4.5 Article

Evaluation of Model Validation Techniques in Land Cover Dynamics

Journal

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Volume 2, Issue 3, Pages 577-597

Publisher

MDPI
DOI: 10.3390/ijgi2030577

Keywords

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

Funding

  1. Monash University, Australia
  2. Monash International Postgraduate Research Scholarship (MIPRS)
  3. Monash Graduate Scholarship (MGS)

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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.

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