Analysis of urban sprawl at mega city Cairo, Egypt using multisensoral remote sensing data, landscape metrics and gradient analysis

This paper is intended to highlight the capabilities of synergistic usage of remote sensing, landscape metrics and gradient analysis. We aim to improve the understanding of spatial characteristics and effects of urbanization on city level. Multisensoral and multitemporal remotely sensed data sets from the Landsat and TerraSAR-X sensor enable monitoring a long time period with area-wide information on the spatial urban expansion over time. Landscape metrics aim to quantify patterns on urban footprint level complemented by gradient analysis giving insight into the spatial developing of spatial parameters from the urban center to the periphery. The results paint a characteristic picture of the emerging spatial urban patterns at mega city Cairo, Egypt since the 1970s

Dynamics of Land Use and Land Cover Changes in Harare, Zimbabwe: A Case Study on the Linkage between Drivers and the Axis of Urban Expansion

With increasing population growth, the Harare Metropolitan Province has experienced accelerated land use and land cover (LULC) changes, influencing the city’s growth. This study aims to assess spatiotemporal urban LULC changes, the axis, and patterns of growth as well as drivers influencing urban growth over the past three decades in the Harare Metropolitan Province. The analysis was based on remotely sensed Landsat Thematic Mapper and Operational Land Imager data from 1984–2018, GIS application, and binary logistic regression. Supervised image classification using support vector machines was performed on Landsat 5 TM and Landsat 8 OLI data combined with the soil adjusted vegetation index, enhanced built-up and bareness index and modified difference water index. Statistical modelling was performed using binary logistic regression to identify the influence of the slope and the distance proximity characters as independent variables on urban growth. The overall mapping accuracy for all time periods was over 85%. Built-up areas extended from 279.5 km2 (1984) to 445 km2 (2018) with high-density residential areas growing dramatically from 51.2 km2 (1984) to 218.4 km2 (2018). The results suggest that urban growth was influenced mainly by the presence and density of road networks

The global issue 'mega-urbanization': An unsolvable challenge for stakeholders, researchers and residents?

This study aims at discussing the complex, multi-dimensional issue of the global phenomenon of urbanization. Based on a theoretical review and discussion on the situation of cities, the causes, dimensions and consequences of urban growth the idea is to raise the main questions for future activities to meet this challenge. For it a pragmatic and holistic framework is proposed to systematize the manifold approaches and to stimulate discussions on this issue addressing inter- and transdisciplinary thinking

Geospatial approach for assessing spatiotemporal dynamics of urban green space distribution among neighbourhoods: A demonstration in Mumbai

Green spaces are an integral part of urban landscape and offer numerous benefits related to quality of urban life. However, due to various factors, the distribution of green spaces among city neighbourhoods is often skewed. Hence, urban planners require effective tools to routinely map and monitor the greening/ un-greening phenomena among the neighbourhoods. This study caters to this need by adopting a geospatial green space distribution assessment approach that encompasses green space quantity, quality and accessibility aspects. The green space distribution indicators were derived from remote sensing data, which facilitates cost-effective green space assessments at desired time scales. In this study, the approach is demonstrated in Mumbai, a typical city in a developing country undergoing urbanization transition accompanied by stark environmental challenges. The study results revealed that the green spaces in Mumbai had generally diminished, fragmented and disaggregated between 2001 and 2011. However, the level of degeneration of green spaces was found to vary significantly among the neighbourhoods. The results also unveiled that the verdant spaces in the city's western suburbs had experienced the worst degradation during the study period. These results would aid Mumbai's planners in formulating local greening strategies in a cost-effective manner. Further, the study has wider implications for green space planning, especially in the understudied, fast-urbanizing developing countries

Conceptualizing Spatial Heterogeneity of Urban Composition Impacts on Precipitation Within Tropics

