Abdul-Lateef Balogun

Dr. Abdul-Lateef Balogun

Universiti Teknologi PETRONAS (UTP)
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2020 in Sustainable Cities and Society
Verified
Journal Article
Closed access
ABAbdul-Lateef Balogun
Abdul-Lateef Balogun
DMDanny Marks
Danny Marks
RSRicha Sharma
Richa Sharma
Himanshu ShekharHimanshu Shekhar
Himanshu Shekhar
CBChiden Balmes
Chiden Balmes
PSPourya Salehi
Pourya Salehi

1 May 2019 in Journal of Cleaner Production
Verified
Journal Article
Open access
Walter Leal FilhoWalter Leal Filho
Walter Leal Filho
DEDawn Ellams
Dawn Ellams
SHSara Han
Sara Han
DTDavid Tyler
David Tyler
VBValérie Julie Boiten
Valérie Julie Boiten
ABAbdul-Lateef Balogun
Abdul-Lateef Balogun

1 December 2019 in Journal of Cleaner Production
Verified
Journal Article
Closed access
APAngelo Paletta
Angelo Paletta
Walter Leal FilhoWalter Leal Filho
Walter Leal Filho
ABAbdul-Lateef Balogun
Abdul-Lateef Balogun
EFEleonora Foschi
Eleonora Foschi
ABAlessandra Bonoli
Alessandra Bonoli


25 March 2019 in Water
Verified
Journal Article
Open access
PDF file
Umar Lawal DanoUmar Lawal Dano
Umar Lawal Dano
ABAbdul-Lateef Balogun
Abdul-Lateef Balogun
AMAbdul-Nasir Matori
Abdul-Nasir Matori
KYKhmaruzzaman Wan Yusouf
Khmaruzzaman Wan Yusouf
Ismaila Rimi AbubakarIsmaila Rimi Abubakar
Ismaila Rimi Abubakar
Biswajeet PradhanBiswajeet Pradhan
Biswajeet Pradhan
Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts’ opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control.

3 April 2012 in Arabian Journal of Geosciences
Verified
Journal Article
Closed access
PDF file
ICImtiaz Ahmed Chandio
Imtiaz Ahmed Chandio
AMAbd Nasir B. Matori
Abd Nasir B. Matori
KWKhamaruzaman B. WanYusof
Khamaruzaman B. WanYusof
Mir Aftab Hussain TalpurMir Aftab Hussain Talpur
Mir Aftab Hussain Talpur
ABAbdul-Lateef Balogun
Abdul-Lateef Balogun
Umar Lawal DanoUmar Lawal Dano
Umar Lawal Dano