Case study greater Cairo Region Egypt

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively

Investigation into land-use change in two contrasting areas in the Nile Delta, Egypt

Understanding land-use change in developing countries, particularly those situated in environmentally vulnerable and and semi-arid zones, is crucial given the considerable pressures arising due to rapid population growth, climate change and desertification. The purpose of this research was to investigate the main drivers affecting land-use change in the eastern part of the Nile Delta, Egypt in the last two decades. Two contrasting cities in the region were selected for detailed analysis. Almansourah is an ancient settlement relatively close to the Damietta branch of the Nile whereas Alzaqazig is a recent development and the surrounding area was reclaimed from the desert. The DPSIR (driving forces, pressures, state, impacts and responses) model was adopted as the conceptual framework for organising and categorising the factors affecting landuse change in these two areas. It is a linear, `formulaic' approach, based on the concept of causality chains which connect human activities with environmental information. The case study approach was used as the main methodology, although both qualitative and quantitative techniques were employed throughout. A range of sources were consulted throughout the investigation to ensure that the evidence was internally consistent: remote sensing data, questionnaire data, interviews, participant observation and census data. More than 180 farmers were interviewed in the two study areas and the majority of these (71%) farmed less than 2ha. Using remote sensing data it was found that crop patterns had changed considerably in the two areas both with regard to their geographical distribution and extent. In the Almansourah study area, the key changes during the past two decades were the increase of cotton area and the decrease in rice, maize and other crops. In contrast, the Alzagazig study area experienced an increase in cotton and rice area with minor increase in maize fields. There was also an expansion of urban and rural-urban settlements into agricultural land in both the study areas.One of the critical physical factors for land-use change was found to be the need for irrigation water. Regarding the two study areas, Almansourah currently enjoys greater availability of irrigation water because of its proximity to the Nile compared to Alzagazig which facilitated land-use change in Almansourah. On a more general level the aridity of the Nile Delta region makes water a limiting factor in agricultural production. Analysis of the driving forces showed that land-use change was highly dependent on economic factors such as transportation availability and cost as well as the contribution of women. Land-use change was significantly influenced by transportation availability in Almansourah but not in Alzaqazig possibly because of the greater need to transport agricultural produce to market. Social drivers were also found to be significant. One significant pressure was caused by population growth; in Almansourah the lack of alternative sources of land led to the expansion of urban and rural urban settlements onto fertile agricultural fields. The study confirmed that a farmer's educational level plays an important role in agricultural production. Almost 25% of farmers in Almansourah and 30% in Alzaqaziq had no formal education and this difference led to variations in land-use change between the areas. Education level was found to have a considerable influence on crop rotation and manure use in the Almansourah study area. Conversely, subsidies from private financial sources and rural women's contribution to agricultural production were among the key drivers for land-use change in the Alzaqazig study area. One of the innovative aspects of this study was the application of the DPSIR framework. Although it has been used to advantage in the developed world, it has not been applied to study land-use change in an arid, developing country. The study confirmed that the framework worked well in such a context. Notable strengths included its comprehensive nature, ability to deal with uncertainty and handle different types of data. A further advantage was that it could incorporate sub-models to investigate individual driving forces, for example, the need for irrigation water. Overall the use of DPSIR was flexible enough to highlight the major causative drivers affecting land-use and also to take account of the action of more subtle and complex factors.The University of Damascus, Syria anthe University of Plymout

predictSLUMS: A new model for identifying and predicting informal settlements and slums in cities from street intersections using machine learning

Identifying current and future informal regions within cities remains a crucial issue for policymakers and governments in developing countries. The delineation process of identifying such regions in cities requires a lot of resources. While there are various studies that identify informal settlements based on satellite image classification, relying on both supervised or unsupervised machine learning approaches, these models either require multiple input data to function or need further development with regards to precision. In this paper, we introduce a novel method for identifying and predicting informal settlements using only street intersections data, regardless of the variation of urban form, number of floors, materials used for construction or street width. With such minimal input data, we attempt to provide planners and policy-makers with a pragmatic tool that can aid in identifying informal zones in cities. The algorithm of the model is based on spatial statistics and a machine learning approach, using Multinomial Logistic Regression (MNL) and Artificial Neural Networks (ANN). The proposed model relies on defining informal settlements based on two ubiquitous characteristics that these regions tend to be filled in with smaller subdivided lots of housing relative to the formal areas within the local context, and the paucity of services and infrastructure within the boundary of these settlements that require relatively bigger lots. We applied the model in five major cities in Egypt and India that have spatial structures in which informality is present. These cities are Greater Cairo, Alexandria, Hurghada and Minya in Egypt, and Mumbai in India. The predictSLUMS model shows high validity and accuracy for identifying and predicting informality within the same city the model was trained on or in different ones of a similar context.Comment: 26 page

