Author(s)

Papia F. Rozario^1*, Peter G. Oduor², Larry Kotchman³, Michael Kangas⁴

¹Environmental & Conservation Sciences, North Dakota State University, Fargo, ND, USA.
²Department of Geosciences, North Dakota State University, Fargo, ND, USA.
³State Forester, North Dakota Forest Service, Molberg Forestry Center, Bottineau, ND, USA.
⁴Nursery & State Forest Team Leader, North Dakota State University, Fargo, ND, USA.

A major threat to biodiversity in North Dakota is the conversion of forested land to cultivable land, especially those that act as riparian buffers. To reverse this trend of transformation, a validation and prediction model is necessary to assess the change. Spatial prediction within a Geographic Information System (GIS) using Kriging is a popular stochastic method. The objective of this study was to predict spatial and temporal transformation of a small agricultural watershed—Pipestem Creek in North Dakota; USA using satellite imagery from 1976 to 2015. To enhance the difference between forested land and non-forested land, a spectral transformation method—Tasseled-Cap’s Greenness Index (TCGI) was used. To study the spatial structure present in the imagery within the study period, semivariograms were generated. The Kriging prediction maps were post-classified using Remote Sensing techniques of change detection to obtain the direction and intensity of forest to non-forest change. TCGI generated higher values from 1976 to 2000 and it gradually reduced from 2000 to 2011 indicating loss of forested land.

Kriging, Tasseled Cap, Greenness Index, Land-Use and Land-Cover

Rozario, P. F., Oduor, P. , Kotchman, L. and Kangas, M. (2017) Uncertainty Analysis of Spatial Autocorrelation of Land-Use and Land-Cover Data within Pipestem Creek in North Dakota. Journal of Geoscience and Environment Protection, 5, 71-88. doi: 10.4236/gep.2017.58008.