Urban composition has exacerbated precipitation patterns. Rapid urbanization with dynamic composition and anthropogenic activities lead to the change of physical environment, especially land-use and land cover which subsequently magnifies the environmental effects such as flash floods, extreme lightning, and landslides. Due to extreme and elevated temperature trends with exacerbated rainfall patterns, these environmental effects become major issues in tropics. Albeit several studies pointed out that rapid urbanization induced precipitation, studies about the heterogeneity of urban composition on precipitation variables are still limited. Thus, this paper review studies about precipitation pattern in relation to the heterogeneity of urban composition that successfully integrates geographical information system (GIS) and remote sensing techniques to enhance the understanding of interactions between precipitation patterns against heterogeneity of urban composition. This article also addressed the current state of uncertainties and scarcity of data concerning remote sensing techniques. Evidently, with a comprehensive investigation and probing of the precipitation variables in the context of urbanization models fused with remote sensing and GIS, they put forward powerful set tools for geographic cognition and understand how its influence on spatial variation. Hence, this study indicated a great research opportunity to set the course of action in determining the magnitude of spatial heterogeneity of an urban composition towards the pattern of precipitation

Patterns of historical and future urban expansion in Nepal

Globally, urbanization is increasing at an unprecedented rate at the cost of agricultural and forested lands in peri-urban areas fringing larger cities. Such land-cover change generally entails negative implications for societal and environmental sustainability, particularly in South Asia, where high demographic growth and poor land-use planning combine. Analyzing historical land-use change and predicting the future trends concerning urban expansion may support more effective land-use planning and sustainable outcomes. For Nepal's Tarai region-a populous area experiencing land-use change due to urbanization and other factors-we draw on Landsat satellite imagery to analyze historical land-use change focusing on urban expansion during 1989-2016 and predict urban expansion by 2026 and 2036 using artificial neural network (ANN) and Markov chain (MC) spatial models based on historical trends. Urban cover quadrupled since 1989, expanding by 256 km2 (460%), largely as small scattered settlements. This expansion was almost entirely at the expense of agricultural conversion (249 km2). After 2016, urban expansion is predicted to increase linearly by a further 199 km2 by 2026 and by another 165 km2 by 2036, almost all at the expense of agricultural cover. Such unplanned loss of prime agricultural lands in Nepal's fertile Tarai region is of serious concern for food-insecure countries like Nepal

Index-based Approach in Relation to Built-up and LST Dynamics; A Study of Lahore, Pakistan

In 21st century, cities outpaced in size and also in density due to development of economic sector. Consequently, the wide spread expansion of urban areas is resulting in the loss of productive green cover and water bodies. Therefore, realizing this alarming situation, the present study is aimed to investigate and evaluate the pattern of urban expansion by considering two major land cover types (i) built-up area (ii) other classes (vegetation, waterbody, soil etc.) during the last six years (2015-2020). For this study Sentinel imagery was acquired from USGS Earth Explorer, while Modis Terra images were acquired from World View NASA. New built-up area index (NBUI), normalized difference vegetation index (NDVI), worldview water index (WV-WI) and land surface temperature (LST) were calculated in order to analyze variations in Lahore’s major land cover types and its varying temperature patterns. Spatial analysis presented the obvious impacts of land development on Lahore. NBUI indicated that the built-up area has increased drastically from 34.0% in 2015 to 84.2% in 2020; NDVI analysis depicted a decline from 0.76% to 0.73%, in the green spaces of Lahore during the study period; WV-WI portrayed inconsistent values of water bodies, a gift of massive rise in the built-up area in Lahore. LST results presented that the temperature was 42.21°C in 2015, which simultaneously increased and recorded at 49.51°C in 2020. The increase in LST exhibited the alarming situation for urban environment and can become threat to increase the air pollution level in Lahore. Therefore, this study will serve as a snapshot for policy makers to control the menace of unplanned urbanization by formulating stringent policies to protect environment

Assessment of Urban Sprawl, Land Use and Land Cover Changes in Voi Town, Kenya Using Remote Sensing and Landscape Metrics

