Simulating Urban Land Expansion in the Context of Land Use Planning in the Abuja City-Region, Nigeria

In the Global South, including the Sub-Saharan African city-regions, the possible future urban expansion patterns may pose a challenge towards improving environmental sustainability. Land use planning strategies and instruments for regulating urban expansion are faced with challenges, including insufficient data availability to offer insights into the possible future urban expansion. This study integrated empirical data derived from Geographic Information Systems, Remote Sensing, and surveys of experts to offer insights into the possible future urban expansion under spatial planning scenarios to support land use planning and environmental sustainability of city-regions. We analyzed the spatial determinants of urban expansion, calibrated the land cover model using the Multi-Layer Perceptron Neural Network and Markov, and developed three scenarios to simulate land cover from 2017 to 2030 and to 2050. The scenarios include Business As Usual that extrapolates past trends; Regional Land Use Plan that restricts urban expansion to the land designated for urban development, and; Adjusted Urban Land that incorporates the leapfrogged settlements into the land designated for urban development. Additionally, we quantified the potential degradation of environmentally sensitive areas by future urban expansion under the three scenarios. Results indicated a high, little, and no potential degradation of environmentally sensitive areas by the future urban expansion under the Business As Usual, Adjusted Urban Land, and Regional Land Use Plan scenarios respectively. The methods and the baseline information provided, especially from the Adjusted Urban Land scenario showed the possibility of balancing the need for urban expansion and the protection of environmentally sensitive areas. This would be useful to improve the environmental sustainability of the Sub-Saharan African city-regions and across the Global South, where insufficient data availability challenges land use planning.Peer Reviewe

Key Challenges for Land Use Planning and Its Environmental Assessments in the Abuja City-Region, Nigeria

Land use planning as strategic instruments to guide urban dynamics faces particular challenges in the Global South, including Sub-Saharan Africa, where urgent interventions are required to improve urban and environmental sustainability. This study investigated and identified key challenges of land use planning and its environmental assessments to improve the urban and environmental sustainability of city-regions. In doing so, we combined expert interviews and questionnaires with spatial analyses of urban and regional land use plans, as well as current and future urban land cover maps derived from Geographic Information Systems and remote sensing. By overlaying and contrasting land use plans and land cover maps, we investigated spatial inconsistencies between urban and regional plans and the associated urban land dynamics and used expert surveys to identify the causes of such inconsistencies. We furthermore identified and interrogated key challenges facing land use planning, including its environmental assessment procedures, and explored means for overcoming these barriers to rapid, yet environmentally sound urban growth. The results illuminated multiple inconsistencies (e.g., spatial conflicts) between urban and regional plans, most prominently stemming from conflicts in administrative boundaries and a lack of interdepartmental coordination. Key findings identified a lack of Strategic Environmental Assessment and inadequate implementation of land use plans caused by e.g., insufficient funding, lack of political will, political interference, corruption as challenges facing land use planning strategies for urban and environmental sustainability. The baseline information provided in this study is crucial to improve strategic planning and urban/environmental sustainability of city-regions in Sub-Saharan Africa and across the Global South, where land use planning faces similar challenges to address haphazard urban expansion patterns.Peer Reviewe

Land-use and land-cover analysis of Ilorin Emirate between 1986 and 2006 using landsat imageries

This paper examines changes in land-use and land-cover pattern in Ilorin Emirate in Nigeria between 1986 and 2006. Landsat images of Ilorin Emirates at  three epochs (1986, 2000 and 2006) were used. An administrative map of local governments in Kwara State and a land-use map of Ilorin were used as base maps. Global Mapper Software was used for the image enhancement; image classification was done with environment for visualizing images (ENVI) software   and was later exported to the ArcGIS for further  processing and analysis. The land consumption rate and land absorption coefficient was determined to aid  the  quantitative assessment of change. Subsequently, an attempt was made at projecting the observed land-use / land-cover for a period of 14 years  ending  at 2020. The result of the work shows a gradual growth in built-up land between 1986 and 2000 and this tends to grow more rapidly between 2000  and 2006. It was also observed that the change by 2020 may likely follow the trend observed in 2000 and 2006. It is recommended that the information from the results of this work should be use to optimally and effectively plan and manage the study area.Key words: Land-use, land-cover, land consumption rate, land absorption coefficient, change detection

