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Urban land-use modeling has gained increased attention as a research topic over the last decade. This has been attributed to advances in remote sensing and computing technology that now can process several models simultaneously at regional and local levels. In this research we imple-mented a cellular automata (CA) urban growth model (UGM) integrate...
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Citations
... In Africa, SLEUTH has been applied in urban growth or land use changes in Accra (Agyemang and Silva, 2019), Nairobi (Mubea and Menz, 2014), Cape Town (Watkiss, 2008) and Yaoundé (Sietchiping (2004). Badmos et al. (2019) go a step further and integrate a Logistic Regression (LR) model into SLEUTH to model slum development in Lagos. ...
The global urban population is expected to grow by 2.5 billion over the next three decades, and 90% of this growth will occur in African and Asian countries. Urban expansion in these regions is often characterised by ‘informal urbanization’ whereby households self-build without planning permission in contexts of ambiguous, insecure or disputed property rights. Despite the scale of informal urbanization, it has received little attention from scholars working in the domains of urban analytics and city science. Towards addressing this gap, we introduce TI-City, an urban growth model designed to predict the locations, legal status and socio-economic status of future residential developments in an African city. In a bottom-up approach, we use agent-based and cellular automata modelling techniques to predict the geospatial behaviour of key urban development actors, including households, real estate developers and government. We apply the model to the city-region of Accra, Ghana, drawing on local data collection, including a household survey, to parameterise the model. Using a multi-spatial-scale validation technique, we compare TI-City’s ability to simulate historically observed built-up patterns with SLEUTH, a highly popular urban growth model. Results show that TI-City outperforms SLEUTH at each scale, suggesting the model could offer a valuable decision support tool in similar city contexts.
... Forests with an undisturbed ecology and with no indications of human activity are referred to as primary forests (Lung and Schaab, 2009). In comparison to all terrestrial ecosystems, primary forests are the most species-rich and diverse (Mubea and Menz 2014). Zones that have vegetation cover other than forests, but are not under intensive land use, are defined as woodland. ...
... Other wooded land covers about 1.1 billion hectares (Mubea and Menz 2014). Africa's forests cover is approximately 21.4 percent of the land area (FAO, 2009), which covers a total of 674 million hectares (Mubea and Menz 2014). In the greater East Africa, approximately 13 percent of the land area is covered by forests and woodlands which make the resources rather limited. ...
... Between 2000 and 2010, about 4.0 million hectares were lost annually in South America followed by Africa with a forest loss of 3.4 million hectares per year. The net loss of forests has been significantly reduced, mainly because of several projects including forest planting, restoration of landscape and natural expansion of forests (Mubea and Menz 2014). But even if the net loss of forests is decreasing in some parts of the world, it continues at a high rate in other countries (FAO, 2006). ...
... Forests with an undisturbed ecology and with no indications of human activity are referred to as primary forests (Lung and Schaab, 2009). In comparison to all terrestrial ecosystems, primary forests are the most species-rich and diverse (Mubea and Menz 2014). Zones that have vegetation cover other than forests, but are not under intensive land use, are defined as woodland. ...
... Other wooded land covers about 1.1 billion hectares (Mubea and Menz 2014). Africa's forests cover is approximately 21.4 percent of the land area (FAO, 2009), which covers a total of 674 million hectares (Mubea and Menz 2014). In the greater East Africa, approximately 13 percent of the land area is covered by forests and woodlands which make the resources rather limited. ...
... Between 2000 and 2010, about 4.0 million hectares were lost annually in South America followed by Africa with a forest loss of 3.4 million hectares per year. The net loss of forests has been significantly reduced, mainly because of several projects including forest planting, restoration of landscape and natural expansion of forests (Mubea and Menz 2014). But even if the net loss of forests is decreasing in some parts of the world, it continues at a high rate in other countries (FAO, 2006). ...
The study entails detecting forest degradation and modeling future scenario using GIS and remote sensing, in Elgeyo/Marakwet County, a case study of Embobut forest, it is evident that forests have been managed for several years in the world, but in most cases especially in the developing world, various regimes have tried to come up with institutional to guide forest management with no much success, in many countries, there is no regular monitoring system that collects information about the situation of the forests and trends of the distribution. This makes it difficult to quantify the status of the existing forest cover. We used high-resolution satellite imagery as well as GIS and remote sensing software (ArcGIS and ENVI) with mathematical models to project the forest status, apart from satellite images there will be a ground truthing using Global positioning system (GPS) as data collection tool to as well as use of Auxiliary data; which will include Socio economic and data for the years 1980, 1990, 2000 and 2010. Policy implications especially with the enactment of Kenya forest act, 2005 was examined. Recorded positive changes hence increased in size while all other forest classes decreased in size. The study found out that the total forest loss was 7,172.31 hectares, this represents a loss of 28 percent of the total forested area that existed in 1986 which corresponds to an annual forest loss of 286.892 hectares. According to this study, as population increased the rate of deforestation also increased. The future scenarios from the studies were based on a fixed annual deforestation rate and a conclusion is made that Bare land & rocky and water bodies classes increased in area while Mixed Podocarpus latifolius, Juniperus-Nuxia-Podocarpus factus, Tree ferns Cyathea manniana & Bamboo, Acacia abyssica & Scrubby grassland classes decreased in size. As Population grew forestry loss increased, between 1986 and 2011, the total forest loss was 7,172.31 hectares. Future Scenario found that with the same trend, there will be no forest remaining natural forest block by the year 2038 in the study area.
