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A Landscape Similarity Index Multitemporal Remote Sensing to Track Changes in Big Sagebrush Ecological Sites


A Landscape Similarity Index Multitemporal Remote Sensing to Track Changes in Big Sagebrush Ecological Sites



Rangeland Ecology and Management 66(1): 71-81



ISSN/ISBN: 1550-7424

DOI: 10.2111/rem-d-11-00195.1

A similarity index for big sagebrush ecological sites was developed in northern Utah. In contrast to field measurements used to calculate similarity to reference states, our approach relies on the utilization of historic archives of satellite imagery to measure the ecological distance to benchmarks of undesired conditions such as invasion by exotic annuals and woodland encroachment. Our benchmarks consisted of locations for which there are field data collected for monitoring and evaluation purposes for several time periods. We utilized a temporal series of Landsat thematic mapper (TM) imagery that spanned 1984 to 2008 from which the soil-adjusted vegetation index (SAVI) and other transformations were extracted. Topographic and climatic variables were also included as ancillary data. Multidimensional scaling (MDS) was used to obtain scores in reduced ordination space for two periods of interest: 1984 1996 and 1997 2008. Interannual SAVI mean-variance plots provided evidence that the benchmarks and ecological sites have a distinct temporal response that allows an objective comparison. Our MDS results also show that natural clusters can be identified in the reduced statistical space for ecological sites that are a dominant component of a soil map unit. The two MDS solutions allowed the ordination of ecological sites in two gradients of productivity and bare ground. Interpretations of the transitions and trajectories of mountain, Wyoming, and basin big sagebrush sites correlated well with the ecological expectation. We anticipate that range conservationists and others actively working in rangeland evaluation can use this application to develop and update ecological site descriptions and state-and-transition models from a remotely sensed perspective.

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Accession: 036741744

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