Validation of CA-Markov for Simulation of Land Use and Cover Change in the Langat Basin, Malaysia

Hadi Memarian,Alias Mohd Sood,Siva Kumar Balasundram,Karim Abbaspour,Jamal Bin Talib,Christopher Teh Boon Sung

doi:10.4236/jgis.2012.46059

Abstract

Validity of CA-Markov in land use and cover change simulation was investigated at the Langat Basin, Selangor, Malaysia. CA-Markov validation was performed using validation metrics, allocation disagreement, quantity disagreement, and figure of merit in a three-dimensional space. The figure of merit, quantity error, and allocation error for total landscape simulation using the 1990-1997 calibration data were 5.62%, 3.53%, and 6.13%, respectively. CA-Markov showed a poor performance for land use and cover change simulation due to uncertainties in the source data, the model, and future land use and cover change processes in the study area.

Highlights

Land use change impacts biodiversity, water and radiation budgets, emission of green house gases, carbon cycling, and livelihoods
CA-Markov was chosen to simulate land use change based on the following requirements: dynamic simulation capability, high efficiency with data scarcity, simple calibration, ability to simulate multiple land covers and complex patterns
Calibration of CA-Markov was done based on the changes in land cover over the period 1990-1997 (Figure 4)

Summary

Introduction

Land use change impacts biodiversity, water and radiation budgets, emission of green house gases, carbon cycling, and livelihoods. The study of Land Use and Cover Change (LUCC) and its dynamics is crucial for environmental management, especially with regard to sustainable agriculture and forestry. In terms of structure and application, have been used to understand LUCC dynamics [1,2]. As emphasized by Verburg et al (2004) [3], Chen and Pontius (2006) [4], and Luo et al (2010) [5], LUCC models are fundamentally different, and have their own capabilities and limitations. Performance comparison of LUCC models is very difficult. CA-Markov was chosen to simulate land use change based on the following requirements: dynamic simulation capability, high efficiency with data scarcity, simple calibration, ability to simulate multiple land covers and complex patterns

Objectives

Methods

Results