... Encouraged by John Estes, urban remote sensing and urban growth modeling also became an important part of Gunter's research interests [18][19][20][21][22]. Over the past ten years, wetlands became another prominent field of application in Gunter's research portfolio [23,24]. ...
Abstrakt: W artykule omówiono wybrane relacje między rozwojem aglomeracji Nairobi a funkcjonowaniem położonego w jej granicach Parku Narodowego Nairobi. Zwrócono szczególną uwagę na rozwój społeczno-ekonomiczny i przestrzenny Nairobi, który wywiera coraz silniejszą presję na ekosystem parku. Wśród głównych czynników antropopresji wymieniono przestrzenne rozlewanie się (sprawl) miasta oraz blokowanie korytarzy migracji ssaków na tereny poza parkiem. Potrzeby rozwojowe miasta stawiają pod znakiem zapytania przyszłość PN Nairobi, która w znacznym stopniu jest uzależniona od decyzji politycznych władz krajowych. Słowa kluczowe: Nairobi, Park Narodowy Nairobi, relacje, oddziaływania, sytuacje konfliktowe.
Abstract: The article discusses selected relations between the agglomeration of Nairobi and the functioning of the Nairobi National Park located within its borders. The close attention was paid to the socioeconomic and spatial development of Nairobi, which exerts pressure on the ecosystem of the park. The spatial development (sprawl) of the city and blocking the migration corridors of mammals leading to the areas outside the park were listed among the main factors of anthropopression. The city development needs raise the question about the future of the Nairobi NP, which in fact is strictly dependent on the political decisions on national level.
Against the backdrop of urbanization, cities have evolved globally, but more so in Sub-Saharan Africa (SSA) in recent decades. Cities in the sub-region differ in many ways from those in other parts of world. One of the major differences is the overwhelmingly informal nature of urban growth in many cities in SSA, a feature that has regulation and spatial pattern dimensions. These dimensions are, however, less explored in urban modelling research. Cities have not evolved alone, but, alongside with massive evolution in the methods of their abstraction. Cellular Automata (CA) and Agent-Based Modelling (ABM) are two popular techniques that have emerged from this evolution. These models are rarely applied to cities in SSA. After a period of independent applications, there is an increasing recognition that the two approaches are mutually reinforcing, hence are mostly integrated in recent urban growth models. Existing integrated ABM and CA models of urban growth hardly account for the predominantly informal dynamics (unplanned and unregulated growth) that characterise many cities in Sub-Saharan Africa. Following the above, this research pursues three main objectives: one, simulates the urban growth of a predominantly informal Sub-Saharan African city-region with urban CA; two, examines the evolving urban spatial structure of Sub-Saharan African cities and the relationship with mainstream urban spatial structure models; and, three, develops an integrated ABM and CA model that simulates urban residential growth of a predominantly informal city-region in SSA. In exploring the first objective, diverse spatially explicit datasets are drawn from Accra, and SLEUTH, a dynamic urban CA model, is applied to the Ghanaian city-region. In relation to the second objective, the research draws on wide ranging spatial datasets and combines SLEUTH with urban spatial metrics to analyse the evolving spatial structure of Kumasi city-region (Ashanti region) of Ghana. The third, also the overarching objective, develops TI-City model (The Informal City model), an integrated ABM and CA model for simulating urban residential growth of predominantly informal cities in SSA. The model, which relies on spatial and empirical socio-economic datasets in its development, is applied to Accra city-region The research finds urban growth in both Accra and Kumasi city-region to be highly spontaneous and rapid; and new developments fast turn into urban growth nuclei. It also uncovers that, while Kumasi city-region’s urban spatial structure before the turn of the Twenty-first century largely conforms to the traditional monocentric model, it is increasingly becoming deconcentrated and dispersive, which suggests a likely pending phase of coalescence in a stochastic fractal urban growth process. Contrary to what is observed in other parts of the world, the declining monocentricity has not transformed into a polycentric urban structure, rather, urban growth is becoming amorphous. The application of TI-City, the model newly developed by this research, to Accra city-region shows that the model can offer unique insights into the dynamics of urban residential growth in predominantly informal SSA cities. TI-City could, therefore, function as a decision support tool in Ghana and many Sub-Saharan African countries. The research further discusses the implications of the model for theory, urban policy and practice.
