Assessing long-term variations in sagebrush habitat: characterization of spatial extents and distribution patterns using multi-temporal satellite remote-sensing data

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.