Abstract
An approach that can generate sagebrush habitat change estimates for monitoring large-area sagebrush ecosystems has been developed and tested in southwestern Wyoming, USA. This prototype method uses a satellite-based image change detection algorithm and regression models to estimate sub-pixel percentage cover for five sagebrush habitat components: bare ground, herbaceous, litter, sagebrush and shrub. Landsat images from three different months in 1988, 1996 and 2006 were selected to identify potential landscape change during these time periods using change vector (CV) analysis incorporated with an image normalization algorithm. Regression tree (RT) models were used to estimate percentage cover for five components on all change areas identified in 1988 and 1996, using unchanged 2006 baseline data as training for both estimates. Over the entire study area (24 950 km2), a net increase of 98.83 km2, or 0.7%, for bare ground was measured between 1988 and 2006. Over the same period, the other four components had net losses of 20.17 km2, or 0.6%, for herbaceous vegetation; 30.16 km2, or 0.7%, for litter; 32.81 km2, or 1.5%, for sagebrush; and 33.34 km2, or 1.2%, for shrubs. The overall accuracy for shrub vegetation change between 1988 and 2006 was 89.56%. Change patterns within sagebrush habitat components differ spatially and quantitatively from each other, potentially indicating unique responses by these components to disturbances imposed upon them.
Acknowledgements
We thank Debbie Meyer for selecting and providing Landsat imagery and certain GIS data layers. We thank Greg Fox, Austin Krcmarik, Chris Mahony, Katie Moon, Roger Pearce, Tracy Perfors, Sarah Rehme, John Severson and Greg Wann for their tireless efforts to collect all the field data, and Spencer Shell for his extraordinary efforts in the field. We also thank Dan Neubaum and Diana Keck for coordination of field crews. The Wyoming State office and the Lander Bureau of Land Management field office were instrumental in supporting this project, both logistically and financially. Specifically, we thank T. Rinkes, R. Vigil, K. Henke and D. Simpson for their support and interest in this research. We thank the USGS Central Region Office and all individuals involved with the Central Region Integrated Science Proposals and the Central Region's DOI on the Landscape Program for financial support. Drs James Vogelmann and Robert Klaver are also thanked for their suggestions to improve this article. Two anonymous reviewers are thanked for their constructive suggestions. Work by George Xian was performed under USGS contract 08HQCN0007.