PLANTED: A Dataset for Planted Forest Identification from Multi-Satellite Time Series

Protecting and restoring forest ecosystems is critical for bio-diversity conservation and climate change mitigation. Forest monitoring on a global scale is essential for prioritizing and assessing conservation efforts. Satellite-based remote sensing is the only viable solution for providing global coverage, but to date, large-scale forest monitoring is limited mostly to single modalities or single time points. In this paper, we present a dataset consisting of data from five public satellites for recognizing forest plantations and planted tree species across the globe. Each satellite modality consists of a multi-year time series. The dataset, named "Planted" includes over 2M examples of 64 tree label classes (46 genera and 40 distinctive species), distributed among 41 countries. This dataset is released to foster research in forest monitoring using multimodal, multi-scale, multi-temporal data sources. Additionally, we present initial baseline results and evaluate modality fusion and data augmentation approaches for this dataset.