The effect of spatial settlement patterns on urban climatology

Increasing urbanization, in addition to driving climate change and pollution, can have a profound effect on the ecosystem properties within and even far from urban areas. As such, it is important to understand the energy balance of cities including the extent of its modification by urban form. This PhD thesis examines the effect of spatial settlement pattern on urban climatology. The initial study focussed on UK overpasses of the Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite instrument, covering the period between 2000 and 2017, were sampled to examine the seasonal (winter and summer) night-time clear-sky upwelling long-wave energy for 35 UK cities. Total (area-summed) emitted energy was calculated per city. Well-defined (R2≥0.79) and robust ‘allometric’ scaling against city population was found for all samples. Total night-time emitted energy is found to scale sub-linearly with population on both summer and winter nights, with slope of 0.85±0.03. The scaling of night-time emitted energy with urban areas is close to linear (1.0±0.05). This indicates that UK Cities, although often appearing superficially very different, are similar in their gross thermal properties, i.e., in terms of the components of urban form, which dictate thermal properties. A case study of Nigeria’s cities on allometric scaling of emitted energy with population is also investigated, and it turned out to be very different from the UK study with slope of 0.41±0.05. Nigerian cities show much more sub-linear allometric scaling of total emitted energy with population, indicating slightly economy of scale in terms of nocturnal heat production. Local climate zones are further used to interpret results from the study. The study went further to investigate how the sum measure of the spatial distribution of emitted energy inside the city’s boundary is affected by the urban morphology, using the previous UK study. A fitted distribution of both extremes’ percentiles of emitted energy and land use maps within city were used as basis for comparison across cities in order to delineate the hottest and coldest spots in the distribution of long-wave energy for a sample night

The Spatial and Temporal Characteristics of the Urban Thermal Environment in East Africa: Implications for Sustainable Urban Development

Targeting cities in East Africa, where urbanisation and climate change are posing unprecedented threats to livelihoods and ecosystems, this thesis focuses on the combined effects of rapid urbanisation and climate change on Land Surface Temperature (LST), Surface Urban Heat Island (SUHI) effects and the role of Blue Green infrastructure (BGI) and vegetation dynamics. The aim of this thesis is to advance understanding of the urban thermal environment and the role of factors such as climate, vegetation and urbanisation patterns that add to its complexity. Through the use of satellite and remote sensing data (e.g., Google Earth Engine), spatial and statistical analyses, conducted in ArcGIS, Geoda and R, this thesis provides analyses of temporal trends between 2003 and 2017, and spatial differences in LST and SUHI in five East African cities (Khartoum, Addis Ababa, Kampala, Nairobi, Dar es Salaam). It advances understanding of how the configuration of urban areas affects the urban thermal environment, the amount of vegetation and surface water, and demonstrates the influence of urban density on the changes in SUHI intensity in both space and time. By linking the findings from the three results chapters and placing this in the context of the broader literature, corresponding policy implications and solutions are presented. The urgent need to provide a more detailed understanding of urban thermal environments, including macroclimate differences, seasonal variation and urban morphological characteristics, is highlighted. Recommendations emphasise the use of cloud-based analysis methods to overcome data scarcity, while the results point towards the utility of nature-based solutions for urban sustainable development. The methods and lessons emerging from this study can also be applied in other rapidly urbanising cities, where climate change is posing an unprecedented threat to livelihoods and ecosystems, and where resources are limited

Urban expansion occurred at the expense of agricultural lands in the Tarai region of Nepal from 1989 to 2016

Recent rapid urbanization in developing countries presents challenges for sustainable environmental planning and peri-urban cropland management. An improved understanding of the timing and pattern of urbanization is needed to determine how to better plan urbanization for the near future. Here, we describe the spatio-temporal patterns of urbanization and related land-use/land-cover (LULC) changes in the Tarai region of Nepal, as well as discuss the factors underlying its rapid urban expansion. Analyses are based on regional time-series Landsat 5, 7 and 8 image classifications for six years between 1989 and 2016, representing the first long-term observations of their kind for Nepal. During this 27-year period, gains in urban cover and losses of cultivated lands occurred widely. Urban cover occupied 221.1 km2 in 1989 and increased 320% by 2016 to a total 930.22 km2. Cultivated land was the primary source of new urban cover. Of the new urban cover added since 1989, 93% was formerly cultivated. Urban expansion occurred at moderately exponential rates over consecutive observation periods, with nearly half of all urban expansion occurring during 2006–2011 (305 km2). The annual rate of urban growth during 1989–1996 averaged 3.3% but reached as high as 8.09% and 12.61% during 1996–2001 and 2011–2016, respectively. At the district level, the rate of urban growth and, by extension, agricultural loss, were weakly related to total population growth. Variability in this relationship suggests that concerted urban-growth management may reduce losses of agricultural lands relative to historic trends despite further population growth and urbanization. Urbanization and LULC change in the Tarai region are attributable to significant inter-regional migration in a context of poor urban planning and lax policies controlling the conversion and fragmentation of peri-urban cultivated lands. Urban expansion and farmland loss are expected to continue in the future

