Monitoring temporal dynamics of rangelands to detect and understand change in vegetation cover and composition provides a wealth of information to improve management and sustainability. Remote sensing allows the evaluation of both abrupt and gradual rangeland change at unprecedented spatial and temporal extents. The National Land Cover Database (NLCD) has produced the Back in Time (BIT) dataset to quantify the percent cover of rangeland components (bare ground, herbaceous, annual herbaceous, litter, shrub, and sagebrush) across the western United States using Landsat imagery from 1985–2018. The BIT dataset was trained using a previously published circa 2016 fractional cover product developed with extensive ground measurements and Landsat imagery. Time-series BIT predictions were completed with regression tree modeling, change detection between and among years, and post-processing to ensure accurate post-burn trajectories. Noise and illogical change were eliminated in the predictions. In addition to capturing abrupt changes, scientists endeavored to track gradual change related to vegetation succession, interannual weather variation, and climate change. Key to this detection is the development of the change fraction approach, which considers yearly change in the context of the temporal variability of each pixel. Results were validated using data from long-term field monitoring sites and high-resolution time-series imagery, showing promising levels of correspondence. Data show that shrub, sagebrush, herbaceous, and litter cover decreased, and bare ground and annual herbaceous cover increased over the study period. The BIT data facilitate a comprehensive assessment of rangeland condition, evaluation of past management actions, understanding of system variability, and opportunities for future planning.
Component cover trends from 1985–2018 by Environmental Protection Agency Level III ecoregions.