Peer reviewe

Megacities Spatiotemporal Dynamics Monitored with the Global Human Settlement Layer

Megacities are urban agglomerations hosting at least 10 million inhabitants. The rise in number, population size, and spatial extent of megacities are among the most prominent manifestations of the process of urbanisation taking place in the contemporary urban age. Until recently, urban growth has been quantified with data derived from satellites mainly for single megacities or for a limited subset of them. With the current advances in Remote Sensing and data processing, the integration of satellite data with other datasets could become a key contributor to the data revolution and support more complete urban studies and better informed policymaking. Although many remote sensing-derived products exist, few are open and free and possess the adequate resolution, information and contents to monitor the process of urban expansion. This research article builds on the premier open and free geospatial information contained in the Global Human Settlements Layer (GHSL) data package (produced at the European Commission - Joint Research Centre). This research takes advantage of existing GHSL data to identify megacities and to analyse their spatial and demographic change over the last 25 years (between 1990 and 2015). This paper quantifies how much and how fast megacities have expanded in spatial and demographic terms, and we provide graphical examples of the different manifestations of growth across megacities. The main findings of our research reveal an average demographic growth in megacities exceeding 2% a year between 1990 and 2000, and of 1.9% a year between 2000 and 2015. In the first period (1990 to 2000), megacities have expanded faster than the global average and more than the average of other urban centres. In the second period, global urban population increase has been greater than that of megacities. The comparative analysis of megacities however, reveals swift population growth in several cases: in seven cities population more than doubled between 1990 and 2015, and in six the average annual population growth exceeded 4% a year. Spatial expansion of megacities tends to occur at rates slower than that of population. In 27 cities built-up per capita has decreased over 25 years, by more than 10% in 17 cities. Megacities also differ in population density (in 2015), which in five is above 10,000 inhabitants per square kilometre, while in others, especially the ones in high-income countries, density remains around half this figure. Results highlight the value of new remote sensing-based data and methods for mapping and characterizing global urbanisation processes, in a consistent and comparable manner across space and time. The provision of open and free data ensures methods and findings can be audited and analyses extended to other cities, while the temporal dimension enables monitoring urbanisation and intergovernmental policies on sustainable urban development

Urban footprint of Mumbai - the commercial capital of India

Urban footprint refers to the proportion of paved surface (built up, roads, etc.) with the reduction of other land use types in a region. Rapid increase in the urban areas is the major driver in landscape dynamics with the significant erosion in the quality and quantity of the natural ecosystems. The urban expansion process hence needs to be monitored, quantified and understood for effective planning and the sustainable management of natural resources. Cities and towns have been experiencing considerable growth in urban area, population size, social aspects, negative environmental and geographical influence, and complexity. Mumbai, the commercial capital of India, has experienced a spurt in infrastructural and industrial activities with globalization and opening up of Indian markets. Unplanned urbanization has resulted in dispersed growth inperi-urban pockets due to socio-economic aspects with the burgeoning population of the city. Consequent to this, there has been an uneven growth pattern apart from the increase in slums in and around the city. This has necessitated the understanding of the urbanization pattern and process focusing especially on the expanding geographical area, its geometry and the spatial pattern of its development. This communication discusses the urban footprint dynamics of Mumbai using multi-temporal remote sensing data with spatial metrics. Land use analysis indicated a decrease of vegetation by 20% with an increase in urban extent by 155% during the last three decades. Landscape metrics aided in assessing the spatial structure and composition of the urban footprints through the zonal analysis by dividing the region into four zones with concentric circles of 1 km incrementing radius from the city centre. The study reveals a significant variation in the composition of the urban patch dynamics with increasing complexity and aggregation of urban area at the centre and sprawl at the outskirts. Shannon's entropy further confirms of sprawl with time. Further zoning with the circular gradients aided in understanding the transition process of land use categories into urban patch