Woodcock, C.E., Strahler, A.H. and Jupp, D.L.B. (1988) The Use of the Variogram in Remote Sensing: II. Real Digital Images. Remote Sensing of Environments, 25, 349-379.
https://doi.org/10.1016/0034-4257(88)90109-5

has been cited by the following article:

• TITLE: Uncertainty Analysis of Spatial Autocorrelation of Land-Use and Land-Cover Data within Pipestem Creek in North Dakota

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

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

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.5 No.8, August 2, 2017

  ABSTRACT: 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.