scholarly journals Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

2018 ◽  
Vol 51 (1) ◽  
pp. 251-265 ◽  
Author(s):  
Jianzhu Wang ◽  
Ikechukwu Nnamdi Maduako
Proceedings ◽  
2019 ◽  
Vol 46 (1) ◽  
pp. 17
Author(s):  
Garima Nautiyal ◽  
Sandeep Maithani ◽  
Ashutosh Bhardwaj ◽  
Archana Sharma

Relative Entropy (RE) is defined as the measure of the degree of randomness of any geographical variable (i.e., urban growth). It is an effective indicator to evaluate the patterns of urban growth, whether compact or dispersed. In the present study, RE has been used to evaluate the urban growth of Dehradun city. Dehradun, the capital of Uttarakhand, is situated in the foothills of the Himalayas and has undergone rapid urbanization. Landsat satellite data for the years 2000, 2010 and 2019 have been used in the study. Built-up cover outside municipal limits and within municipal limits was classified for the given time period. The road network and city center of the study area were also delineated using satellite data. RE was calculated for the periods 2000–2010 and 2010–2019 with respect to the road network and city center. High values of RE indicate higher levels of urban sprawl, whereas lower values indicate compactness. The urban growth pattern over a period of 19 years was examined with the help of RE.


Sci ◽  
2020 ◽  
Vol 2 (4) ◽  
pp. 80
Author(s):  
Olalekan O. Onilude ◽  
Eric Vaz

Urban growth in various cities across the world, especially in developing countries, leads to land use change. Thus, predicting future urban growth in the most rapidly growing region of Nigeria becomes a significant endeavor. This study analyzes land use and land cover (LULC) change and predicts the future urban growth of the Lagos metropolitan region, using Cellular Automata (CA) model. To achieve this, the GlobeLand30 datasets from years 2000 and 2010 were used to obtain LULC maps, which were utilized for modeling and prediction. Change analysis and prediction for LULC scenario for 2030 were performed using LCM and CA_Markov chain modeling. The results show a substantial growth of artificial surfaces, which will cause further reductions in cultivated land, grassland, shrubland, wetland, and waterbodies. There was no appreciable impact of change for bare land, as its initial extent of cover later disappeared completely. Additionally, artificial surfaces/urban growth in Lagos expanded to the neighboring towns and localities in Ogun State during the study period, and it is expected that such growth will be higher in 2030. Lastly, the study findings will be beneficial to urban planners and land use managers in making key decisions regarding urban growth and improved land use management in Nigeria.


2018 ◽  
Vol 47 (6) ◽  
pp. 1047-1064
Author(s):  
Sanaz Alaei Moghadam ◽  
Mohammad Karimi ◽  
Kyoumars Habibi

Interactions between cities play a significant role in the development of metropolitan regions. Although these interactions and their role in the urban growth modelling have already been investigated, there is still room for more studies. In this research, in addition to conventional urban growth factors, spatial interactions between the cities (SIBC) are incorporated into urban growth modelling. This causes directional trends in urban growth (DTUG). Therefore, first the DTUG of each city was measured using a developed indicator based on the history of urban growth that was extracted from satellite images and spatial statistics. The SIBC was then estimated by integrating the DTUG of the cities. Finally, the SIBC and other driving forces, including the physical suitability, accessibility and neighbourhood effects, were integrated using a cellular automata-based model. The accuracy of the model in the Tehran metropolitan region was increased by 6.44% after considering the SIBC. The analysis of the DTUG and SIBC in the Tehran metropolitan region during 1991–2000–2007–2014 revealed specific patterns as the spatial interactions intensified over time and usually peaked in the periphery of the central business districts and intense interactions existed between the metropolises and other major cities. These findings could help urban managers with strategic decision-making in the metropolitan regions and adjust the science and practice relation in this field.


2021 ◽  
Vol 26 (43) ◽  
Author(s):  
Maximilian Muenchhoff ◽  
Alexander Graf ◽  
Stefan Krebs ◽  
Caroline Quartucci ◽  
Sandra Hasmann ◽  
...  

Background In the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data. Aim We applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata. Methods We investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission. Results We identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions. Conclusions Early spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.


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