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has been cited by the following article:

• TITLE: Transition Modeling of Land-Use Dynamics in the Pipestem Creek, North Dakota, USA

  AUTHORS: Papia F. Rozario, Peter Oduor, Larry Kotchman, Michael Kangas

  KEYWORDS: Markov Chain, LULC Change, Transition Probabilities

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.5 No.3, March 29, 2017

  ABSTRACT: Significant land-use changes in North Dakota have been reported and are widespread over the entire state. Such changing patterns may portend localized impairment to agricultural watersheds. In this study, Land-use Land-cover (LULC) change was modeled using geostatistics. The study area was within the Pipestem Creek watershed, a part of the Missouri Watershed James Subregion of North Dakota, USA. Landsat Thematic mapper images from the years 2007, 2011 and 2015 were used as preliminary data. LULC information for these datasets was acquired from the Global Land-cover facility and Landsat Program. Data analysis, spectral classification and post classification techniques were applied on the datasets. A transition matrix was derived using a Markov chain Monte Carlo (MCMC) model. This study demonstrates that the integration of satellite remote sensing, GIS and statistics may be an effective approach for analyzing the direction, rate, and spatial pattern of land-use change.