frontiermetrics : An R Package for Characterizing Deforestation Frontiers

Abstract

Deforestation frontiers are regions where land use expands into forests, causing much of the world's biodiversity loss, carbon emissions, and ecosystem degradation. Recent advances in remote sensing now allow us to robustly monitor where forest loss occurs, yet our understanding of how deforestation progresses in space and time is limited. Such information is critical for ecological assessments, conservation planning, and sustainability initiatives more broadly. We introduce the R package frontiermetrics , a tool designed to derive a set of metrics that consistently and robustly characterize the deforestation process for downstream analyses in ecology and conservation. Specifically, frontiermetrics offers a flexible set of functions to calculate eight frontier metrics, including speed, severity, and spatio‐temporal patterns of forest loss. These metrics are embedded in a consistent workflow, ensuring repeatability and documentation, while offering users flexibility to adjust geographical extents and the spatial and temporal resolutions analyzed. We exemplify the usefulness of frontiermetrics with two case studies. One example uses Global Forest Watch time series of forest loss to compare frontier impacts on tropical forest ecosystems across diverse regions, while a second example highlights how frontier metrics based on user‐derived time series of deforestation can provide insights into protected‐area effectiveness. By offering a reproducible and standardized workflow, frontiermetrics facilitates frontier monitoring, supports evidence‐based conservation planning, and enables robust comparison of deforestation trends and patterns across regions and spatial scales.