Change Detection Process and Techniques

Land use / land cover changes studies have become very interesting over the past decades through using remote sensing because of the availability of a suite of sensors operating at various imaging scales and scope of using various techniques as well as considered the good ways for effective monitoring and accurate land use /land cover changes. This paper looks into the following aspects related to the remote sensing technology, change detection process and techniques for land cover changes, and factor affecting change detection techniques and considerations. Keywords: Remote Sensing, Land Use / Land Cover, Change Detectio

Quantitative Estimation of Saline-Soil Amelioration Using Remote-Sensing Indices in Arid Land for Better Management

Soil salinity and sodicity are significant issues worldwide. In particular, they represent the most dominant types of degraded lands, especially in arid and semi-arid regions with minimal rainfall. Furthermore, in these areas, human activities mainly contribute to increasing the degree of soil salinity, especially in dry areas. This study developed a model for mapping soil salinity and sodicity using remote sensing and geographic information systems (GIS). It also provided salinity management techniques (leaching and gypsum requirements) to ameliorate soil and improve crop productivity. The model results showed a high correlation between the soil electrical conductivity (ECe) and remote-sensing spectral indices SIA, SI3, VSSI, and SI9 (R-2 = 0.90, 0.89, 0.87, and 0.83), respectively. In contrast, it showed a low correlation between ECe and SI5 (R-2 = 0.21). The salt-affected soils in the study area cover about 56% of cultivated land, of which the spatial distribution of different soil salinity levels ranged from low soil salinity of 44% of the salinized cultivated land, moderate soil salinity of 27% of salinized cultivated land, high soil salinity of 29% of the salinized cultivated land, and extreme soil salinity of 1% of the salinized cultivated land. The leaching water requirement (LR) depths ranged from 0.1 to 0.30 m ha(-1), while the gypsum requirement (GR) ranged from 0.1 to 9 ton ha(-1)

Monitoring, modelling and managing urban growth in Alexandria, Egypt using remote sensing and GIS

Alexandria is the second largest urban governorate in Egypt and has seen significant urban growth in its modern and contemporary history. This study investigates the urban growth phenomenon in Alexandria, Egypt using the integration of remote sensing and GIS. The study has revealed some significant findings that can help in understanding the current and future trends of urban growth in Alexandria. For demographic analysis, growth rates dropped off between 1976 and 1996. In the same manner, Alexandria's population decreased from 6.33% of total country in 1976 to 5.6% in 1996. Family size and crowding rates are declining as well. Moreover, the role of internal migration has changed and the city sends out more population than it receives. In addition, there is a clear decline in population density in the city's core, while city fringes have witnessed increases in their density. For physical expansion, Alexandria experienced a long history of deterioration from the end of the Roman era until the French expedition's departure in the beginning of the 19`" century. Alexandria began to revive again from the first half of the 19`n century during Mohamed Ali era up to date. The city expanded in all available directions. Therefore, the side effects of urban growth commenced to develop in some parts such as informal housing on the cultivated land in the east and southeast of the city. The urban physical expansion and change were detected using Landsat satellite images. The satellite images of years 1984 and 1993 were first georeferenced, achieving a very small RMSE that provided high accuracy data for satellite image analysis. Then, the images were classified using a tailored classification scheme with accuracy of 93.82% and 95.27% for 1984 and 1993 images respectively. This high accuracy enabled detecting land use/cover changes with high confidence using a postclassification comparison method. One of the most important findings here is the loss of cultivated land in favour of urban expansion. If the current loss rates continued, 75% of green lands would be lost by year 2191. These hazardous rates call for an urban growth management policy that can preserve such valuable resources to achieve sustainable urban development. The starting point of any management programme will be based on the modelling of the future growth. Modelling techniques can help in defining the scenarios of urban growth. In this study, the SLEUTH urban growth model was applied to predict future urban expansion in Alexandria until the year 2055. The application of this model in Alexandria of Egypt with its different environmental characteristics is the first application outside USA and Europe. The results revealed that future urban growth would continue in the edges of the current urban extent, which means the cultivated lands in the east and the southeast of the city will continue to lose more day by day from their area. To deal with this crisis, there is a serious need for a comprehensive urban growth management programme that based on the best practices in similar situations. Good urban governance, public participation, using GIS and remote sensing, and decentralisation (among others) are found to be the most important principles for such programme.EThOS - Electronic Theses Online ServiceEgyptian Government, Ministry of Higher EducationGBUnited Kingdo

Land cover change from national to global scales:A spatiotemporal assessment of trajectories, transitions and drivers

