Treeline remote sensing: from tracking treeline shifts to multi‐dimensional monitoring of ecotonal change

Remote sensing applications have a long history in treeline research. Recentreviews have examined the topic mainly from a methodological point of view.Here, we propose a question-oriented review of remote sensing in treeline ecol-ogy to relate remote sensing methodologies to key ecological metrics and iden-tify knowledge gaps and promising areas for future research. We performed ameta-analysis to assess the role of remote sensing as a tool for measuring spatialpatterns and dynamics of alpine and Arctic treeline ecotone globally. Weassessed the geographic distribution, scale of analysis, and relationships betweenremote sensing techniques and treeline ecological metrics through co-occurrence mapping and multivariate statistics. Our analysis revealed that only10% of treeline ecology studies applied remote sensing tools, often associatedwith the keyword ‘climate change’. Monitoring studies adopted coarser spatialresolutions over longer temporal extents in comparison with other treelinestudies. A multiscale and multi-sensor spatial approach was implemented injust 19% of papers. Long-term research commonly relied on aerial and obliquephotography to measure treeline shifts through photointerpretation within amultidisciplinary framework. More recent treeline dynamics were often quanti-fied using greenness trends derived from the pixel-based classification of satel-lite images. Many recent short-term studies focused on delineating tree scalemetrics derived from the object-based classification of uncrewed aerial vehicle(UAV) images or LiDAR data. Over the past decade, high-resolution and low-cost UAV remote sensing has emerged as an interesting opportunity to fill thegap between local-scale ecological patterns and coarse-resolution satellite sen-sors. Additionally, treeline remote sensing applications would strongly benefitfrom multidisciplinary frameworks that integrate field studies in ecology andenvironmental science. The multi-dimensional structural complexity of treelinestypically responds to environmental drivers over multiple scales and thus is bestdescribed with multiscale and multi-sensor approaches.