infill growth form in the core area, while the dispersed urban sprawl trends followed with increasing distance from the city centre. Moreover, the research findings will provide a conceptual model for assessing urban growth trends for other cities as well.

Urban sprawl in context to transportation is a matter of serious concern. It creates unusual environmental challenges for an emerging economy like India, known for geographical spread, population, and use of fossil fuel-based automobiles on road. Indian automotive sector is often held responsible for the emission of greenhouse gasses causing serious environmental deterioration. Government at both central and state levels is dealing with this challenge in two ways-adding more infrastructure for public transport and encouraging electrical vehicles (EVs). Adoption of EVs for public mobility is eco-friendlier and economic. But it is observed that EV penetration in many pockets is not growing and is yet to mature for usage. Regardless of subsidies, it is not picking up as expected and needs to be investigated. Earlier research mainly focused on reporting barriers and did not guide EV penetration enablers. This study bridges the research gap and offers useful insights about EV penetration phenomenon and makes use of both qualitative and quantitative treatments. Accordingly, it models thirteen enablers, guides about tangling interrelationships using an interpretive structural modeling (ISM), and validates it using best worst method (BWM) approach. The study reports six key enablers, which are-developing high-capacity batteries with short recharge time, improving service support, framing promotive government policies, lowering electricity tariffs using sustainable and reliable sources, and reducing dependence on imported raw materials. These enablers need an urgent attention from the industries and researchers for successful EV penetration in Indian context. Authors hope the findings will be useful for other developing countries as well and will influence both researchers and practitioners.

There is a lack of research on urban sprawl in developing countries, particularly in Sub-Saharan Africa, undergoing significant demographic change. There is an urgent need to conduct more studies on African cities and investigate spatial variations in urban sprawl to fill a knowledge gap in Sub-Saharan Countries (SSC). There have been no studies of urban sprawl in the Somali capital of Mogadishu, a fragile metropolis struggling with the legacy of decades of civil war. This study has two main objectives: (i) to examine sprawl patterns in Mogadishu, Somalia; and (ii) to identify the drivers and impacts of urban sprawl in Mogadishu, Somalia. The study used spatiotemporal imagery from 2006, 2013, and 2021 to identify sprawl patterns. A quantitative method in the form of a cross-sectional survey with 265 participants was then used to identify the drivers and impacts of sprawl, which was then analysed using the structural equation model (SEM). The spatiotemporal analysis results showed sprawl patterns in nine districts and three settlements, mainly scattered and leapfrog patterns. The SEM discovered five significant drivers: low price of land and dwelling (LP), development of transportation infrastructure (DTI), rising income, security reasons, and low commute cost (LCC), in addition to eight significant impacts: less social interaction (LSI), agriculture land and natural habitat loss (AGL NHL), unsafe environment (USE), insufficient health and educational services (IHF IEF), high public services cost (HPSC), insufficient public transport (IPT), less physical activity (LPA), pollution (POL) and mental health issues (MH). Undoubtedly, the impacts found in the study proved that urban sprawl negatively impacted the residents and environment of Mogadishu, which will continue as the security situation in the city improves and more residents are attracted.

This study shows how remote sensing and Geographic Information System (GIS) can extract land surface temperature (LST) from the Landsat 5, 7, and 8 datasets. In this research, LST over Kharun’s lower catchment, located in Chhattisgarh, India, has been estimated. LST data from 2000, 2006, 2011, 2016, and 2021 were analyzed to see how the LULC pattern changed and how that changed LST. In 2000, the average temperature of the study region was 27.73 °C, whereas in 2021, it reached 33.47 °C. When the average temperature values for each class were determined, it was discovered that forest and adjacent waterbodies had the lowest values, with about 24.15 °C in 2000 and 27.65 °C in 2021, whereas urban regions had more variation in values, ranging from 30.15 °C in 2000 to 38.95 °C in 2021. There could be an increase in LST over time because cities are replacing the green cover. For example, there was a notable increase of 5.74 °C in the mean LST over the research area. The findings revealed that places with extensive urban sprawl had LST between 26 and 45°, which was greater than other natural land cover types, such as vegetation and waterbodies, which was between 24 and 35°. These findings support the suggested method’s effectiveness for retrieving LST from the Landsat 5, 7, and 8 thermal bands when combined with integrated GIS approaches. So, the goal of this study is to look at Land Use Change (LUC) and changes in LST using Landsat data and figure out how they are related to LST, the Normalized Difference Vegetation Index (NDVI), and the Normalized Built-up Index (NDBI), which are used as major components.