Changes in global land cover (LC) have significant consequences for global environmental change, impacting the sustainability of biogeochemical cycles, ecosystem services, biodiversity, and food security. Different forms of LC change have taken place across the world in recent decades due to a combination of natural and anthropogenic drivers, however, the types of change and rates of change have traditionally been hard to quantify. This thesis exploits the properties of the recently released ESA-CCI-LC product – an internally consistent, high-resolution annual time-series of global LC extending from 1992 to 2018. Specifically, this thesis uses a combination of trajectories and transition maps to quantify LC changes over time at national, continental and global scales, in order to develop a deeper understanding of what, where and when significant changes in LC have taken place and relates these to natural and anthropogenic drivers. This thesis presents three analytical chapters that contribute to achieving the objectives and the overarching aim of the thesis. The first analytical chapter initially focuses on the Nile Delta region of Egypt, one of the most densely populated and rapidly urbanising regions globally, to quantify historic rates of urbanisation across the fertile agricultural land, before modelling a series of alternative futures in which these lands are largely protected from future urban expansion. The results show that 74,600 hectares of fertile agricultural land in the Nile Delta (Old Lands) was lost to urban expansion between 1992 and 2015. Furthermore, a scenario that encouraged urban expansion into the desert and adjacent to areas of existing high population density could be achieved, hence preserving large areas of fertile agricultural land within the Nile Delta. The second analytical chapter goes on to examine LC changes across sub-Saharan Africa (SSA), a complex and diverse environment, through the joint lenses of political regions and ecoregions, differentiating between natural and anthropogenic signals of change and relating to likely drivers. The results reveal key LC change processes at a range of spatial scales, and identify hotspots of LC change. The major five key LC change processes were: (i) “gain of dry forests” covered the largest extent and was distributed across the whole of SSA; (ii) “greening of deserts” found adjacent to desert areas (e.g., the Sahel belt); (iii) “loss of tree-dominated savanna” extending mainly across South-eastern Africa; (iv) “loss of shrub-dominated savanna” stretching across West Africa, and “loss of tropical rainforests” unexpectedly covering the smallest extent, mainly in the DRC, West Africa and Madagascar. The final analytical chapter considers LC change at the global scale, providing a comprehensive assessment of LC gains and losses, trajectories and transitions, including a complete assessment of associated uncertainties. This chapter highlights variability between continents and identifies locations of high LC dynamism, recognising global hotspots for sustainability challenges. At the national scale, the chapter identifies the top 10 countries with the largest percentages of forest loss and urban expansion globally. The results show that the majority of these countries have stabilised their forest losses, however, urban expansion was consistently on the rise in all countries. The thesis concludes with recommendations for future research as global LC products become more refined (spatially, temporally and thematically) allowing deeper insights into the causes and consequences of global LC change to be determined

Earth Resources: A continuing bibliography with indexes

This bibliography lists 623 reports, articles, and other documents introduced into the NASA scientific and technical information system between April 1 and June 30, 1983. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Understanding spatial growth and resilience of megacities based on the DPSIR conceptual model:study case: Greater Cairo Metropolis, Egypt

Die Bewältigung stadtplanerischer Aufgaben in komplexen urbanen Systemen, wie des Großraums Kairo (GCM) bedarf eines vertieften Verständnisses dieses sozio-ökologischen Systems. In dieser Studie werden die Konzepte des räumlichen Wachstums und der räumlichen Resilienz genutzt, um über die Analyse der physisch-räumlichen Gegebenheiten hinaus, auf die Prozesse und Beziehungen der Akteure zur sie umgebenden Umwelt zu schließen und zu analysieren, wie sich diese in Raum und Zeit verändert haben. Die Basis bildet das DPSIR-Schema als Rahmenkonzept, um räumliche Indikatoren auf zwei Ebenen abzubilden. Diese resultieren aus pixel- und objektorientierten Klassifikationen von Fernerkundungsdaten (LANDSAT und SPOT), welche die Änderungen in der Landbedeckung und Landnutzung in mehreren Zeitschnitten abbilden. In der Studie konnten über vierzehn Hotspots identifiziert werden, die in verschiedene Kategorien eingeteilt werden konnten. Auf sie sollte die Stadtentwicklung ein verstärktes Augenmerk richten.Planning the sustainable development of complex socio-ecological systems such as the megacity Greater Cairo Metropolis (GCM) requires an understanding of the physical change of the main components of the system. From that point of view, this study introduces the analysis of spatial growth and spatial resilience as two fundamental concepts to find out the relation between social actors and activities, and their physical and environmental expressions and impacts in time and space. The thesis uses the DPSIR conceptual model as a framework to examine spatial indicators on different levels. Both of them represent pixel and object based interpretations of remotedly sensed data (LANDSAT and SPOT) especially focused on land use/land cover change (LULCC). The study could show that there are about fourteen hot spot areas which are in need of different responses e.g. by land management based on their types, properties and spatial features. Most of them can be categorized as open corridors of urban sprawl and saturated closed slums