Evaluation of Model Validation Techniques in Land Cover Dynamics

ISPRS International Journal of Geo-Information

Bayes Ahmed¹  Raquib Ahmed² 

[1] School of Geography & Environmental Science, Building 11, Clayton Campus, Monash University, Melbourne, Victoria 3800, Australia; E-Mail:;Department of Geography & Environmental Studies, University of Rajshahi, Rajshahi 6205, Bangladesh; E-Mail:

关键词: model validation;    map comparison;    land cover change;    Kappa;    fuzzy;    Markov chain;    cellular automata;    artificial neural network;    three map comparison;   

DOI  :  10.3390/ijgi2030577

来源: mdpi

【 摘 要 】

This paper applies different methods of map comparison to quantify the characteristics of three different land change models. The land change models used for simulation are termed as “Stochastic Markov (St_Markov)”, “Cellular Automata Markov (CA_Markov)” and “Multi Layer Perceptron Markov (MLP_Markov)” models. Various model validation techniques such as per category method, kappa statistics, components of agreement and disagreement, three map comparison and fuzzy methods have then been applied. A comparative analysis of the validation techniques has also been discussed. In all cases, it is found that “MLP_Markov” gives the best results among the three modeling techniques. Fuzzy set theory is the method that seems best able to distinguish areas of minor spatial errors from major spatial errors. Based on the outcome of this paper, it is recommended that scientists should try to use the Kappa, three map comparison and fuzzy methods for model validation. This paper facilitates communication among land change modelers, because it illustrates the range of results for a variety of model validation techniques and articulates priorities for future research.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.