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Yusuf Aina   Mr.  University Educator/Researcher 
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Yusuf Aina published an article in November 2017.
Top co-authors
Muhammad Umair

28 shared publications

Department of Biochemistry, Faculty of Biological Sciences; Quaid-i-Azam University (QAU); Islamabad Pakistan

Elhadi Adam

9 shared publications

School of Geography, Archaeological and Environmental Studies, University of the Witwatersrand, Johannesburg, South Africa

H. M. Alshuwaikhat

3 shared publications

King Fahd University of Petroleum & Minerals , Dhahran, Saudi Arabia

9
Publications
9
Reads
0
Downloads
15
Citations
Publication Record
Distribution of Articles published per year 
(2004 - 2017)
Total number of journals
published in
 
8
 
Publications See all
Article 0 Reads 1 Citation Achieving smart sustainable cities with GeoICT support: The Saudi evolving smart cities Yusuf A. Aina Published: 01 November 2017
Cities, doi: 10.1016/j.cities.2017.07.007
DOI See at publisher website
Article 2 Reads 3 Citations The Development of a GIS-Based Model for Campus Environmental Sustainability Assessment Habib M. Alshuwaikhat, Ismaila Rimi Abubakar, Yusuf A. Aina,... Published: 17 March 2017
Sustainability, doi: 10.3390/su9030439
DOI See at publisher website
ABS Show/hide abstract
Sustainability indicators and assessments are vital in promoting campus sustainability. Despite the plethora of indicator frameworks, campus sustainability assessment in developing countries encounters many challenges including lack of, or restricted access to, data and difficulties in measuring indicators. There is also a limited application of Geographical Information Systems (GIS) in campus environmental sustainability assessment, although campus operations have spatial dimensions. This article proposes a GIS-based model for environmental sustainability assessment of campus operations and demonstrates its usefulness using King Fahd University of Petroleum and Minerals, Saudi Arabia. The model applies spatial analysis techniques, including inverse distance weighted (IDW) interpolation, to statistically assess the various campus operational activities by using land use data to estimate greenhouse gas emissions from energy use, water consumption, solid waste, and transportation. The integration of spatial dimension in the model facilitates the collection and measurement of spatially related indicators, helps identify hotspots of campus operations, and provides better visualization of the existing condition and future scenario of campus environmental sustainability status. This model can assist decision-makers to construct strategies for improving the overall environmental sustainability of university campuses. The paper concludes by highlighting how the model can address some challenges of campus sustainability assessment in developing countries.
BOOK-CHAPTER 3 Reads 0 Citations Examining the Effect of Land Use on the Spatiotemporal Dynamics of Urban Temperature in an Industrial City: A Landsat Im... Yusuf A. Aina, Irshad M. Parvez, Abdul-Lateef Balogun Published: 01 January 2017
Global Changes and Natural Disaster Management: Geo-information Technologies, doi: 10.1007/978-3-319-51844-2_1
DOI See at publisher website
PREPRINT 2 Reads 0 Citations Examining the Spatio-temporal Dynamics of PM2.5 in Saudi Arabia Using Satellite-derived Data: A Cluster Study Yusuf Aina, Elhadi Adam, Fethi Ahmed Published: 01 December 2016
doi: 10.20944/preprints201612.0011.v1
DOI See at publisher website
ABS Show/hide abstract
The study of the concentrations and effects of fine particulate matter in urban areas have been of great interest to researchers in recent times. This is due to the acknowledgment of the far-reaching impacts of fine particulate matter on public health. Remote sensing data have been used to monitor the trend of concentrations of particulate matter by deriving aerosol optical depth (AOD) from satellite images. The Center for International Earth Science Information Network (CIESIN) has released the second version of its global PM2.5 data with improvement in spatial resolution. This paper revisits the study of spatial and temporal variations in particulate matter in Saudi Arabia by exploring the cluster analysis of the new data. Cluster analysis of the PM2.5 values of Saudi cities is performed by using Anselin local Moran’s I statistic. Also, the analysis is carried out at the regional level by using self-organizing map (SOM). The results show an increasing trend in the concentrations of particulate matter in Saudi Arabia, especially in some selected urban areas. The eastern and south-western parts of the Kingdom have significantly clustering high values. Some of the PM2.5 values have passed the threshold indicated by the World Health Organization (WHO) standard and targets posing health risks to Saudi urban population.
BOOK-CHAPTER 2 Reads 0 Citations Networking the Sustainable Campus Awards: Engaging with the Higher Education Institutions in Developing Countries Habib M. Alshuwaikhat, Ismaila Rimi Abubakar, Yusuf A. Aina,... Published: 24 November 2016
World Sustainability Series, doi: 10.1007/978-3-319-47889-0_7
DOI See at publisher website
Article 0 Reads 1 Citation Spatial and Temporal Variations of Satellite-Derived Multi-Year Particulate Data of Saudi Arabia: An Exploratory Analysi... Yusuf A. Aina, Johannes H. Van Der Merwe, Habib M. Alshuwaik... Published: 27 October 2014
International Journal of Environmental Research and Public Health, doi: 10.3390/ijerph111111152
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PubMed View at PubMed
ABS Show/hide abstract
The effects of concentrations of fine particulate matter on urban populations have been gaining attention because fine particulate matter exposes the urban populace to health risks such as respiratory and cardiovascular diseases. Satellite-derived data, using aerosol optical depth (AOD), have been adopted to improve the monitoring of fine particulate matter. One of such data sources is the global multi-year PM2.5 data (2001–2010) released by the Center for International Earth Science Information Network (CIESIN). This paper explores the satellite-derived PM2.5 data of Saudi Arabia to highlight the trend of PM2.5 concentrations. It also examines the changes in PM2.5 concentrations in some urbanized areas of Saudi Arabia. Concentrations in major cities like Riyadh, Dammam, Jeddah, Makkah, Madinah and the industrial cities of Yanbu and Jubail are analyzed using cluster analysis. The health risks due to exposure of the populace are highlighted by using the World Health Organization (WHO) standard and targets. The results show a trend of increasing concentrations of PM2.5 in urban areas. Significant clusters of high values are found in the eastern and south-western part of the country. There is a need to explore this topic using images with higher spatial resolution and validate the data with ground observations to improve the analysis.
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