An Integrated Remote Sensing and Urban Growth Model Approach to Curb Slum Formation in Lagos Megacity

Rapid urbanization with limited development has led to slum proliferation in many sub-Saharan African cities. Slums are recognized as a menace to planned cities, as they do not conform to planning standards, thus the need to curb their growth. However, this proves to be a challenge for many of these cities due to unavailability of data on the existing situation. It is against this background that this study aims to contribute ground information and a spatial planning tool to support urban planning to better manage slum formation in Lagos, Nigeria. Slum growth can be described as spatial or as population growth; hence this study first analyzed and quantified the spatial growth of slums in Lagos using remote sensing techniques and intensity analysis. Then the influence of residential choices of slum dwellers on population growth in Lagos slums was assessed using ethnographic survey approach through questionnaires and focus group discussions. An urban growth model coupling logistic regression with modified cellular automata SLEUTH was used to simulate scenarios of the patterns of slum development in Lagos by 2035. RapidEye imagery from 2009 and 2015 was used to create maps for each time point for six land-use categories (water, vegetated area, open space, road, slum, and other urban) in the study area. Intensity analysis was applied to quantify the annual intensity of changes at the category and transition level. An overall accuracy (and kappa coefficient) of 94% (0.9) and 89% (0.86) was achieved for the 2009 and 2015 land-use and land-cover maps. The results of this study show that slums in Lagos increased spatially between 2009 and 2015 gaining a land area of 9.14 km2 influenced by in-migration. However, the intensity analysis reveals slum as an active land-use category, losing some of its land area but also gaining new land area during this period. The annual gain and loss was 10.08% and 6.41%, respectively, compared to the uniform intensity of 3.15%. A systematic process of transition was observed between slums and other urban areas and open space in the interval studied, and this process was mainly influenced by the Lagos state government. The transition from slum to other land-use categories, such as other urban, is attributed to gentrification and demolition processes, while the transition from other land-use categories to slum is due to poor maintenance of existing buildings and encroachment on available spaces in the city. Questionnaires administration and focus group discussion were conducted in four communities (Ajegunle, Iwaya, Itire and Ikorodu) in Lagos to investigate the factors influencing the residential choices and reasons of the people to remain in the Lagos slums. Descriptive statistics was used to analyze and describe the factors influencing the residential location choice, and logistic regression was applied to determine the extent to which the neighborhood and household attributes influence slum dwellers’ decisions to remain in the slums. Over 70% of the respondents were migrants from neighboring geopolitical zones (in Nigeria). The movement patterns of slum dwellers in Lagos support two theories of human mobility in slums: slum as a sink and slum as a final destination. Also, the factors that attracted most of the slum dwellers to the slums (cheap housing, proximity to work, etc.) differ from those that made them stay (duration of stay, housing status, etc.). A hybrid land-use model, which involves the coupling of logistic regression with cellular automata SLEUTH, implemented in XULU, was utilized for the simulation of scenarios of slum growth in Lagos. The scenarios were designed based on the modification of the exclusion layer and the transition rules. The scenario 1 was business as usual with slum development similar to the present trend. The scenario 2 was based on the future population projection for the city, while the scenario 3 was based on limited