Title: Assessment of spatial models for interpolation of elevation in Pakistan

Authors: Ijaz Hussain; Muhammad Faisal; Muhammad Yousaf Shad; Tajammal Hussain; Saeed Ahmed

Addresses: Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan ' National Centre for Bioinformatics (NCB), Quaid-i-Azam University, 45320 Islamabad, Pakistan ' Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan ' Department of Statistics, COMSATS Institute of Information Technology, Lahore, Pakistan ' Islamabad Model College, Islamabad, Pakistan

Abstract: Elevation has major impact on the climate change. Interpolation of elevation at any location in Pakistan may be useful for predicting environmental parameters such as precipitation, temperature, humidity and wind speed. The locations with low elevations are more effecting global warming as compared with locations at high elevation. Present study interpolates the amount of elevation at unobserved locations using: 1) model-based ordinary kriging; 2) model-based Bayesian kriging with constant trend; 3) model-based Bayesian kriging with varying trend; 4) spatial artificial neural network. Prediction maps of elevation for complete domain are estimated along with prediction standard deviation. The results of suggested methods are compared with means of leave one take others cross validation method. It is observed from cross validation method that model-based Bayesian kriging with constant trend performs better than the other methods of predicting the amount of elevation in Pakistan.

Keywords: Bayesian kriging; elevation; height; ordinary kriging; spatial ANNs; artificial neural networks; SANN; Pakistan; spatial modelling; climate change; precipitation; rainfall; temperature; humidity; wind speed; global warming; spatial interpolation.

DOI: 10.1504/IJGW.2015.069371

International Journal of Global Warming, 2015 Vol.7 No.3, pp.409 - 422

Received: 15 Jul 2013
Accepted: 11 Dec 2013
Published online: 14 May 2015 *

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