Header menu link for other important links
Statistical independence test and validation of CA Markov land use land cover (LULC) prediction results
M.S. Mondal, , P.K. Garg, M. Kappas
Published in Elsevier B.V.
Volume: 19
Issue: 2
Pages: 259 - 272
Statistical independence test and validity of the CA (Cellular Automata) Markov process for projecting future land use and land cover (LULC) changes were carried out in this study. Predicting quantity and location changes have been analyzed, and statistically evaluated. Validity of the CA Markov process has been examined using various Kappa Index of Agreement (KIA or Kstandard) and related statistical variations on the KIA. Statistical test of independence (K2) was performed and markovian suitability has been checked using hypothesis of goodness of fit (Xc2). Hypothesis of statistical independence was rejected, which proved that land use land cover change trends are similar like previous development of land. With acceptance of the hypothesis of goodness of fit (Xc2) proved that actual transition probability of matrix is fitted with expected transition probability prepared using Markov chain method. Statistics indicates Kno, Klocation, Klocation Strata and Kstandard are 0.8347, 0.859, 0.8591 and 0.7928, respectively. © 2016 National Authority for Remote Sensing and Space Sciences
About the journal
Published in Elsevier B.V.
Open Access
Impact factor