GIS modelling for new landfill sites: critical review of employed criteria and methods of selection criteria
Sohaib K. M. Abujayyab1, Mohd Sanusi S. Ahamad1, Ahmad Shukri Yahya1, Mohammed J.K. Bashir2 andHamidi Abdul Aziz1,3
1School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, P. Pinang, Malaysia
2Faculty of Engineering and Green Technology (FEGT), University Tunku Abdul Rahman, 31900 Kampar, Perak, Malaysia.
3Solid Waste Management Cluster, Science and Engineering Research Centre, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia.Corresponding author E-mail: s.jayyab@hotmail.com
IOP Conference Series: Earth and Environmental Science, Volume 37, 2016,
Abstract
Policy makers and the public are increasingly concerned with the determination of landfill-siting input criteria (DLSIC) in landfill modelling procedures as an area of research. Thus, its procedures are complicated and decision makers are increasingly pressured. These procedures can be considerably develop in order to reduce the negative effect of landfill locations on the environment, economy, and society. In this review article, literature related to the developments of 64 models and their procedures in the past 18 years (from 1997 to 2014) were comprehensively survey. DLSIC are determined through a conventional method. The frequency of criterion usage reflects the limitation of Conventional method for DLSIC. Moreover, some of these studies utilize unrelated criteria that are time-consuming, costly, arduous, and fruitless. Potential improvement in Geographic information systems GIS modelling parameter for landfill sites via utilizing multivariate analysis (MVA) instead of Conventional method (CM) through for DLSIC (e.g., Input variables, Accuracy, objectivity, reliability of criteria, time consumption, cost and comprehensiveness) were emphasize. It can be conclude that expenses can be reduce by implementing MVA in DLSIC for landfill modelling using geographic information systems (GIS) based on the corresponding significant level. Moreover, the determined criteria can be accurate, satisfying, sufficient, and free of bias from experts and human error.
