Abstract
In this Technical Advance, we describe a novel method to improve ecological interpretation of remotely sensed vegetation greenness measurements that involved sampling 24,395 Landsat pixels (30 m) across 639 km of Alaska's central Brooks Range. The method goes well beyond the spatial scale of traditional plot‐based sampling and thereby more thoroughly relates ground‐based observations to satellite measurements. Our example dataset illustrates that, along the boreal‐Arctic boundary, vegetation with the greatest Landsat Normalized Difference Vegetation Index (NDVI) is taller than 1 m, woody, and deciduous; whereas vegetation with lower NDVI tends to be shorter, evergreen, or non‐woody. The field methods and associated analyses advance efforts to inform satellite data with ground‐based vegetation observations using field samples collected at spatial scales that closely match the resolution of remotely sensed imagery.