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The Scientific World Journal
Volume 2013, Article ID 587284, 13 pages
http://dx.doi.org/10.1155/2013/587284
Research Article

Updating Categorical Soil Maps Using Limited Survey Data by Bayesian Markov Chain Cosimulation

1Department of Geography and Center for Environmental Sciences & Engineering, University of Connecticut, Storrs, CT 06269, USA
2Department of Statistics, University of Connecticut, Storrs, CT 06269, USA
3Center for Environmental Sciences & Engineering and Department of Ecology & Evolutionary Biology, University of Connecticut, Storrs, CT 06269, USA

Received 19 April 2013; Accepted 19 July 2013

Academic Editors: J. C. Domec and J. J. Wang

Copyright © 2013 Weidong Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [8 citations]

The following is the list of published articles that have cited the current article.

  • Weidong Li, Chuanrong Zhang, Michael R. Willig, Dipak K. Dey, Guiling Wang, and Liangzhi You, “Bayesian Markov Chain Random Field Cosimulation for Improving Land Cover Classification Accuracy,” Mathematical Geosciences, 2014. View at Publisher · View at Google Scholar
  • Weixing Zhang, Weidong Li, and Chuanrong Zhang, “Land cover post-classifications by Markov chain geostatistical cosimulation based on pre-classifications by different conventional classifiers,” International Journal of Remote Sensing, vol. 37, no. 4, pp. 926–949, 2016. View at Publisher · View at Google Scholar
  • Weixing Zhang, Weidong Li, Chuanrong Zhang, and Xiaojiang Li, “Incorporating Spectral Similarity Into Markov Chain Geostatistical Cosimulation for Reducing Smoothing Effect in Land Cover Postclassification,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 3, pp. 1082–1095, 2017. View at Publisher · View at Google Scholar
  • Weixing Zhang, Weidong Li, Chuanrong Zhang, and William B. Ouimet, “Detecting horizontal and vertical urban growth from medium resolution imagery and its relationships with major socioeconomic factors,” International Journal of Remote Sensing, vol. 38, no. 12, pp. 3704–3734, 2017. View at Publisher · View at Google Scholar
  • Andreas Langousis, Vassilios Kaleris, Angeliki Kokosi, and George Mamounakis, “Markov based transition probability geostatistics in groundwater applications: assumptions and limitations,” Stochastic Environmental Research and Risk Assessment, 2017. View at Publisher · View at Google Scholar
  • Weidong Li, and Chuanrong Zhang, “Comments on “Spatial hidden Markov chain models for estimation of petroleum reservoir categorical variables”,” Journal of Petroleum Exploration and Production Technology, 2017. View at Publisher · View at Google Scholar
  • Weixing Zhang, Weidong Li, Chuanrong Zhang, and Tian Zhao, “Parallel computing solutions for Markov chain spatial sequential simulation of categorical fields,” International Journal of Digital Earth, pp. 1–17, 2018. View at Publisher · View at Google Scholar
  • Adem Ersoy, and Tayfun Y. Yunsel, “Geochemical modelling and mapping of Cu and Fe anomalies in soil using combining sequential Gaussian co-simulation and local singularity analysis: a case study from Dedeyazı (Malatya) region, SE Turkey,” Geochemistry: Exploration, Environment, Analysis, pp. geochem2018-083, 2019. View at Publisher · View at Google Scholar