interference by the government in slum development in the city. Distance to markets, shoreline, and local government administrative buildings, and land prices, etc., were predictors of slum development in Lagos. An overall accuracy of 79.17% and a relative operation characteristics (ROC) value of 0.85 were achieved for the prediction of slum development, based on the logistic regression model. The probability map generated from fitting the coefficients of the estimates in the logistic regression shows that slums can develop within the city and at the fringe, and also in places mostly inaccessible to the Lagos state government. Scenarios 1, 2 and 3 predict that the slum area will increase by 1.18 km2, 4.02 km2 and 1.28 km2, respectively, in 2035 through further densification of the existing slums and new development at the south-eastern fringe of the city. The limited growth is due to the high population density in the city, and thus it is assumed that new slums will probably develop in the neighboring cities due to spill over of the Lagos population. The outcome of this research shows that the landscape is very dynamic in Lagos, and even over an interval of a few years, changes can be observed. It also shows that the integration of remote sensing, social science method and spatially explicit land-use model can address the challenges of data availability in the slum dynamic, especially in sub-Saharan African countries with high slum proliferation. This can support a comprehensive set of techniques important for the management of existing slums and prevention of new slum development.Reduzierung des Slumwachstums in der Megastadt Lagos: Ein integrierter Ansatz aus Fernerkundung und urbanem Wachstumsmodell Eine schnelle Urbanisierung bei begrenzter Entwicklung hat in vielen afrikanischen Städten südlich der Sahara zu einer Zunahme von Slums geführt. Slums werden dabei als Bedrohung für die Planstädte angesehen, da sie nicht den Planungsstandards entsprechen, ihr Wachstum sollte daher reduziert werden. Dies erweist sich jedoch für viele dieser Länder als Herausforderung, da keine Daten über die aktuelle Situation vorliegen. Vor diesem Hintergrund zielt diese Studie darauf ab, Informationen und ein Raumplanungsinstrument zur Unterstützung der Stadtplanung zur Verfügung zu stellen, dies soll ein besseres Management der Slumbildung in Lagos, Nigeria ermöglichen. Slumwachstum kann als räumliches Wachstum, oder als Wachstum der Bevölkerung bezeichnet werden; daher hat diese Studie zunächst das räumliche Wachstum von Slums in Lagos mit Hilfe von Fernerkundungstechniken und Intensitätsanalysen analysiert und quantifiziert. Anschließend wurde der Einfluss der Wohnortwahl von Slumbewohnern auf das Bevölkerungswachstum in den Slums von Lagos mit Hilfe eines ethnographischen Erhebung Ansatzes bewertet. Dabei kamen Fragebögen und Fokusgruppendiskussionen zum Einsatz. Ein urbanes Wachstumsmodell, das die logistische Regression mit dem modifizierten zellulären Automaten SLEUTH koppelt, wurde verwendet, um Szenarien und Strukturen der Slumentwicklung in Lagos bis 2035 zu simulieren. RapidEye-Datenaus den Jahren 2009 und 2015 wurden verwendet, um Karten zu jeden Zeitpunkt für sechs Landnutzungskategorien (Wasser, Vegetationsflächen, Freiflächen, Straßen, Slum und andere städtische Gebiete) zu erstellen. Mit Hilfe der Intensitätsanalyse wurde die jährliche Intensität der Veränderungen hinsichtlich der Kategorien und Veränderungstypen quantifiziert. Für die Landnutzungs- und Bodenbedeckungskarten 2009 und 2015 wurde eine Gesamtgenauigkeit (und ein Kappa-Koeffizient) von 94 % (0,9) und 89 % (0,86) erreicht. Die Ergebnisse dieser Studie zeigen, dass die Slums in Lagos zwischen 2009 und 2015 räumlich gewachsen sind und durch Zuzug eine Landfläche von 9,14 km2 erreicht haben. Die Intensitätsanalyse zeigt auch, dass der Slums in Lagos als aktive Landnutzungskategorie einen Teil ihrer Fläche im Beobachtungszeitraum verloren haben. Der jährliche Gewinn und Verlust betrug 10,08 % bzw. 6,41 % im Vergleich zur einheitlichen