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Abstract Kelp species provide many ecosystem services associated with their three‐dimensional structures. Among these, fast‐growth, canopy‐forming species, like giant kelpMacrocystis pyrifera, are the foundation of kelp forests across many temperate reefs. Giant kelp populations have experienced regional declines in different parts of the world. Giant kelp canopy is very dynamic and can take years to recover from disturbance, challenging comparisons of standing biomass with historical baselines. The Santa Barbara Coastal LTER (SBC LTER), curates a time series of Landsat sensed surface cover and biomass for giant kelp in the west coast of North America. In the last decade, this resource has been fundamental to understanding the species' population dynamics and drivers. However, simple ready‐to‐use summary statistics aimed at classifying regional kelp decline or recovery are not readily available to stakeholders and coastal managers. To this end, we describe here two simple metrics made available through the R package kelpdecline. First, the proportion of Landsat pixels in decline (PPD), in which current biomass is compared with a historical baseline, and second, a pixel occupancy trend (POT), in which current year pixel occupancy is compared to the time‐series long probability of occupancy. The package produces raster maps and output tables summarizing kelp decline and trends over a 0.25 × 0.25° scale. Using kelpdecline, we show how sensitivity analysis onPPDparameter variation can increase the confidence of kelp decline estimates.