Detecting Land-Cover Change using Stochastic Simulation Models and Multivariate Analysis of Multi-Temporal Landsat Data for Cass County, North Dakota

Buddhika Madurapperuma, Peter Oduor, Larry Kotchman Kotchman

Abstract


Understanding forest transiting at wildland-urban interfaces offers a glimpse into the effect of anthropogenic activities that may threaten biota.We examined forest conversion from 2006 to 2011 at urban-wildland fringes in Cass County, North Dakota. Grid data from the National Agricultural Statistic Service, published by USDA, was used as preliminary inputs to ascertain land-use and land-cover dynamics. Markovian transition probabilities were derived for each pair of years from 2006 to 2011. These transition probabilities were further subjected to multivariate analysis to detect forest change in one-year time steps. From this study, pairwise combinations of years yielded two distinct statistical groups. The first group comprised of seven pairs of year combinations displaying high transition probability of unchanged forest (0.54 ? Pff ? 0.68), while the second group comprised of eight pairs of year combinations and showed a low transition probability of unchanged forest (0.26 ? Pff ? 0.37). A third group displayed comparatively high transition probabilities of forest transiting to non-forest (0.26 ? Pfnf ? 0.36), such as forest to row crops, with an increasing trend over time. We also generated the forest cover in relation to soil characteristics. We can surmise that forest cover at poorly drained soils showed a higher distribution, which could be due to the unsuitability of this soil for crop cultivation. The results of this study on how land-cover has changed in Cass County for the last six years could be used by policy makers and forest managers in applying BMPs (Best Management Practices).


Full Text: PDF DOI: 10.5539/enrr.v3n4p78

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Environment and Natural Resources Research   ISSN 1927-0488 (Print)   ISSN 1927-0496 (Online)

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