Intensität von 3,15 %. Ebenfalls wurde ein systematischer Prozess des Übergangs zwischen Slums und anderen städtischen Gebieten sowie Freiraum in der untersuchten Zeitspanne beobachtet. Dieser Prozess wurde hauptsächlich von der Regierung von Lagos beeinflusst. Der Übergang von Slum zu anderen Landnutzungskategorien, wie zum Beispiel andere städtische Gebiete ist auf Gentrifizierung und Abrissprozesse zurückzuführen, während der Übergang von anderen Landnutzungskategorien hin zu Slums auf eine schlechte Instandhaltung bestehender Gebäude und auf die Beeinträchtigung der verfügbaren Flächen in der Stadt zurückzuführen ist. In vier Gemeinden (Ajegunle, Iwaya, Itire and Ikorodu) in Lagos wurden Umfragen mit Fragebögen und Fokusgruppendiskussionen durchgeführt, um die Faktoren zu untersuchen, welche die Wahl des Wohnortes beeinflussen, und um zu untersuchen, warum die Menschen in den Slums von Lagos bleiben. Mit Hilfe der deskriptiven Statistik wurden die Faktoren analysiert und beschrieben, die die Wahl des Wohnortes beeinflussen, und mit Hilfe der logistischen Regression wurde ermittelt, inwieweit die Nachbarschafts- und Haushaltsattribute die Entscheidung der Slumbewohner, in den Slums zu bleiben, beeinflussen. Über 70 % der Befragten waren Migranten aus benachbarten geopolitischen Zonen (Lagos). Die Bewegungsmuster der Slumbewohner in Lagos unterstützen zwei Theorien der menschlichen Mobilität in Slums: Der Slum als Senke oder Endziel. Auch die Faktoren, die die meisten Slumbewohner in die Slums lockten (günstiger Wohnraum, Nähe zum Arbeitsplatz usw.), unterscheiden sich von denen, die sie am Ende zum Bleiben brachten (Aufenthaltsdauer, Wohnstatus usw.). Ein hybrides Landnutzungsmodell, das eine Kopplung der logistischen Regression mit den zellulären Automaten SLEUTH in XULU verbindet, wurde für die Simulation von Szenarien des Slumwachstums in Lagos bis zum Jahr 2035 verwendet. Die Szenarien wurden mittels der Ausschlussflächen und Wachstumskoeffizienten implementiert. Das Szenario 1 „business as usual“ simulierte eine Slumentwicklung ähnlich dem aktuellen Trend. Das Szenario 2 basierte auf der generellen Bevölkerungsprognose für die Stadt, während das Szenario 3 eine begrenzte Einmischung der Regierung auf die Slumentwicklung in der Stadt einbezieht. Die Entfernung zu Märkten, Verwaltungseinrichtungen, Küsten sowie die Grundstückspreisen usw. waren Antriebskräfte für die Entwicklung der Slums in Lagos. Für die Vorhersage der Slum-Entwicklung auf Basis des logistischen Regressionsmodells wurden eine Gesamtgenauigkeit von 79,17 % und einem Receiver-Operating-Characteristic-Wert (ROC) von 0,85 erreicht. Die Wahrscheinlichkeitskarte, die durch die Anpassung der Koeffizienten und der Schätzungen in der logistischen Regression erzeugt wurde, zeigt, dass sich Slums innerhalb der Stadt und in der Peripherie entwickeln können, aber auch an Orten, die dem Einfluss der Landesregierung von Lagos weitgehend entzogen sind. Szenarien 1, 2 und 3 prognostizieren, dass das Slumgebiet bis 2035 durch weitere Verdichtung der bestehenden Slums und Neuentwicklung am südöstlichen Stadtrand um 1,18 km2, 4,02 km2 bzw. 1,28 km2 zunehmen wird. Das relativ begrenzte Wachstum ist auf die hohe Bevölkerungsdichte in der Stadt zurückzuführen, so dass davon ausgegangen wird, dass sich in den Nachbarstädten durch das Verlagern der Lagos-Bevölkerung neue Slums entwickeln werden Das Ergebnis dieser Disertation zeigt, dass die Stadtlandschaft in Lagos sehr dynamisch ist, Veränderungen können selbst über einen Zeitraum von nur wenigen Jahren beobachtet werden. Die Ergebnisse zeigen auch, dass eine Integration von Fernerkundung, sozialwissenschaftlicher Methoden und räumlich explizites Landnutzungsmodells das Problem der geringen Datenverfügbarkeit in dynamischen Slums lösen kann. Dies ist besonders hilfreich in afrikanischen Ländern südlich der Sahara mit hoher Slum,proliferation. Umfassende Techniken des Slum-Managements, insbesondere zur Verhinderung der Entstehung von neuen Slums, können so wirksam unterstützt werden